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Presented August 19, 2015 at NoSQL NOW in San Jose, California.<button type="button" class="Button_root__i1yp0 Button_primary__K25Gq Button_text__ZT_3O Button_small__sqsEx Description_less__BvWbY Description_hidden__a9QZJ" data-testid="button" aria-label="Read less"><span>Read less</span></button></p></div><button type="button" class="Button_root__i1yp0 Button_primary__K25Gq Button_text__ZT_3O Button_small__sqsEx Description_more__ChrRK" data-testid="button" aria-label="Read more" data-cy="read-more-button"><span>Read more</span></button></div></div><div class="MetadataToolbar_root__c03ao metadata-toolbar" data-cy="slideshow-toolbar"><div class="MetadataToolbar_wrapper__r7XEc"><div class="actions Actions_root__00yIC"><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_regular__i28NX Button_icon__1C4qi like-button unliked" data-testid="button" aria-label="Like" data-favorited="false" data-cy="like-button" aria-haspopup="dialog" aria-controls=":R2654f6:" popovertarget=":R2654f6:" style="anchor-name:--popover-R2654f6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/like.3870b074.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2654f6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2654f6"></div><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_regular__i28NX Button_icon__1C4qi save-slideshow-button SaveToListButton_root__T0ltL" data-testid="button" aria-label="Save for later" data-cy="save-slideshow-logged-out-button" aria-haspopup="dialog" aria-controls=":R3654f6:" popovertarget=":R3654f6:" style="anchor-name:--popover-R3654f6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R3654f6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R3654f6"></div><button type="button" class="unstyled-button more-button MoreDropdownButton_trigger__x7wGs" aria-label="More options" data-cy="more-options-icon" data-testid="ellipsis" aria-haspopup="dialog" aria-controls=":Rc654f6:" popovertarget=":Rc654f6:" style="anchor-name:--popover-Rc654f6"><span class="icon Icon_root__AjZyv" style="anchor-name:--popover-R3c654f6" aria-haspopup="dialog" aria-controls=":R3c654f6:" popovertarget=":R3c654f6:"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/more-horizontal.f69be1b8.svg);background-color:currentColor"></span><span class="sr-only"></span></span><div class="Tooltip_root__7FS0Y" id=":R3c654f6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R3c654f6"></div></button><div class="" id=":Rc654f6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rc654f6"></div></div><span data-cy="page-number" class="MetadataToolbar_pageNumber__i6Bhj">1 of 50</span><div class="MetadataToolbar_actions__FB33C"><div class="DownloadButton_root__adY00"><button type="button" class="Button_root__i1yp0 Button_primary__K25Gq Button_contained__gyjai Button_large__Yv_oe" data-testid="download-button" data-cy="download-button-toolbar"><span><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/download.b1b2622c.svg);background-color:currentColor"></span><span class="sr-only"></span></span>Download now</span></button><span class="Text_root__is73U Text_secondary__EPWj0 Text_xsmall__vYp9p text" style="-webkit-line-clamp:0">Downloaded 356 times</span></div></div><div class="MetadataToolbar_underline__QQn0C"></div></div></div><div class="player Player_root__L1AmF"><div id="new-player" class="vertical-player VerticalPlayer_root__K8_YS" data-slideshow-id="51792873"><div><div id="slide1" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-0" alt="The Gremlin Graph Traversal Language Marko A. Rodriguez and Daniel Kuppitz http://tinkerpop.incubator.apache.org " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="eager" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-1-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-1-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-1-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-1-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide2" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-1" alt="user movie categoryoccupation occupation rated category name:String gender:[M,F] age:integer name:String year:integer name:String stars:[1,2,3,4,5] http://grouplens.org/datasets/movielens/ MovieLens Dataset " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-2-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-2-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-2-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-2-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide3" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-2" alt="user |Vuser| = 6040 |Vmovie| = 3883 movie |Vcategory| = 18 category |Voccupation| = 21 occupation occupation |Eoccupation| = 6040 rated |Erated| = 1000209 category |Ecategory| = 6408 name:String gender:[M,F] age:integer name:String year:integer name:String stars:[1,2,3,4,5] http://grouplens.org/datasets/movielens/ G = (V, E) MovieLens Dataset " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-3-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-3-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-3-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-3-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide4" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-3" alt="~/tinkerpop3$ bin/gremlin.sh gremlin> " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-4-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-4-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-4-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-4-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide5" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-4" alt="~/tinkerpop3$ bin/gremlin.sh ,,,/ (o o) -----oOOo-(3)-oOOo----- plugin activated: tinkerpop.server plugin activated: tinkerpop.utilities plugin activated: tinkerpop.tinkergraph gremlin> " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-5-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-5-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-5-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-5-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide6" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-5" alt="~/tinkerpop3$ bin/gremlin.sh ,,,/ (o o) -----oOOo-(3)-oOOo----- plugin activated: tinkerpop.server plugin activated: tinkerpop.utilities plugin activated: tinkerpop.tinkergraph gremlin> Gremlin-Java8 Gremlin-Groovy* Gremlin-Scala Gremlin-Clojure Gremlin-JavaScript Gremlin-Python Gremlin-PHP ... " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-6-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-6-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-6-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-6-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide7" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-6" alt="~/tinkerpop3$ bin/gremlin.sh ,,,/ (o o) -----oOOo-(3)-oOOo----- plugin activated: tinkerpop.server plugin activated: tinkerpop.utilities plugin activated: tinkerpop.tinkergraph gremlin> graph = TinkerGraph.open() ==>tinkergraph[vertices:0 edges:0] gremlin> "Create a new TinkerGraph." " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-7-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-7-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-7-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-7-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide8" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-7" alt="~/tinkerpop3$ bin/gremlin.sh ,,,/ (o o) -----oOOo-(3)-oOOo----- plugin activated: tinkerpop.server plugin activated: tinkerpop.utilities plugin activated: tinkerpop.tinkergraph gremlin> graph = TinkerGraph.open() ==>tinkergraph[vertices:0 edges:0] gremlin> "Create a new TinkerGraph." G = (V = ∅, E = ∅) G The graph is a set of vertices and edges V The set of vertices in the graph E The set of edges in the graph ∅ The empty set -- no elements " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-8-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-8-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-8-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-8-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide9" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-8" alt="~/tinkerpop3$ bin/gremlin.sh ,,,/ (o o) -----oOOo-(3)-oOOo----- plugin activated: tinkerpop.server plugin activated: tinkerpop.utilities plugin activated: tinkerpop.tinkergraph gremlin> graph = TinkerGraph.open() ==>tinkergraph[vertices:0 edges:0] gremlin> "Create a new TinkerGraph." G = (V = ∅, E = ∅) TitanGraph.open(…) Neo4jGraph.open(…) OrientGraph.open(…) SqlgGraph.open(…) HadoopGraph.open(…) GiraphGraphComputer SparkGraphComputer ElasticGraph.open(…) ... " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-9-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-9-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-9-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-9-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide10" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-9" alt="G = (V = ∅, E ⊆ (V × V )) ~/tinkerpop3$ bin/gremlin.sh ,,,/ (o o) -----oOOo-(3)-oOOo----- plugin activated: tinkerpop.server plugin activated: tinkerpop.utilities plugin activated: tinkerpop.tinkergraph gremlin> graph = TinkerGraph.open() ==>tinkergraph[vertices:0 edges:0] gremlin> graph.io(gryo()).readGraph('/tmp/movie-lens.kryo') ==>null gremlin> "Load the MovieLens dataset into the newly created TinkerGraph." Set A is a subset of (or equal to) set B The set of all ordered pairs of vertices (directed binary edges) A ⊆ B (V × V ) " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-10-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-10-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-10-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-10-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide11" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-10" alt="~/tinkerpop3$ bin/gremlin.sh ,,,/ (o o) -----oOOo-(3)-oOOo----- plugin activated: tinkerpop.server plugin activated: tinkerpop.utilities plugin activated: tinkerpop.tinkergraph gremlin> graph = TinkerGraph.open() ==>tinkergraph[vertices:0 edges:0] gremlin> graph.io(gryo()).readGraph('/tmp/movie-lens.kryo') ==>null gremlin> g = graph.traversal() ==>graphtraversalsource[tinkergraph[vertices:9962 edges:1012657], standard] gremlin> "Create a graph traversal source for spawning graph traversals over the MovieLens graph." " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-11-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-11-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-11-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-11-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide12" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-11" alt="~/tinkerpop3$ bin/gremlin.sh ,,,/ (o o) -----oOOo-(3)-oOOo----- plugin activated: tinkerpop.server plugin activated: tinkerpop.utilities plugin activated: tinkerpop.tinkergraph gremlin> graph = TinkerGraph.open() ==>tinkergraph[vertices:0 edges:0] gremlin> graph.io(gryo()).readGraph('/tmp/movie-lens.kryo') ==>null gremlin> g = graph.traversal() ==>graphtraversalsource[tinkergraph[vertices:9962 edges:1012657], standard] gremlin> g.V().count() ==>9962 gremlin> "Count the number of vertices in the graph." |V | = 9962 " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-12-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-12-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-12-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-12-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide13" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-12" alt="~/tinkerpop3$ bin/gremlin.sh ,,,/ (o o) -----oOOo-(3)-oOOo----- plugin activated: tinkerpop.server plugin activated: tinkerpop.utilities plugin activated: tinkerpop.tinkergraph gremlin> graph = TinkerGraph.open() ==>tinkergraph[vertices:0 edges:0] gremlin> graph.io(gryo()).readGraph('/tmp/movie-lens.kryo') ==>null gremlin> g = graph.traversal() ==>graphtraversalsource[tinkergraph[vertices:9962 edges:1012657], standard] gremlin> g.V().count() ==>9962 gremlin> "Count the number of vertices in the graph." |V | = 9962 Vertex map 9962 reducing barrier Long seed=0 value=seed binary operator: value -> value+1 count() { "m any-to-one" " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-13-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-13-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-13-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-13-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide14" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-13" alt="Edge map 1012657 reducing barrier Long |E| = 1012657 ~/tinkerpop3$ bin/gremlin.sh ,,,/ (o o) -----oOOo-(3)-oOOo----- plugin activated: tinkerpop.server plugin activated: tinkerpop.utilities plugin activated: tinkerpop.tinkergraph gremlin> graph = TinkerGraph.open() ==>tinkergraph[vertices:0 edges:0] gremlin> graph.io(gryo()).readGraph('/tmp/movie-lens.kryo') ==>null gremlin> g = graph.traversal() ==>graphtraversalsource[tinkergraph[vertices:9962 edges:1012657], standard] gremlin> g.V().count() ==>9962 gremlin> g.E().count() ==>1012657 gremlin> "Count the number of edges in the graph." count() { "m any-to-one" " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-14-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-14-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-14-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-14-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide15" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-14" alt="~/tinkerpop3$ bin/gremlin.sh ,,,/ (o o) -----oOOo-(3)-oOOo----- plugin activated: tinkerpop.server plugin activated: tinkerpop.utilities plugin activated: tinkerpop.tinkergraph gremlin> graph = TinkerGraph.open() ==>tinkergraph[vertices:0 edges:0] gremlin> graph.io(gryo()).readGraph('/tmp/movie-lens.kryo') ==>null gremlin> g = graph.traversal() ==>graphtraversalsource[tinkergraph[vertices:9962 edges:1012657], standard] gremlin> g.V().count() ==>9962 gremlin> g.E().count() ==>1012657 gremlin> g.V().label().groupCount() ==>[occupation:21, movie:3883, category:18, user:6040] gremlin> "For each vertex in the graph, emit its label, then group and count each distinct label." user user movie category ... Vertex String Map<String,Long> user user movie category map map reducing barrier [ occupation=21, movie=3883, category=18, user=6040 ] label() groupCount(){"one-to-one" "many-to-one" " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-15-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-15-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-15-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-15-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide16" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-15" alt="~/tinkerpop3$ bin/gremlin.sh ,,,/ (o o) -----oOOo-(3)-oOOo----- plugin activated: tinkerpop.server plugin activated: tinkerpop.utilities plugin activated: tinkerpop.tinkergraph gremlin> graph = TinkerGraph.open() ==>tinkergraph[vertices:0 edges:0] gremlin> graph.io(gryo()).readGraph('/tmp/movie-lens.kryo') ==>null gremlin> g = graph.traversal() ==>graphtraversalsource[tinkergraph[vertices:9962 edges:1012657], standard] gremlin> g.V().count() ==>9962 gremlin> g.E().count() ==>1012657 gremlin> g.V().label().groupCount() ==>[occupation:21, movie:3883, category:18, user:6040] gremlin> g.E().hasLabel('rated').values('stars').mean() ==>3.581564453029317 gremlin> "For each rated-edge in the graph, emit its stars property value and compute the average value." " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-16-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-16-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-16-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-16-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide17" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-16" alt="~/tinkerpop3$ bin/gremlin.sh ,,,/ (o o) -----oOOo-(3)-oOOo----- plugin activated: tinkerpop.server plugin activated: tinkerpop.utilities plugin activated: tinkerpop.tinkergraph gremlin> graph = TinkerGraph.open() ==>tinkergraph[vertices:0 edges:0] gremlin> graph.io(gryo()).readGraph('/tmp/movie-lens.kryo') ==>null gremlin> g = graph.traversal() ==>graphtraversalsource[tinkergraph[vertices:9962 edges:1012657], standard] gremlin> g.V().count() ==>9962 gremlin> g.E().count() ==>1012657 gremlin> g.V().label().groupCount() ==>[occupation:21, movie:3883, category:18, user:6040] gremlin> g.E().hasLabel('rated').values('stars').mean() ==>3.581564453029317 gremlin> g.V().hasLabel('user').map(outE('rated').count()).max() ==>2314 gremlin> "What is the maximum number of movies a single user rated?" " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-17-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-17-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-17-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-17-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide18" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-17" alt="~/tinkerpop3$ bin/gremlin.sh ,,,/ (o o) -----oOOo-(3)-oOOo----- plugin activated: tinkerpop.server plugin activated: tinkerpop.utilities plugin activated: tinkerpop.tinkergraph gremlin> graph = TinkerGraph.open() ==>tinkergraph[vertices:0 edges:0] gremlin> graph.io(gryo()).readGraph('/tmp/movie-lens.kryo') ==>null gremlin> g = graph.traversal() ==>graphtraversalsource[tinkergraph[vertices:9962 edges:1012657], standard] gremlin> g.V().count() ==>9962 gremlin> g.E().count() ==>1012657 gremlin> g.V().label().groupCount() ==>[occupation:21, movie:3883, category:18, user:6040] gremlin> g.E().hasLabel('rated').values('stars').mean() ==>3.581564453029317 gremlin> g.V().hasLabel('user').map(outE('rated').count()).max() ==>2314 gremlin> g.V().hasLabel('movie').values('year').min() ==>1919 gremlin> "What year was the oldest movie made?" " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-18-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-18-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-18-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-18-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide19" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-18" alt="gremlin> g.V().hasLabel('category').values('name') ==>Animation ==>Children's ==>Comedy ==>Adventure ==>Fantasy ==>Romance ==>Drama ==>Action ==>Crime ==>Thriller ==>Horror ==>Sci-Fi ==>Documentary ==>War ==>Musical ==>Mystery ==>Film-Noir ==>Western "For each vertex that is labeled 'category,' emit the name property value of that vertex." category user user movie category Vertex category category category category category categorycategory category Vertex Animation Children's Comedy Adventure Western ... String ﬁlter map hasLabel('category') values('name') "one-to-[one-or-none]" "one-to-one" " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-19-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-19-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-19-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-19-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide20" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-19" alt="gremlin> g.V().hasLabel('category').as('a','b'). select('a','b'). by('name'). by(inE('category').count()) "For each category vertex, emit a map of its name and the number of movies it represents." " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-20-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-20-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-20-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-20-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide21" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-20" alt="hasLabelcategory : V ∗ → V ∗ gremlin> g.V().hasLabel('category').as('a','b'). select('a','b'). by('name'). by(inE('category').count()) "For each category vertex, emit a map of its name and the number of movies it represents." V : G → V ∗ asa,b : V ∗ → (V × V )∗ G The set of all graphs f : A → B The function f maps values of type A to values of type B A∗ A stream of values of type A (A × B) The set of all pairs of values from A and B (cross product) N The set of all natural numbers (1, 2, 3, 4, …) The set of all strings (a, b, aa, ab, bb, …) selecta,b : (V × V )∗ → a valuesname : V ∗ → S b (inEcategory : V ∗ → E∗ ) ◦ (count : E∗ → N) → (S × N)∗ S Σ∗ typically denoted " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-21-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-21-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-21-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-21-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide22" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-21" alt="gremlin> g.V().hasLabel('category').as('a','b'). select('a','b'). by('name'). by(inE('category').count()) ==>[a:Animation, b:105] ==>[a:Children's, b:251] ==>[a:Comedy, b:1200] ==>[a:Adventure, b:283] ==>[a:Fantasy, b:68] ==>[a:Romance, b:471] ==>[a:Drama, b:1603] ==>[a:Action, b:503] ==>[a:Crime, b:211] ==>[a:Thriller, b:492] ==>[a:Horror, b:343] ==>[a:Sci-Fi, b:276] ==>[a:Documentary, b:127] ==>[a:War, b:143] ==>[a:Musical, b:114] ==>[a:Mystery, b:106] ==>[a:Film-Noir, b:44] ==>[a:Western, b:68] "For each category vertex, emit a map of its name and the number of movies it represents." category user user movie category Vertex category category category category category categorycategory category Vertex [a:Animation, b:105] [a:Children's, b:251] [a:Comedy, b:1200] [a:Adventure, b:283] … [a:Western, b:68] Map<String,Long> ﬁlter map category name:Animation category category category ... category map map reducing barrier 105 Vertex Edge Long category name:Animation Vertex String map Animationa b map ﬂatMap {"one-to-m any" "one-to-one" " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-22-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-22-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-22-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-22-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide23" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-22" alt="gremlin> g.V().hasLabel('movie').as('a','b'). select('a','b'). by('name'). by(inE('rated').values('stars').mean()). order().by(select('b'),decr). limit(10) "For each movie, emit a map of its name and average rating. Sort the maps in decreasing order by their average rating. Emit the ﬁrst 10 maps (i.e. top 10)." " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-23-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-23-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-23-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-23-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide24" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-23" alt="gremlin> g.V().hasLabel('movie').as('a','b'). select('a','b'). by('name'). by(inE('rated').values('stars').mean()). order().by(select('b'),decr). limit(10) ==>[a:Charm's Incidents, b:NaN] ==>[a:Prerokbe Ognja, b:NaN] ==>[a:Leopard Son, The, b:NaN] ==>[a:Bird of Prey, b:NaN] ==>[a:Plutonium Circus, b:NaN] ==>[a:Hustler White, b:NaN] ==>[a:Curtis's Charm, b:NaN] ==>[a:Three Lives and Only One Death, b:NaN] ==>[a:Hoogste tijd, b:NaN] ==>[a:Entertaining Angels: The Dorothy Day Story, b:NaN] category user user movie category Vertex movie movie movie movie movie moviemovie movie Vertex [a:Charm's Incidents, b:NaN] [a:Prerokbe Ognja, b:NaN] [a:Leopard Son, The, b:NaN] [a:Bird of Prey, b:NaN] ... [a:Entertaining Angels, b:NaN] Map<String,Double> ﬁlter map movie name:Charm's Incidents map reducing barrier NaN Vertex Edge Double movie name:Charm's Incidents Vertex String map Charm's Incidentsa b map map Integer ... "For each movie, emit a map of its name and average rating. Sort the maps in decreasing order by their average rating. Emit the ﬁrst 10 maps (i.e. top 10)." ﬂatMap " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-24-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-24-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-24-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-24-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide25" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-24" alt="gremlin> g.V().hasLabel('movie').as('a','b'). select('a','b'). by('name'). by(coalesce( inE('rated').values('stars'), constant(0)).mean()). order().by(select('b'),decr). limit(10) ==>[a:Lured, b:5.0] ==>[a:One Little Indian, b:5.0] ==>[a:Bittersweet Motel, b:5.0] ==>[a:Gate of Heavenly Peace, The, b:5.0] ==>[a:Follow the Bitch, b:5.0] ==>[a:Schlafes Bruder (Brother of Sleep), b:5.0] ==>[a:Ulysses (Ulisse), b:5.0] ==>[a:Song of Freedom, b:5.0] ==>[a:Smashing Time, b:5.0] ==>[a:Baby, The, b:5.0] "For each movie, get its name and mean rating (or 0 if no ratings). Order by average rating and emit top 10." user user movie category Vertex movie movie movie movie moviemovie movie Vertex Map<String,Double> ﬁlter map movie name:Charm's Incidents map map reducing barrier 0.0 Vertex Integer Double movie name:Charm's Incidents Vertex String map Charm's Incidentsa b map 0 [a:Lured, b:5.0] [a:One Little Indian, b:5.0] [a:Bittersweet Motel, b:5.0] [a:Gate of Heavenly Peace, b:5.0] ... [a:Baby, The, b:5.0] Map<String,Double> map [a:Charm's Incidents, b:NaN] [a:Prerokbe Ognja, b:NaN] [a:Leopard Son, The, b:NaN] [a:Bird of Prey, b:NaN] ... [a:Entertaining Angels, b:NaN] collecting barrier " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-25-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-25-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-25-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-25-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide26" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-25" alt="gremlin> g.V().hasLabel('movie').as('a','b'). where(inE('rated').count().is(gt(10))). select('a','b'). by('name'). by(inE('rated').values('stars').mean()). order().by(select('b'),decr). limit(10) "For each movie with at least 11 ratings, emit a map of its name and average rating. Sort the maps in decreasing order by their average rating. Emit the ﬁrst 10 maps (i.e. top 10)." " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-26-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-26-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-26-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-26-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide27" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-26" alt="gremlin> g.V().hasLabel('movie').as('a','b'). where(inE('rated').count().is(gt(10))). select('a','b'). by('name'). by(inE('rated').values('stars').mean()). order().by(select('b'),decr). limit(10) ==>[a:Sanjuro, b:4.608695652173913] ==>[a:Seven Samurai (The Magnificent Seven), b:4.560509554140127] ==>[a:Shawshank Redemption, The, b:4.554557700942973] ==>[a:Godfather, The, b:4.524966261808367] ==>[a:Close Shave, A, b:4.52054794520548] ==>[a:Usual Suspects, The, b:4.517106001121705] ==>[a:Schindler's List, b:4.510416666666667] ==>[a:Wrong Trousers, The, b:4.507936507936508] ==>[a:Sunset Blvd. (a.k.a. Sunset Boulevard), b:4.491489361702127] ==>[a:Raiders of the Lost Ark, b:4.47772] "For each movie with at least 11 ratings, emit a map of its name and average rating. Sort the maps in decreasing order by their average rating. Emit the ﬁrst 10 maps (i.e. top 10)." map movie name:Sanjuro rated rated rated ... rated map reducing barrier 4.60 Vertex Edge Double movie name:Sanjuro Vertex String map Sanjuroa b map map Integer user user movie category Vertex movie movie movie movie moviemovie movie Vertex ﬁlter movie rated rated rated ... rated reducing barrier Vertex Edge map Long 69 name:Sanjuro ﬁlter movie movie movie movie movie Vertex 5 4 … 5 [[a:Sanjuro, b:4.60] [a:Seven Samurai, b:4.56] [a:Shawshank Redemption, b:4.55] [a:Godfather, The, b:4.52] ... [a:Raiders of the Lost Ark, b:4.47] […] […] […] […] … […] Map<String,Double> Map<String,Double> map collecting barrier ﬂatMap ﬂatMap { { " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-27-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-27-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-27-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-27-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide28" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-27" alt="gremlin> g.V().hasLabel('movie'). where(inE('rated').count().is(gt(10))). toString() ==>[GraphStep([],vertex), HasStep([~label.eq(movie)]), TraversalFilterStep([ VertexStep(IN,[rated],edge), CountGlobalStep, IsStep(gt(10))])] "What is the execution plan for the traversal prior to compiler optimizations being applied?" V : G → V ∗ hasLabelmovie : V ∗ → V ∗ where : V ∗ → inErated : V ∗ → E∗ count : E∗ → N isgt(10) : N → (N ∪ ∅) → V ∗ "true orfalse" " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-28-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-28-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-28-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-28-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide29" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-28" alt="gremlin> g.V().hasLabel('movie'). where(inE('rated').count().is(gt(10))). iterate().toString() ==>[TinkerGraphStep(vertex,[~label.eq(movie)]), TraversalFilterStep([ VertexStep(IN,[rated],edge), RangeGlobalStep(0,11), CountGlobalStep, IsStep(gt(10))])] "What is the execution plan for the traversal after compiler optimizations have been applied?" * TinkerGraphStragegy: Access vendor-speciﬁc vertex partition by label. * RangeByIsCountStrategy: Only iterate 1 more than required count. where : V ∗ → inErated : V ∗ → E∗ count : E∗ → N isgt(10) : N → (N ∪ ∅) limit11 : E∗ → E∗ Vlabel=movie : G → V ∗ → V ∗ "true orfalse" " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-29-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-29-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-29-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-29-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide30" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-29" alt="gremlin> g.getStrategies() ==>ConjunctionStrategy a.and().b => and(a,b) a.or().b => or(a,b) a.or().b.and().c => or(a,and(b,c)) a.and().b.or().c => or(and(a,b),c) ==>IncidentToAdjacentStrategy a.outE().inV().b => a.out().b ==>AdjacentToIncidentStrategy a.in().count().b => a.inE().count().b a.where(out()).b => a.where(outE()).b a.and(in(),out()).b => a.and(inE(),outE()).b ==>IdentityRemovalStrategy a.identity().b => a.b ==>FilterRankingStrategy a.order().dedup().b => a.dedup().order().b a.and(c,d).has().b => a.has().and(c,d).b a.simplePath().where().b => b.where().simplePath().a ==>MatchPredicateStrategy a.match(c,d).where(e).b => a.match(c,d,e) a.match(has(),c,d).b => a.has().match(c,d).b ==>RangeByIsCountStrategy a.count().is(0) => a.limit(1).count().is(0) ==>TinkerGraphStepStrategy V.has().has().b => V[has,has].b ==>ProfileStrategy a.b.c.profile() => a.profile().b.profile().c.profile() ==>ComputerVerificationStrategy a.order.b => IllegalStateException a.local(out().out()).b => IllegalStateException "What compilation strategies are associated with the graph traversal source?" " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-30-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-30-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-30-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-30-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide31" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-30" alt="gremlin> g.V().has('movie','name','Die Hard'). inE('rated').values('stars').mean() ==>4.121848739495798 "What is Die Hard's average rating?" " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-31-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-31-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-31-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-31-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide32" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-31" alt="gremlin> g.V().has('movie','name','Die Hard'). inE('rated').values('stars').mean() ==>4.121848739495798 "What is Die Hard's average rating?" movie movie movie Vertex movie Vertex ﬁlter name:Die Hard ﬂatMap rated rated rated ... rated Edge map 3 5 5 … 4 Integer map Double 4.1218 reducing barrier V : G → V ∗ hasLabelmovie : V ∗ → V ∗ hasname=Die Hard : V ∗ → V ∗ inErated : V ∗ → E∗ mean : N∗ → R valuesstars : E∗ → N∗ user user movie user Vertex ﬁlter { "one-to-[one-or-none]" "one-to-[one-or-none]" "one-to-many" "one-to-one" "many-to-one" " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-32-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-32-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-32-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-32-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide33" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-32" alt="gremlin> g.V().has('movie','name','Die Hard').as('a'). inE('rated').has('stars',5).outV(). where(out('occupation').has('name','programmer')). outE('rated').has('stars',5).inV(). where(neq('a')). groupCount().by('name'). order(local).by(valueDecr). limit(local,10). unfold() // so its not printed on a single line "Which programmers like Die Hard and what other movies do they like? Group and count the movies by their name. Sort the group count map in decreasing order by the count. Clip the map to the top 10 entries and stream out the map's entries (for display purposes)." " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-33-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-33-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-33-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-33-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide34" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-33" alt="gremlin> g.V().has('movie','name','Die Hard').as('a'). inE('rated').has('stars',5).outV(). where(out('occupation').has('name','programmer')). outE('rated').has('stars',5).inV(). where(neq('a')). groupCount().by('name'). order(local).by(valueDecr). limit(local,10). unfold() // so its not printed on a single line "Which programmers like Die Hard and what other movies do they like? Group and count the movies by their name. Sort the group count map in decreasing order by the count. Clip the map to the top 10 entries and stream out the map's entries (for display purposes)." user user movie user Vertex movie Vertex ﬁlter ﬁlter name:Die Hard ﬂatMap rated rated rated ... rated Edge ﬁlter rated ... rated Edge map Vertex user user user useruser user Vertex Vertex occupationﬂatMap Vertex ﬁlter rated rated rated ... rated Edge ﬁlter rated ... rated Edge map Vertex movie movie moviemovie movie Vertex Vertex user user user ﬂatMap ﬁlter movie Vertex ﬁlter Vertex movie movie movie map reducing barrier [ Aliens=105, Braveheart=24, … Pulp Fiction=19 ] Map<String,Long> map collecting barrier [ Raider of the Lost Ark=36, Star Wars: Episode V=24, Star Wars: Episode IV=34 … Airplane II: The Sequel=1 ] Map<String,Long> [ Raider of the Lost Ark=36, Star Wars: Episode V=24, Star Wars: Episode IV=34 … Alien=22 ] Map<String,Long> map occupation programmer not Die Hard " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-34-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-34-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-34-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-34-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide35" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-34" alt="gremlin> g.V().has('movie','name','Die Hard').as('a'). inE('rated').has('stars',5).outV(). where(out('occupation').has('name','programmer')). outE('rated').has('stars',5).inV(). where(neq('a')). groupCount().by('name'). order(local).by(valueDecr). limit(local,10). unfold() // so its not printed on a single line ==>Raiders of the Lost Ark=36 ==>Star Wars: Episode V - The Empire Strikes Back=36 ==>Star Wars: Episode IV - A New Hope=34 ==>Matrix, The=32 ==>Terminator, The=29 ==>Star Wars: Episode VI - Return of the Jedi=26 ==>Sixth Sense, The=26 ==>Braveheart=24 ==>Aliens=23 ==>Alien=22 gremlin> "Which programmers like Die Hard and what other movies do they like? Group and count the movies by their name. Sort the group count map in decreasing order by the count. Clip the map to the top 10 entries and stream out the map's entries (for display purposes)." " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-35-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-35-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-35-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-35-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide36" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-35" alt="gremlin> g.V(). match( __.as('a').hasLabel('movie'), __.as('a').out('category').has('name','Action'), __.as('a').has('year',between(1980,1990)), __.as('a').inE('rated').as('b'), __.as('b').has('stars',5), __.as('b').outV().as('c'), __.as('c').out('occupation').has('name','programmer'), __.as('c').has('age',between(30,40))). select('a').groupCount().by('name'). order(local).by(valueDecr). limit(local,10). unfold() // so its not printed on a single line "What 80's action movies do 30-something programmers like? Group count the movies by their name and sort the group count map in decreasing order by value. Clip the map to the top 10 and emit the map entries." " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-36-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-36-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-36-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-36-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide37" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-36" alt=""What 80's action movies do 30-something programmers like? Group count the movies by their name and sort the group count map in decreasing order by value. Clip the map to the top 10 and emit the map entries." gremlin> g.V(). match( __.as('a').hasLabel('movie'), __.as('a').out('category').has('name','Action'), __.as('a').has('year',between(1980,1990)), __.as('a').inE('rated').as('b'), __.as('b').has('stars',5), __.as('b').outV().as('c'), __.as('c').out('occupation').has('name','programmer'), __.as('c').has('age',between(30,40))). select('a').groupCount().by('name'). order(local).by(valueDecr). limit(local,10). unfold() // so its not printed on a single line ==>Raiders of the Lost Ark=26 ==>Star Wars: Episode V - The Empire Strikes Back=26 ==>Terminator, The=23 ==>Star Wars: Episode VI - Return of the Jedi=22 ==>Princess Bride, The=19 ==>Aliens=18 ==>Boat, The (Das Boot)=11 ==>Indiana Jones and the Last Crusade=11 ==>Star Trek: The Wrath of Khan=10 ==>Abyss, The=9 gremlin> " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-37-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-37-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-37-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-37-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide38" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-37" alt="MatchStep GraphTraversal.match(Traversal... traversalPatterns) x.match( a...b a...c c... or( a...c a...b ) c.repeat(...).b not(c...a) b...count().e c...count().e ).dedup(a,b).y a,b,c,e : once a variable is set, it must hold equal for all patterns c... : "predicate patterns" simply check for the existence of a result or()/and() : nested conjunctive patterns supported repeat(...) : recursive patterns supported not(...) : not'ing of patterns supported count() : barrier patterns supported dedup(a,b) : internal de-duplication of variable values supported x.match().y : possible to go from imperative to declarative, etc. Plug and Play MatchAlgorithms GreedyMatchAlgorithm : try each pattern in the order provided by the user CountMatchAlgorithm : continually re-sort patterns by the cardinality of their set reductions " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-38-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-38-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-38-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-38-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide39" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-38" alt="// CountMatchAlgorithm (default) gremlin> clockWithResult(50){ g.V().match( __.as('a').out('rated').as('b'), __.as('a').out('occupation').has('name','farmer')). select('a','b').count().next()} ==>66.31955294 // time in milliseconds ==>2706 // number of results // GreedyMatchAlgorithm gremlin> g = graph.traversal(GraphTraversalSource.build(). with(MatchAlgorithmStrategy.build(). algorithm(MatchStep.GreedyMatchAlgorithm).create())) ==>graphtraversalsource[tinkergraph[vertices:9962 edges:1012657], standard] gremlin> clockWithResult(50){ g.V().match( __.as('a').out('rated').as('b'), __.as('a').out('occupation').has('name','farmer')). select('a','b').count().next()} ==>1902.6290871599997 // time in milliseconds ==>2706 // number of results "Which movies did each farmer rate? -- benchmark CountMatchAlgorithm vs. GreedyMatchAlgorithm." farmermoviesusers 1000209 2706 farmer moviesusers 17 2706 " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-39-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-39-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-39-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-39-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide40" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-39" alt="gremlin> g.V().hasLabel('movie'). where(inE('rated').count().is(gt(10))). group(). by{((int)(it.value('year') / 10)) * 10}. by(). by(unfold().order(). by(inE('rated').values('stars').mean(),decr). values('name'). limit(1)). order(local).by(keyIncr). unfold() // so its not printed on a single line "What is the most liked movie in each decade?" " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-40-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-40-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-40-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-40-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide41" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-40" alt="gremlin> g.V().hasLabel('movie'). where(inE('rated').count().is(gt(10))). group(). by{((int)(it.value('year') / 10)) * 10}. by(). by(unfold().order(). by(inE('rated').values('stars').mean(),decr). values('name'). limit(1)). order(local).by(keyIncr). unfold() // so its not printed on a single line "What is the most liked movie in each decade?" λ λ Nearly every step that takes a traversal argument can also take a lambda. It is recommended that users do not use lambdas as they are not subject to traversal strategy (i.e. compiler) optimization. However, they are useful when no provided step yields the desired computation. " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-41-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-41-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-41-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-41-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide42" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-41" alt="gremlin> g.V().hasLabel('movie'). where(inE('rated').count().is(gt(10))). group(). by{((int)(it.value('year') / 10)) * 10}. by(). by(unfold().order(). by(inE('rated').values('stars').mean(),decr). values('name'). limit(1)). order(local).by(keyIncr). unfold() // so its not printed on a single line ==>1910=Daddy Long Legs ==>1920=General, The ==>1930=City Lights ==>1940=Third Man, The ==>1950=Seven Samurai (The Magnificent Seven) ==>1960=Sanjuro ==>1970=Godfather, The ==>1980=Raiders of the Lost Ark ==>1990=Shawshank Redemption, The ==>2000=Almost Famous gremlin> "What is the most liked movie in each decade?" " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-42-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-42-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-42-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-42-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide43" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-42" alt="gremlin> graph = HadoopGraph.open('conf/hadoop/movie-lens.properties') ==>hadoopgraph[gryoinputformat->gryooutputformat] gremlin> g = graph.traversal(computer(SparkGraphComputer)) ==>graphtraversalsource [hadoopgraph[gryoinputformat->gryooutputformat], sparkgraphcomputer] gremlin> "Which movies are most central in the implicit 5-stars graph?" " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-43-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-43-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-43-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-43-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide44" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-43" alt="gremlin> graph = HadoopGraph.open('conf/hadoop/movie-lens.properties') ==>hadoopgraph[gryoinputformat->gryooutputformat] gremlin> g = graph.traversal(computer(SparkGraphComputer)) ==>graphtraversalsource [hadoopgraph[gryoinputformat->gryooutputformat], sparkgraphcomputer] gremlin> g.V().repeat(outE('rated').has('stars', 5).inV(). groupCount('m').by('name'). inE('rated').has('stars', 5).outV()). times(4).cap('m') "Which movies are most central in the implicit 5-stars graph?" user movie user ratedrated m 4x cap('m') repeat(…).times(4) g.V() stars=5 stars=5 " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-44-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-44-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-44-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-44-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide45" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-44" alt="gremlin> graph = HadoopGraph.open('conf/hadoop/movie-lens.properties') ==>hadoopgraph[gryoinputformat->gryooutputformat] gremlin> g = graph.traversal(computer(SparkGraphComputer)) ==>graphtraversalsource [hadoopgraph[gryoinputformat->gryooutputformat], sparkgraphcomputer] gremlin> g.V().repeat(outE('rated').has('stars', 5).inV(). groupCount('m').by('name'). inE('rated').has('stars', 5).outV()). times(4).cap('m') ==>Fantasia 2000=2676505178171564 ==>Pale Rider=1369969000295362 ==>Crucible, The=401712993698149 ==>About Adam=37981148456999 ==>Akira=3659939409345918 ... gremlin> "Which movies are most central in the implicit 5-stars graph?" " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-45-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-45-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-45-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-45-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide46" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-45" alt="gremlin> graph = HadoopGraph.open('conf/hadoop/movie-lens.properties') ==>hadoopgraph[gryoinputformat->gryooutputformat] gremlin> g = graph.traversal(computer(SparkGraphComputer)) ==>graphtraversalsource [hadoopgraph[gryoinputformat->gryooutputformat], sparkgraphcomputer] gremlin> g.V().repeat(outE('rated').has('stars', 5).inV(). groupCount('m').by('name'). inE('rated').has('stars', 5).outV()). times(4).cap('m') ==>Fantasia 2000=2676505178171564 ==>Pale Rider=1369969000295362 ==>Crucible, The=401712993698149 ==>About Adam=37981148456999 ==>Akira=3659939409345918 ... gremlin> hdfs.ls('output/m') ==>rw-r--r-- daniel supergroup 0 _SUCCESS ==>rw-r--r-- daniel supergroup 245314 part-r-00000 gremlin> hdfs.head('output/m', ObjectWritable).sort {-it.value}.take(10) ==>Star Wars: Episode IV - A New Hope 35405394353105332 ==>American Beauty 31943228282020585 ==>Raiders of the Lost Ark 31224779793238499 ==>Star Wars: Episode V - The Empire Strikes Back 30434677119726223 ==>Godfather, The 30258518523013057 ==>Shawshank Redemption, The 28297717387901031 ==>Schindler's List 27539336654199309 ==>Silence of the Lambs, The 26736276376806173 ==>Fargo 26531050311325270 ==>Matrix, The 26395118239203191 "Which movies are most central in the implicit 5-stars graph?" " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-46-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-46-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-46-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-46-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide47" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-46" alt="gremlin> :plugin use tinkerpop.gephi ==>tinkerpop.gephi activated gremlin> :remote connect tinkerpop.gephi ==>Connection to Gephi - http://localhost:8080/workspace0 with stepDelay:1000, startRGBColor:[0.0, 1.0, 0.5], colorToFade:g, colorFadeRate:0.7, startSize: 20.0,sizeDecrementRate:0.33 gremlin> " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-47-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-47-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-47-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-47-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide48" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-47" alt="gremlin> :plugin use tinkerpop.gephi ==>tinkerpop.gephi activated gremlin> :remote connect tinkerpop.gephi ==>Connection to Gephi - http://localhost:8080/workspace0 with stepDelay:1000, startRGBColor:[0.0, 1.0, 0.5], colorToFade:g, colorFadeRate:0.7, startSize: 20.0,sizeDecrementRate:0.33 gremlin> :> g.V().hasLabel('user'). order(). by(outE('rated').count(), decr).limit(10).as('a'). local(outE('rated').order(). by('stars', decr). // first by stars by(inV().inE('rated').count(), decr). // then by ratings limit(10)). subgraph('sg').inV().outE('category'). subgraph('sg').select('a').outE('occupation'). subgraph('sg').cap('sg').next() ==>tinkergraph[vertices:82 edges:233] gremlin> "Which users rated the most movies? For each user, display their 10 favorite movies, the categories of those movies, and their occupation. "moviebuffs" " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-48-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-48-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-48-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-48-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide49" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-48" alt="The Gremlin Graph Traversal Language" class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-49-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-49-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-49-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-49-320.jpg" sizes="100vw"/></div></div></div><div><div id="slide50" class="VerticalSlide_root__jU_9r slide-item" style="aspect-ratio:733 / 576" data-cy="slide-container"><div class="VerticalSlideImage_root__64KSA"><img id="slide-image-49" alt="Thanks for listening… " class="vertical-slide-image VerticalSlideImage_image__VtE4p" data-testid="vertical-slide-image" loading="lazy" srcSet="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-50-320.jpg 320w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-50-638.jpg 638w, https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/75/The-Gremlin-Graph-Traversal-Language-50-2048.jpg 2048w" src="https://image.slidesharecdn.com/nosql-now-2015-150819035929-lva1-app6891/85/The-Gremlin-Graph-Traversal-Language-50-320.jpg" sizes="100vw"/></div></div></div></div></div><div id="sidebar" class="sidebar hide-scrollbar Sidebar_root__1BbNu" style="--slots:17"><div class="above-recs-ad-wrapper AboveRecsAd_root__iTmTR"><div class="AboveRecsAd_desktopAd__ymykj"><div class="freestar-ad-container FreestarAdContainer_root__qPPC_" style="--fallback-aspect-ratio:300 / 260" data-testid="freestar-ad-container"><div><div class="" id="above-recs-desktop-ad-sm"></div></div></div></div></div><div class="rail-recs RailRecommendations_root__zqtZQ"><h2 class="RailRecommendations_title__kt1D2">Recommended</h2><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="recommended-card-description-0" aria-haspopup="dialog" aria-controls=":Rgql4f6:" popovertarget=":Rgql4f6:" style="anchor-name:--popover-Rgql4f6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/gremlins-graph-traversal-machinery/65833736"><span class="sr-only">Gremlin's Graph Traversal Machinery</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:0" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Gremlin's Graph Traversal Machinery" src="https://cdn.slidesharecdn.com/ss_thumbnails/cassandra-summit-2016-160908181128-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Gremlin's Graph Traversal Machinery" src="https://cdn.slidesharecdn.com/ss_thumbnails/cassandra-summit-2016-160908181128-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Gremlin's Graph Traversal Machinery</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Gremlin's Graph Traversal Machinery for later" role="switch" aria-haspopup="dialog" aria-controls=":R5mgql4f6:" popovertarget=":R5mgql4f6:" style="anchor-name:--popover-R5mgql4f6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R5mgql4f6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R5mgql4f6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/slidarko">Marko Rodriguez</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">This document summarizes the key concepts and components of Gremlin's graph traversal machinery: - Gremlin uses a traversal language to express graph queries via step composition, with steps mapping traversers between domains. - Traversals are compiled to bytecode and optimized by traversal strategies before being executed by the Gremlin machine. - The Gremlin machine consists of steps implementing functions that process traverser streams. Their composition forms the traversal. - Gremlin is language-agnostic, with language variants translating to a shared bytecode that interacts with the Java-based implementation.</span></div></div><div class="" id=":Rgql4f6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rgql4f6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="recommended-card-description-1" aria-haspopup="dialog" aria-controls=":Rhal4f6:" popovertarget=":Rhal4f6:" style="anchor-name:--popover-Rhal4f6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/data-modeling-with-neo4j-25767444/25767444"><span class="sr-only">Data Modeling with Neo4j</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:1" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Data Modeling with Neo4j" src="https://cdn.slidesharecdn.com/ss_thumbnails/webinardatamodelingnew-130830215355-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Data Modeling with Neo4j" src="https://cdn.slidesharecdn.com/ss_thumbnails/webinardatamodelingnew-130830215355-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Data Modeling with Neo4j</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Data Modeling with Neo4j for later" role="switch" aria-haspopup="dialog" aria-controls=":R5mhal4f6:" popovertarget=":R5mhal4f6:" style="anchor-name:--popover-R5mhal4f6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R5mhal4f6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R5mhal4f6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/neo4j">Neo4j</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">Neo4j is a powerful and expressive tool for storing, querying and manipulating data. However modeling data as graphs is quite different from modeling data under a relational database. In this talk, Michael Hunger will cover modeling business domains using graphs and show how they can be persisted and queried in Neo4j. We'll contrast this approach with the relational model, and discuss the impact on complexity, flexibility and performance. </span></div></div><div class="" id=":Rhal4f6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rhal4f6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="recommended-card-description-2" aria-haspopup="dialog" aria-controls=":Rhql4f6:" popovertarget=":Rhql4f6:" style="anchor-name:--popover-Rhql4f6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/graph-database-use-cases/35182978"><span class="sr-only">Graph database Use Cases</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:2" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Graph database Use Cases" src="https://cdn.slidesharecdn.com/ss_thumbnails/graphdatabaseusecases-140527143641-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Graph database Use Cases" src="https://cdn.slidesharecdn.com/ss_thumbnails/graphdatabaseusecases-140527143641-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Graph database Use Cases</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Graph database Use Cases for later" role="switch" aria-haspopup="dialog" aria-controls=":R5mhql4f6:" popovertarget=":R5mhql4f6:" style="anchor-name:--popover-R5mhql4f6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R5mhql4f6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R5mhql4f6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/maxdemarzi">Max De Marzi</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">This document provides an overview of graph databases and their use cases. It begins with definitions of graphs and graph databases. It then gives examples of how graph databases can be used for social networking, network management, and other domains where data is interconnected. It provides Cypher examples for creating and querying graph patterns in a social networking and IT network management scenario. Finally, it discusses the graph database ecosystem and how graphs can be deployed for both online transaction processing and batch processing use cases.</span></div></div><div class="" id=":Rhql4f6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rhql4f6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="recommended-card-description-3" aria-haspopup="dialog" aria-controls=":Rial4f6:" popovertarget=":Rial4f6:" style="anchor-name:--popover-Rial4f6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slidarko/acm-dbpl-keynote-the-graph-traversal-machine-and-language"><span class="sr-only">ACM DBPL Keynote: The Graph Traversal Machine and Language</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:3" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="ACM DBPL Keynote: The Graph Traversal Machine and Language" src="https://cdn.slidesharecdn.com/ss_thumbnails/acm-dblp-gremlin-2015-151026193345-lva1-app6891-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="ACM DBPL Keynote: The Graph Traversal Machine and Language" src="https://cdn.slidesharecdn.com/ss_thumbnails/acm-dblp-gremlin-2015-151026193345-lva1-app6891-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">ACM DBPL Keynote: The Graph Traversal Machine and Language</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save ACM DBPL Keynote: The Graph Traversal Machine and Language for later" role="switch" aria-haspopup="dialog" aria-controls=":R5mial4f6:" popovertarget=":R5mial4f6:" style="anchor-name:--popover-R5mial4f6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R5mial4f6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R5mial4f6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/slidarko">Marko Rodriguez</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">The document summarizes the components of the Gremlin traversal machine: - The graph is stored in memory and represents the data as vertices, edges, and properties. - Traversers represent computational threads that traverse the graph. They track their location, path history, and program counter in the traversal program. - Traversals are programs that manipulate traversers to query and update the graph. - Gremlin is agnostic to the underlying graph database and can traverse graphs in various systems like TinkerGraph, Titan, Neo4j, and distributed processors.</span></div></div><div class="" id=":Rial4f6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rial4f6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="recommended-card-description-4" aria-haspopup="dialog" aria-controls=":Riql4f6:" popovertarget=":Riql4f6:" style="anchor-name:--popover-Riql4f6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/maxdemarzi/introduction-to-graph-databases-12735789"><span class="sr-only">Introduction to Graph Databases</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:4" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Introduction to Graph Databases" src="https://cdn.slidesharecdn.com/ss_thumbnails/beginnerpresentation-120429104540-phpapp01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Introduction to Graph Databases" src="https://cdn.slidesharecdn.com/ss_thumbnails/beginnerpresentation-120429104540-phpapp01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Introduction to Graph Databases</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Introduction to Graph Databases for later" role="switch" aria-haspopup="dialog" aria-controls=":R5miql4f6:" popovertarget=":R5miql4f6:" style="anchor-name:--popover-R5miql4f6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R5miql4f6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R5miql4f6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/maxdemarzi">Max De Marzi</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">Max De Marzi gave an introduction to graph databases using Neo4j as an example. He discussed trends in big, connected data and how NoSQL databases like key-value stores, column families, and document databases address these trends. However, graph databases are optimized for interconnected data by modeling it as nodes and relationships. Neo4j is a graph database that uses a property graph data model and allows querying and traversal through its Cypher query language and Gremlin scripting language. It is well-suited for domains involving highly connected data like social networks.</span></div></div><div class="" id=":Riql4f6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Riql4f6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="recommended-card-description-5" aria-haspopup="dialog" aria-controls=":Rjal4f6:" popovertarget=":Rjal4f6:" style="anchor-name:--popover-Rjal4f6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/gremlins-anatomy-88713465/88713465"><span class="sr-only">Gremlin's Anatomy</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:5" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Gremlin's Anatomy" src="https://cdn.slidesharecdn.com/ss_thumbnails/gremlins-anatomy-180223113818-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Gremlin's Anatomy" src="https://cdn.slidesharecdn.com/ss_thumbnails/gremlins-anatomy-180223113818-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Gremlin's Anatomy</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Gremlin's Anatomy for later" role="switch" aria-haspopup="dialog" aria-controls=":R5mjal4f6:" popovertarget=":R5mjal4f6:" style="anchor-name:--popover-R5mjal4f6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R5mjal4f6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R5mjal4f6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/StephenMallette">Stephen Mallette</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">Gremlin is the graph traversal language of Apache TinkerPop, an open source graph computing framework, that is implemented by a great many graph databases, including DSE Graph. Even the most novice Gremlin user will recognize the Gremlin statement of "g.V()", but in this presentation we will stop to take a moment to understand the elements of that ubiquitous statement and the elements of the steps that append to it. With the foundational knowledge of "Gremlin's Anatomy" firmly held, we will perform an autopsy on an advanced Gremlin traversal and thus expose techniques for examining and taming the most complex and confusing Gremlin one might come across.</span></div></div><div class="" id=":Rjal4f6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rjal4f6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="recommended-card-description-6" aria-haspopup="dialog" aria-controls=":Rjql4f6:" popovertarget=":Rjql4f6:" style="anchor-name:--popover-Rjql4f6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/nosqleu-graph-databases-and-neo4j/3792258"><span class="sr-only">NOSQLEU - Graph Databases and Neo4j</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:6" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="NOSQLEU - Graph Databases and Neo4j" src="https://cdn.slidesharecdn.com/ss_thumbnails/nosqleu-graphdatabasesandneo4j-100420134225-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="NOSQLEU - Graph Databases and Neo4j" src="https://cdn.slidesharecdn.com/ss_thumbnails/nosqleu-graphdatabasesandneo4j-100420134225-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">NOSQLEU - Graph Databases and Neo4j</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save NOSQLEU - Graph Databases and Neo4j for later" role="switch" aria-haspopup="dialog" aria-controls=":R5mjql4f6:" popovertarget=":R5mjql4f6:" style="anchor-name:--popover-R5mjql4f6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R5mjql4f6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R5mjql4f6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/thobe">Tobias Lindaaker</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">Graph databases are well suited for complex, interconnected data. Neo4j is a graph database that represents data as nodes connected by relationships. It allows for complex queries and traversals of graph structures. Unlike relational databases, graph databases can directly model real world networks and relationships without needing to flatten the data.</span></div></div><div class="" id=":Rjql4f6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rjql4f6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="recommended-card-description-7" aria-haspopup="dialog" aria-controls=":Rkal4f6:" popovertarget=":Rkal4f6:" style="anchor-name:--popover-Rkal4f6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/intro-to-neo4j-and-graph-databases/60306504"><span class="sr-only">Intro to Neo4j and Graph Databases</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:7" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Intro to Neo4j and Graph Databases" src="https://cdn.slidesharecdn.com/ss_thumbnails/introtoneo4jwebinar331-160331235041-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Intro to Neo4j and Graph Databases" src="https://cdn.slidesharecdn.com/ss_thumbnails/introtoneo4jwebinar331-160331235041-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Intro to Neo4j and Graph Databases</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Intro to Neo4j and Graph Databases for later" role="switch" aria-haspopup="dialog" aria-controls=":R5mkal4f6:" popovertarget=":R5mkal4f6:" style="anchor-name:--popover-R5mkal4f6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R5mkal4f6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R5mkal4f6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/neo4j">Neo4j</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">These webinar slides are an introduction to Neo4j and Graph Databases. They discuss the primary use cases for Graph Databases and the properties of Neo4j which make those use cases possible. They also cover the high-level steps of modeling, importing, and querying your data using Cypher and touch on RDBMS to Graph.</span></div></div><div class="" id=":Rkal4f6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rkal4f6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="recommended-card-description-8" aria-haspopup="dialog" aria-controls=":Rkql4f6:" popovertarget=":Rkql4f6:" style="anchor-name:--popover-Rkql4f6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/intro-to-neo4j-and-dot-net2/49471265"><span class="sr-only">Introduction to Neo4j and .Net</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:8" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Introduction to Neo4j and .Net" src="https://cdn.slidesharecdn.com/ss_thumbnails/introtoneo4janddotnet2-150616182340-lva1-app6891-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Introduction to Neo4j and .Net" src="https://cdn.slidesharecdn.com/ss_thumbnails/introtoneo4janddotnet2-150616182340-lva1-app6891-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Introduction to Neo4j and .Net</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Introduction to Neo4j and .Net for later" role="switch" aria-haspopup="dialog" aria-controls=":R5mkql4f6:" popovertarget=":R5mkql4f6:" style="anchor-name:--popover-R5mkql4f6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R5mkql4f6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R5mkql4f6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/neo4j">Neo4j</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">Complex hierarchical relationships between entities can only be mapped with difficulty in a relational database and demanding queries are usually quite slow. Graph databases are optimized for exactly these kinds of relationships and can provide high-performance results even with huge amounts of data. Moreover, not only the entities that are stored in the database, have attributes, but also their relationships. Queries can look at entities as well as their relationships. Get to know the basics of graph databases, using Neo4j as an example, and see how it is used C# projects.</span></div></div><div class="" id=":Rkql4f6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rkql4f6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="recommended-card-description-9" aria-haspopup="dialog" aria-controls=":Rlal4f6:" popovertarget=":Rlal4f6:" style="anchor-name:--popover-Rlal4f6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/an-introduction-to-rest-api/76492672"><span class="sr-only">An Introduction To REST API</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:9" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="An Introduction To REST API" src="https://cdn.slidesharecdn.com/ss_thumbnails/anintroductiontorestapi-170530164024-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="An Introduction To REST API" src="https://cdn.slidesharecdn.com/ss_thumbnails/anintroductiontorestapi-170530164024-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">An Introduction To REST API</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save An Introduction To REST API for later" role="switch" aria-haspopup="dialog" aria-controls=":R5mlal4f6:" popovertarget=":R5mlal4f6:" style="anchor-name:--popover-R5mlal4f6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R5mlal4f6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R5mlal4f6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/AniruddhBhilvare">Aniruddh Bhilvare</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">This document provides an introduction and overview of REST APIs. It defines REST as an architectural style based on web standards like HTTP that defines resources that are accessed via common operations like GET, PUT, POST, and DELETE. It outlines best practices for REST API design, including using nouns in URIs, plural resource names, GET for retrieval only, HTTP status codes, and versioning. It also covers concepts like filtering, sorting, paging, and common queries.</span></div></div><div class="" id=":Rlal4f6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rlal4f6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="recommended-card-description-10" aria-haspopup="dialog" aria-controls=":Rlql4f6:" popovertarget=":Rlql4f6:" style="anchor-name:--popover-Rlql4f6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/introducing-neo4j/66260495"><span class="sr-only">Introducing Neo4j</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:10" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Introducing Neo4j" src="https://cdn.slidesharecdn.com/ss_thumbnails/neo4jatlantagraphtalk09082016-160921141445-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Introducing Neo4j" src="https://cdn.slidesharecdn.com/ss_thumbnails/neo4jatlantagraphtalk09082016-160921141445-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Introducing Neo4j</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Introducing Neo4j for later" role="switch" aria-haspopup="dialog" aria-controls=":R5mlql4f6:" popovertarget=":R5mlql4f6:" style="anchor-name:--popover-R5mlql4f6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R5mlql4f6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R5mlql4f6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/neo4j">Neo4j</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">This document summarizes a presentation about the graph database Neo4j. The presentation included an agenda that covered graphs and their power, how graphs change data views, and real-time recommendations with graphs. It introduced the presenters and discussed how data relationships unlock value. It described how Neo4j allows modeling data as a graph to unlock this value through relationship-based queries, evolution of applications, and high performance at scale. Examples showed how Neo4j outperforms relational and NoSQL databases when relationships are important. The presentation concluded with examples of how Neo4j customers have benefited.</span></div></div><div class="" id=":Rlql4f6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rlql4f6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="recommended-card-description-11" aria-haspopup="dialog" aria-controls=":Rmal4f6:" popovertarget=":Rmal4f6:" style="anchor-name:--popover-Rmal4f6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/neo4j-presentation/77357254"><span class="sr-only">Neo4j Presentation</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:11" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Neo4j Presentation" src="https://cdn.slidesharecdn.com/ss_thumbnails/newneo4jpresentation-170629025617-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Neo4j Presentation" src="https://cdn.slidesharecdn.com/ss_thumbnails/newneo4jpresentation-170629025617-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Neo4j Presentation</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Neo4j Presentation for later" role="switch" aria-haspopup="dialog" aria-controls=":R5mmal4f6:" popovertarget=":R5mmal4f6:" style="anchor-name:--popover-R5mmal4f6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R5mmal4f6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R5mmal4f6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/maxdemarzi">Max De Marzi</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">The document discusses how property graph databases like Neo4j can model and query relationship data more effectively than relational or other NoSQL databases. It provides examples of modeling user, movie, and product data as graphs and executing queries in Cypher. It also discusses using the Java Core API and Traversal API to navigate graph data and developing recommendation systems and applications for fraud detection by analyzing patterns in user behaviors and connections.</span></div></div><div class="" id=":Rmal4f6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rmal4f6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="recommended-card-description-12" aria-haspopup="dialog" aria-controls=":Rmql4f6:" popovertarget=":Rmql4f6:" style="anchor-name:--popover-Rmql4f6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/graphql-presentation-168238341/168238341"><span class="sr-only">Graphql presentation</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:12" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Graphql presentation" src="https://cdn.slidesharecdn.com/ss_thumbnails/graphql-presentaion-1-190902030950-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Graphql presentation" src="https://cdn.slidesharecdn.com/ss_thumbnails/graphql-presentaion-1-190902030950-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Graphql presentation</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Graphql presentation for later" role="switch" aria-haspopup="dialog" aria-controls=":R5mmql4f6:" popovertarget=":R5mmql4f6:" style="anchor-name:--popover-R5mmql4f6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R5mmql4f6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R5mmql4f6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/vibhorgrover">Vibhor Grover</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">It is a basic presentation which can help you understand the basic concepts about Graphql and how it can be used to resolve the frontend integration of projects and help in reducing the data fetching time This presentation also explains the core features of Graphql and why It is a great alternative for REST APIs along with the procedure with which we can integrate it into our projects</span></div></div><div class="" id=":Rmql4f6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rmql4f6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="recommended-card-description-13" aria-haspopup="dialog" aria-controls=":Rnal4f6:" popovertarget=":Rnal4f6:" style="anchor-name:--popover-Rnal4f6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/introduction-to-graph-databasespdf/261296417"><span class="sr-only">Introduction to Graph Databases.pdf</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:13" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Introduction to Graph Databases.pdf" src="https://cdn.slidesharecdn.com/ss_thumbnails/introductiontographdatabases-230922161549-2d65a621-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Introduction to Graph Databases.pdf" src="https://cdn.slidesharecdn.com/ss_thumbnails/introductiontographdatabases-230922161549-2d65a621-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Introduction to Graph Databases.pdf</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Introduction to Graph Databases.pdf for later" role="switch" aria-haspopup="dialog" aria-controls=":R5mnal4f6:" popovertarget=":R5mnal4f6:" style="anchor-name:--popover-R5mnal4f6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R5mnal4f6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R5mnal4f6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/neo4j">Neo4j</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">This document discusses graph databases and their components. It defines nodes and relationships as the basic elements, and how they can have labels and properties. It introduces the Cypher query language used for graph pattern matching. It also discusses the difference between native and non-native graph databases, where native databases directly store and query relationships without needing indexes.</span></div></div><div class="" id=":Rnal4f6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rnal4f6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="recommended-card-description-14" aria-haspopup="dialog" aria-controls=":Rnql4f6:" popovertarget=":Rnql4f6:" style="anchor-name:--popover-Rnql4f6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/data-modeling-with-neo4j/24210453"><span class="sr-only">Data Modeling with Neo4j</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:14" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Data Modeling with Neo4j" src="https://cdn.slidesharecdn.com/ss_thumbnails/webinardatamodeling-130713191849-phpapp01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Data Modeling with Neo4j" src="https://cdn.slidesharecdn.com/ss_thumbnails/webinardatamodeling-130713191849-phpapp01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Data Modeling with Neo4j</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Data Modeling with Neo4j for later" role="switch" aria-haspopup="dialog" aria-controls=":R5mnql4f6:" popovertarget=":R5mnql4f6:" style="anchor-name:--popover-R5mnql4f6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R5mnql4f6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R5mnql4f6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/neo4j">Neo4j</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">This presentation covers several aspects of modeling data and domains with a graph database like Neo4j. The graph data model allows high fidelity modeling. Using the first class relationships of the graph model allow to use much higher forms of normalization than you would use in a relational database. Video here: https://vimeo.com/67371996</span></div></div><div class="" id=":Rnql4f6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rnql4f6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="recommended-card-description-15" aria-haspopup="dialog" aria-controls=":Roal4f6:" popovertarget=":Roal4f6:" style="anchor-name:--popover-Roal4f6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/graph-databases-43380162/43380162"><span class="sr-only">Graph database</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:15" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Graph database" src="https://cdn.slidesharecdn.com/ss_thumbnails/graphdatabases-150110050756-conversion-gate02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Graph database" src="https://cdn.slidesharecdn.com/ss_thumbnails/graphdatabases-150110050756-conversion-gate02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Graph database</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Graph database for later" role="switch" aria-haspopup="dialog" aria-controls=":R5moal4f6:" popovertarget=":R5moal4f6:" style="anchor-name:--popover-R5moal4f6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R5moal4f6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R5moal4f6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/allerintech">Achintya Kumar</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">Graph databases are well-suited for storing and querying multi-relational data. They provide better performance, flexibility, and agility than relational databases for such data. Tests showed graph databases like Neo4j outperforming relational databases by returning results faster and for more records as depth and complexity of queries increased. Cypher is the query language for Neo4j that allows starting queries, matching patterns, returning and filtering results through clauses like START, MATCH, RETURN, and WHERE. Graph databases are used successfully by many large companies needing to handle complex relationships in data.</span></div></div><div class="" id=":Roal4f6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Roal4f6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="recommended-card-description-16" aria-haspopup="dialog" aria-controls=":Roql4f6:" popovertarget=":Roql4f6:" style="anchor-name:--popover-Roql4f6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://fr.slideshare.net/BorisGuarisma/base-de-donnes-graphe-et-neo4j"><span class="sr-only">Base de données graphe et Neo4j</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:16" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Base de données graphe et Neo4j" src="https://cdn.slidesharecdn.com/ss_thumbnails/prsentationbdgraphes-draft6-160120072438-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Base de données graphe et Neo4j" src="https://cdn.slidesharecdn.com/ss_thumbnails/prsentationbdgraphes-draft6-160120072438-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Base de données graphe et Neo4j</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Base de données graphe et Neo4j for later" role="switch" aria-haspopup="dialog" aria-controls=":R5moql4f6:" popovertarget=":R5moql4f6:" style="anchor-name:--popover-R5moql4f6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R5moql4f6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R5moql4f6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/BorisGuarisma">Boris Guarisma</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">Présentation CNAM 19 janvier 2016</span></div></div><div class="" id=":Roql4f6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Roql4f6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="recommended-card-description-17" aria-haspopup="dialog" aria-controls=":Rpal4f6:" popovertarget=":Rpal4f6:" style="anchor-name:--popover-Rpal4f6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/intro-to-neo4j/78307694"><span class="sr-only">Intro to Neo4j</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:17" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Intro to Neo4j" src="https://cdn.slidesharecdn.com/ss_thumbnails/whatwedo-2017finalversion22217-170727120456-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Intro to Neo4j" src="https://cdn.slidesharecdn.com/ss_thumbnails/whatwedo-2017finalversion22217-170727120456-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Intro to Neo4j</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Intro to Neo4j for later" role="switch" aria-haspopup="dialog" aria-controls=":R5mpal4f6:" popovertarget=":R5mpal4f6:" style="anchor-name:--popover-R5mpal4f6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R5mpal4f6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R5mpal4f6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/neo4j">Neo4j</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">Neo4j is a native graph database that allows organizations to leverage connections in data to create value in real-time. Unlike traditional databases, Neo4j connects data as it stores it, enabling lightning-fast retrieval of relationships. With over 200 customers including Walmart, UBS, and adidas, Neo4j is the number one database for connected data by providing a highly scalable and flexible platform to power use cases like recommendations, fraud detection, and supply chain management through relationship queries and analytics.</span></div></div><div class="" id=":Rpal4f6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rpal4f6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="recommended-card-description-18" aria-haspopup="dialog" aria-controls=":Rpql4f6:" popovertarget=":Rpql4f6:" style="anchor-name:--popover-Rpql4f6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/building-applications-with-a-graph-database/26629522"><span class="sr-only">Building Applications with a Graph Database</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:18" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Building Applications with a Graph Database" src="https://cdn.slidesharecdn.com/ss_thumbnails/buildingapplicationswithagraphdatabase-130927150303-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Building Applications with a Graph Database" src="https://cdn.slidesharecdn.com/ss_thumbnails/buildingapplicationswithagraphdatabase-130927150303-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Building Applications with a Graph Database</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Building Applications with a Graph Database for later" role="switch" aria-haspopup="dialog" aria-controls=":R5mpql4f6:" popovertarget=":R5mpql4f6:" style="anchor-name:--popover-R5mpql4f6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R5mpql4f6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R5mpql4f6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/thobe">Tobias Lindaaker</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">Presented at JavaOne 2013, Tuesday September 24. "Data Modeling Patterns" co-created with Ian Robinson. "Pitfalls and Anti-Patterns" created by Ian Robinson.</span></div></div><div class="" id=":Rpql4f6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rpql4f6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="recommended-card-description-19" aria-haspopup="dialog" aria-controls=":Rqal4f6:" popovertarget=":Rqal4f6:" style="anchor-name:--popover-Rqal4f6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/nosql-graph-databases-why-when-and-where/41759026"><span class="sr-only">NoSQL Graph Databases - Why, When and Where</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:19" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="NoSQL Graph Databases - Why, When and Where" src="https://cdn.slidesharecdn.com/ss_thumbnails/graphdb-nosql-eugene-hanikblum-141119093955-conversion-gate01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="NoSQL Graph Databases - Why, When and Where" src="https://cdn.slidesharecdn.com/ss_thumbnails/graphdb-nosql-eugene-hanikblum-141119093955-conversion-gate01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">NoSQL Graph Databases - Why, When and Where</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save NoSQL Graph Databases - Why, When and Where for later" role="switch" aria-haspopup="dialog" aria-controls=":R5mqal4f6:" popovertarget=":R5mqal4f6:" style="anchor-name:--popover-R5mqal4f6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R5mqal4f6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R5mqal4f6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/eugeneh">Eugene Hanikblum</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">NoSQL Graph Databases - Why, When And Where should we use it. Graph DB - The new era of understanding data</span></div></div><div class="" id=":Rqal4f6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rqal4f6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="recommended-card-description-20" aria-haspopup="dialog" aria-controls=":Rqql4f6:" popovertarget=":Rqql4f6:" style="anchor-name:--popover-Rqql4f6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/sparql-cheat-sheet/1589776"><span class="sr-only">SPARQL Cheat Sheet</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:20" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="SPARQL Cheat Sheet" src="https://cdn.slidesharecdn.com/ss_thumbnails/sparql-cheat-sheet-090616011306-phpapp01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="SPARQL Cheat Sheet" src="https://cdn.slidesharecdn.com/ss_thumbnails/sparql-cheat-sheet-090616011306-phpapp01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">SPARQL Cheat Sheet</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save SPARQL Cheat Sheet for later" role="switch" aria-haspopup="dialog" aria-controls=":R5mqql4f6:" popovertarget=":R5mqql4f6:" style="anchor-name:--popover-R5mqql4f6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R5mqql4f6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R5mqql4f6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/LeeFeigenbaum">LeeFeigenbaum</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">"SPARQL Cheat Sheet" is a short collection of slides intended to act as a guide to SPARQL developers. It includes the syntax and structure of SPARQL queries, common SPARQL prefixes and functions, and help with RDF datasets. The "SPARQL Cheat Sheet" is intended to accompany the SPARQL By Example slides available at http://www.cambridgesemantics.com/2008/09/sparql-by-example/ .</span></div></div><div class="" id=":Rqql4f6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rqql4f6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="recommended-card-description-21" aria-haspopup="dialog" aria-controls=":Rral4f6:" popovertarget=":Rral4f6:" style="anchor-name:--popover-Rral4f6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/shacl-shaping-the-big-ball-of-data-mud/69293562"><span class="sr-only">SHACL: Shaping the Big Ball of Data Mud</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:21" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="SHACL: Shaping the Big Ball of Data Mud" src="https://cdn.slidesharecdn.com/ss_thumbnails/shacl-shapingthebigballofdatamud-161119104603-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="SHACL: Shaping the Big Ball of Data Mud" src="https://cdn.slidesharecdn.com/ss_thumbnails/shacl-shapingthebigballofdatamud-161119104603-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">SHACL: Shaping the Big Ball of Data Mud</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save SHACL: Shaping the Big Ball of Data Mud for later" role="switch" aria-haspopup="dialog" aria-controls=":R5mral4f6:" popovertarget=":R5mral4f6:" style="anchor-name:--popover-R5mral4f6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R5mral4f6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R5mral4f6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/cygri">Richard Cyganiak</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">Semantic Web technologies (such as RDF and SPARQL) excel at bringing together diverse data in a world of independent data publishers and consumers. Common ontologies help to arrive at a shared understanding of the intended meaning of data. However, they don’t address one critically important issue: What does it mean for data to be complete and/or valid? Semantic knowledge graphs without a shared notion of completeness and validity quickly turn into a Big Ball of Data Mud. The Shapes Constraint Language (SHACL), an upcoming W3C standard, promises to help solve this problem. By keeping semantics separate from validity, SHACL makes it possible to resolve a slew of data quality and data exchange issues. Presented at the Lotico Berlin Semantic Web Meetup.</span></div></div><div class="" id=":Rral4f6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rral4f6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="recommended-card-description-22" aria-haspopup="dialog" aria-controls=":Rrql4f6:" popovertarget=":Rrql4f6:" style="anchor-name:--popover-Rrql4f6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/the-opencypher-project-an-open-graph-query-language/58371127"><span class="sr-only">The openCypher Project - An Open Graph Query Language</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:22" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="The openCypher Project - An Open Graph Query Language" src="https://cdn.slidesharecdn.com/ss_thumbnails/opencypher-160217121816-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="The openCypher Project - An Open Graph Query Language" src="https://cdn.slidesharecdn.com/ss_thumbnails/opencypher-160217121816-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">The openCypher Project - An Open Graph Query Language</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save The openCypher Project - An Open Graph Query Language for later" role="switch" aria-haspopup="dialog" aria-controls=":R5mrql4f6:" popovertarget=":R5mrql4f6:" style="anchor-name:--popover-R5mrql4f6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R5mrql4f6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R5mrql4f6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/neo4j">Neo4j</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">We want to present the openCypher project, whose purpose is to make Cypher available to everyone – every data store, every tooling provider, every application developer. openCypher is a continual work in progress. Over the next few months, we will move more and more of the language artifacts over to GitHub to make it available for everyone. openCypher is an open source project that delivers four key artifacts released under a permissive license: (i) the Cypher reference documentation, (ii) a Technology compatibility kit (TCK), (iii) Reference implementation (a fully functional implementation of key parts of the stack needed to support Cypher inside a data platform or tool) and (iv) the Cypher language specification. We are also seeking to make the process of specifying and evolving the Cypher query language as open as possible, and are actively seeking comments and suggestions on how to improve the Cypher query language. The purpose of this talk is to provide more details regarding the above-mentioned aspects. We want to present the openCypher project, whose purpose is to make Cypher available to everyone – every data store, every tooling provider, every application developer. openCypher is a continual work in progress. Over the next few months, we will move more and more of the language artifacts over to GitHub to make it available for everyone. openCypher is an open source project that delivers four key artifacts released under a permissive license: (i) the Cypher reference documentation, (ii) a Technology compatibility kit (TCK), (iii) Reference implementation (a fully functional implementation of key parts of the stack needed to support Cypher inside a data platform or tool) and (iv) the Cypher language specification. We are also seeking to make the process of specifying and evolving the Cypher query language as open as possible, and are actively seeking comments and suggestions on how to improve the Cypher query language. The purpose of this talk is to provide more details regarding the above-mentioned aspects.</span></div></div><div class="" id=":Rrql4f6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rrql4f6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="recommended-card-description-23" aria-haspopup="dialog" aria-controls=":Rsal4f6:" popovertarget=":Rsal4f6:" style="anchor-name:--popover-Rsal4f6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/training-week-introduction-to-neo4j/250183108"><span class="sr-only">Training Week: Introduction to Neo4j</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:23" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Training Week: Introduction to Neo4j" src="https://cdn.slidesharecdn.com/ss_thumbnails/introductiontoneo4j-ahands-oncrashcourse2-210913150256-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Training Week: Introduction to Neo4j" src="https://cdn.slidesharecdn.com/ss_thumbnails/introductiontoneo4j-ahands-oncrashcourse2-210913150256-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Training Week: Introduction to Neo4j</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Training Week: Introduction to Neo4j for later" role="switch" aria-haspopup="dialog" aria-controls=":R5msal4f6:" popovertarget=":R5msal4f6:" style="anchor-name:--popover-R5msal4f6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R5msal4f6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R5msal4f6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/neo4j">Neo4j</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">This document provides an introduction to Neo4j and graph databases. It discusses what a graph is, why graphs are useful, examples of graph scenarios, the components of a property graph database including nodes, relationships and properties, and how to query graphs using Cypher. It also promotes additional Neo4j training resources and encourages continuing the user's graph journey.</span></div></div><div class="" id=":Rsal4f6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rsal4f6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="recommended-card-description-24" aria-haspopup="dialog" aria-controls=":Rsql4f6:" popovertarget=":Rsql4f6:" style="anchor-name:--popover-Rsql4f6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/introduction-to-graph-database/31330223"><span class="sr-only">Introduction to Graph Database</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:24" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Introduction to Graph Database" src="https://cdn.slidesharecdn.com/ss_thumbnails/lsm3241-gdbms-140218033708-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Introduction to Graph Database" src="https://cdn.slidesharecdn.com/ss_thumbnails/lsm3241-gdbms-140218033708-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Introduction to Graph Database</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Introduction to Graph Database for later" role="switch" aria-haspopup="dialog" aria-controls=":R5msql4f6:" popovertarget=":R5msql4f6:" style="anchor-name:--popover-R5msql4f6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R5msql4f6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R5msql4f6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/leezhenyu">Eric Lee</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">Introduction to Graph database, using K-pop as a database modelling case. From the idea of graph database, Neo4j installation, modelling, Cypher to business application.</span></div></div><div class="" id=":Rsql4f6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rsql4f6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="recommended-card-description-25" aria-haspopup="dialog" aria-controls=":Rtal4f6:" popovertarget=":Rtal4f6:" style="anchor-name:--popover-Rtal4f6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/introduction-to-neo4j-for-the-emirates-bahrain/242255825"><span class="sr-only">Introduction to Neo4j for the Emirates & Bahrain</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:25" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Introduction to Neo4j for the Emirates & Bahrain" src="https://cdn.slidesharecdn.com/ss_thumbnails/introductiontoneo4juaebaharain-210204094723-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Introduction to Neo4j for the Emirates & Bahrain" src="https://cdn.slidesharecdn.com/ss_thumbnails/introductiontoneo4juaebaharain-210204094723-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Introduction to Neo4j for the Emirates & Bahrain</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Introduction to Neo4j for the Emirates & Bahrain for later" role="switch" aria-haspopup="dialog" aria-controls=":R5mtal4f6:" popovertarget=":R5mtal4f6:" style="anchor-name:--popover-R5mtal4f6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R5mtal4f6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R5mtal4f6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/neo4j">Neo4j</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">This document provides an agenda and overview of a Neo4j presentation. It discusses Neo4j as the leading native graph database, its graph data science capabilities, and deployment options like Neo4j Aura and Cloud Managed Services. Success stories are highlighted like Minka using Neo4j Aura to power Colombia's new real-time ACH payments system. The presentation aims to demonstrate Neo4j's technology, use cases, and how it can drive business value through connecting data.</span></div></div><div class="" id=":Rtal4f6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rtal4f6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="recommended-card-description-26" aria-haspopup="dialog" aria-controls=":Rtql4f6:" popovertarget=":Rtql4f6:" style="anchor-name:--popover-Rtql4f6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/jena-193716/193716"><span class="sr-only">Jena</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:26" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Jena" src="https://cdn.slidesharecdn.com/ss_thumbnails/jena-1196913303282065-3-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Jena" src="https://cdn.slidesharecdn.com/ss_thumbnails/jena-1196913303282065-3-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Jena</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Jena for later" role="switch" aria-haspopup="dialog" aria-controls=":R5mtql4f6:" popovertarget=":R5mtql4f6:" style="anchor-name:--popover-R5mtql4f6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R5mtql4f6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R5mtql4f6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/yuhana">yuhana</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">This document provides instructions for installing and running Jena, a Java framework for building semantic web and linked data applications. It discusses RDF, the resource description framework, and describes how to download the necessary tools, create a Java project in Eclipse, add the Jena libraries to the project's build path, and import example source code to get started with the Jena API.</span></div></div><div class="" id=":Rtql4f6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rtql4f6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="recommended-card-description-27" aria-haspopup="dialog" aria-controls=":Rual4f6:" popovertarget=":Rual4f6:" style="anchor-name:--popover-Rual4f6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/rdbms-to-graph/79301686"><span class="sr-only">RDBMS to Graph</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:27" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="RDBMS to Graph" src="https://cdn.slidesharecdn.com/ss_thumbnails/rdbmstographwebinar-august2017-170830213253-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="RDBMS to Graph" src="https://cdn.slidesharecdn.com/ss_thumbnails/rdbmstographwebinar-august2017-170830213253-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">RDBMS to Graph</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save RDBMS to Graph for later" role="switch" aria-haspopup="dialog" aria-controls=":R5mual4f6:" popovertarget=":R5mual4f6:" style="anchor-name:--popover-R5mual4f6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R5mual4f6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R5mual4f6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/neo4j">Neo4j</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">Relational databases were conceived to digitize paper forms and automate well-structured business processes, and still have their uses. But RDBMS cannot model or store data and its relationships without complexity, which means performance degrades with the increasing number and levels of data relationships and data size. Additionally, new types of data and data relationships require schema redesign that increases time to market. A native graph database like Neo4j naturally stores, manages, analyzes, and uses data within the context of connections meaning Neo4j provides faster query performance and vastly improved flexibility in handling complex hierarchies than SQL.</span></div></div><div class="" id=":Rual4f6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rual4f6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="recommended-card-description-28" aria-haspopup="dialog" aria-controls=":Ruql4f6:" popovertarget=":Ruql4f6:" style="anchor-name:--popover-Ruql4f6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slidarko/quantum-processes-in-graph-computing"><span class="sr-only">Quantum Processes in Graph Computing</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:28" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Quantum Processes in Graph Computing" src="https://cdn.slidesharecdn.com/ss_thumbnails/quantum-gremlin-graphday-160114154937-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Quantum Processes in Graph Computing" src="https://cdn.slidesharecdn.com/ss_thumbnails/quantum-gremlin-graphday-160114154937-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Quantum Processes in Graph Computing</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Quantum Processes in Graph Computing for later" role="switch" aria-haspopup="dialog" aria-controls=":R5muql4f6:" popovertarget=":R5muql4f6:" style="anchor-name:--popover-R5muql4f6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R5muql4f6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R5muql4f6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/slidarko">Marko Rodriguez</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">This presentation was given on January 17, 2016 at the GraphDay conference in Austin, Texas. The slides demonstrate the use of wave dynamics in graph structures. Moreover, they demonstrate how to implement quantum processes on graph structures. There is an associated article available at http://arxiv.org/abs/1511.06278 (Quantum Walks with Gremlin).</span></div></div><div class="" id=":Ruql4f6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Ruql4f6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="recommended-card-description-29" aria-haspopup="dialog" aria-controls=":Rval4f6:" popovertarget=":Rval4f6:" style="anchor-name:--popover-Rval4f6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/gremlin-a-graphbased-programming-language-3876581/3876581"><span class="sr-only">Gremlin: A Graph-Based Programming Language</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:29" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Gremlin: A Graph-Based Programming Language" src="https://cdn.slidesharecdn.com/ss_thumbnails/cnls-gremlin-2010-100427185653-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Gremlin: A Graph-Based Programming Language" src="https://cdn.slidesharecdn.com/ss_thumbnails/cnls-gremlin-2010-100427185653-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Gremlin: A Graph-Based Programming Language</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Gremlin: A Graph-Based Programming Language for later" role="switch" aria-haspopup="dialog" aria-controls=":R5mval4f6:" popovertarget=":R5mval4f6:" style="anchor-name:--popover-R5mval4f6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R5mval4f6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R5mval4f6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/slidarko">Marko Rodriguez</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">Gremlin is a Turing-complete, graph-based programming language developed for key/value-pair multi-relational graphs called property graphs. Gremlin makes extensive use of XPath 1.0 to support complex graph traversals. Connectors exist to various graph databases and frameworks. This language has application in the areas of graph query, analysis, and manipulation.</span></div></div><div class="" id=":Rval4f6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rval4f6"></div></div></div></div><div class="RelatedContent_root__29Np1"><div class="RelatedContent_wrapper__riU7l"><h2 class="Heading_heading__3MAvZ Heading_h2__f9yvs RelatedContent_title__QUhpL">More Related Content</h2><div class="bottom-recs BottomRecommendation_root__7aU9w"><h3 class="BottomRecommendation_title__SRj68">What's hot <span class="BottomRecommendation_count__4HpLo">(20)</span></h3><div class="BottomRecommendationContent_root__2qm4_"><div class="mobile-recs"><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="whatsHot-card-description-0" aria-haspopup="dialog" aria-controls=":R8b4pkf6:" popovertarget=":R8b4pkf6:" style="anchor-name:--popover-R8b4pkf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/intro-to-neo4j-and-dot-net2/49471265"><span class="sr-only">Introduction to Neo4j and .Net</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:0" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Introduction to Neo4j and .Net" src="https://cdn.slidesharecdn.com/ss_thumbnails/introtoneo4janddotnet2-150616182340-lva1-app6891-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Introduction to Neo4j and .Net" src="https://cdn.slidesharecdn.com/ss_thumbnails/introtoneo4janddotnet2-150616182340-lva1-app6891-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Introduction to Neo4j and .Net</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Introduction to Neo4j and .Net for later" role="switch" aria-haspopup="dialog" aria-controls=":R2r8b4pkf6:" popovertarget=":R2r8b4pkf6:" style="anchor-name:--popover-R2r8b4pkf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2r8b4pkf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2r8b4pkf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/neo4j">Neo4j</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">Complex hierarchical relationships between entities can only be mapped with difficulty in a relational database and demanding queries are usually quite slow. Graph databases are optimized for exactly these kinds of relationships and can provide high-performance results even with huge amounts of data. Moreover, not only the entities that are stored in the database, have attributes, but also their relationships. Queries can look at entities as well as their relationships. Get to know the basics of graph databases, using Neo4j as an example, and see how it is used C# projects.</span></div></div><div class="" id=":R8b4pkf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-R8b4pkf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="whatsHot-card-description-1" aria-haspopup="dialog" aria-controls=":R8j4pkf6:" popovertarget=":R8j4pkf6:" style="anchor-name:--popover-R8j4pkf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/an-introduction-to-rest-api/76492672"><span class="sr-only">An Introduction To REST API</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:1" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="An Introduction To REST API" src="https://cdn.slidesharecdn.com/ss_thumbnails/anintroductiontorestapi-170530164024-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="An Introduction To REST API" src="https://cdn.slidesharecdn.com/ss_thumbnails/anintroductiontorestapi-170530164024-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">An Introduction To REST API</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save An Introduction To REST API for later" role="switch" aria-haspopup="dialog" aria-controls=":R2r8j4pkf6:" popovertarget=":R2r8j4pkf6:" style="anchor-name:--popover-R2r8j4pkf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2r8j4pkf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2r8j4pkf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/AniruddhBhilvare">Aniruddh Bhilvare</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">This document provides an introduction and overview of REST APIs. It defines REST as an architectural style based on web standards like HTTP that defines resources that are accessed via common operations like GET, PUT, POST, and DELETE. It outlines best practices for REST API design, including using nouns in URIs, plural resource names, GET for retrieval only, HTTP status codes, and versioning. It also covers concepts like filtering, sorting, paging, and common queries.</span></div></div><div class="" id=":R8j4pkf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-R8j4pkf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="whatsHot-card-description-2" aria-haspopup="dialog" aria-controls=":R8r4pkf6:" popovertarget=":R8r4pkf6:" style="anchor-name:--popover-R8r4pkf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/introducing-neo4j/66260495"><span class="sr-only">Introducing Neo4j</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:2" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Introducing Neo4j" src="https://cdn.slidesharecdn.com/ss_thumbnails/neo4jatlantagraphtalk09082016-160921141445-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Introducing Neo4j" src="https://cdn.slidesharecdn.com/ss_thumbnails/neo4jatlantagraphtalk09082016-160921141445-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Introducing Neo4j</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Introducing Neo4j for later" role="switch" aria-haspopup="dialog" aria-controls=":R2r8r4pkf6:" popovertarget=":R2r8r4pkf6:" style="anchor-name:--popover-R2r8r4pkf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2r8r4pkf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2r8r4pkf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/neo4j">Neo4j</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">This document summarizes a presentation about the graph database Neo4j. The presentation included an agenda that covered graphs and their power, how graphs change data views, and real-time recommendations with graphs. It introduced the presenters and discussed how data relationships unlock value. It described how Neo4j allows modeling data as a graph to unlock this value through relationship-based queries, evolution of applications, and high performance at scale. Examples showed how Neo4j outperforms relational and NoSQL databases when relationships are important. The presentation concluded with examples of how Neo4j customers have benefited.</span></div></div><div class="" id=":R8r4pkf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-R8r4pkf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="whatsHot-card-description-3" aria-haspopup="dialog" aria-controls=":R934pkf6:" popovertarget=":R934pkf6:" style="anchor-name:--popover-R934pkf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/neo4j-presentation/77357254"><span class="sr-only">Neo4j Presentation</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:3" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Neo4j Presentation" src="https://cdn.slidesharecdn.com/ss_thumbnails/newneo4jpresentation-170629025617-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Neo4j Presentation" src="https://cdn.slidesharecdn.com/ss_thumbnails/newneo4jpresentation-170629025617-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Neo4j Presentation</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Neo4j Presentation for later" role="switch" aria-haspopup="dialog" aria-controls=":R2r934pkf6:" popovertarget=":R2r934pkf6:" style="anchor-name:--popover-R2r934pkf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2r934pkf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2r934pkf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/maxdemarzi">Max De Marzi</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">The document discusses how property graph databases like Neo4j can model and query relationship data more effectively than relational or other NoSQL databases. It provides examples of modeling user, movie, and product data as graphs and executing queries in Cypher. It also discusses using the Java Core API and Traversal API to navigate graph data and developing recommendation systems and applications for fraud detection by analyzing patterns in user behaviors and connections.</span></div></div><div class="" id=":R934pkf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-R934pkf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="whatsHot-card-description-4" aria-haspopup="dialog" aria-controls=":R9b4pkf6:" popovertarget=":R9b4pkf6:" style="anchor-name:--popover-R9b4pkf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/graphql-presentation-168238341/168238341"><span class="sr-only">Graphql presentation</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:4" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Graphql presentation" src="https://cdn.slidesharecdn.com/ss_thumbnails/graphql-presentaion-1-190902030950-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Graphql presentation" src="https://cdn.slidesharecdn.com/ss_thumbnails/graphql-presentaion-1-190902030950-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Graphql presentation</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Graphql presentation for later" role="switch" aria-haspopup="dialog" aria-controls=":R2r9b4pkf6:" popovertarget=":R2r9b4pkf6:" style="anchor-name:--popover-R2r9b4pkf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2r9b4pkf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2r9b4pkf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/vibhorgrover">Vibhor Grover</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">It is a basic presentation which can help you understand the basic concepts about Graphql and how it can be used to resolve the frontend integration of projects and help in reducing the data fetching time This presentation also explains the core features of Graphql and why It is a great alternative for REST APIs along with the procedure with which we can integrate it into our projects</span></div></div><div class="" id=":R9b4pkf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-R9b4pkf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="whatsHot-card-description-5" aria-haspopup="dialog" aria-controls=":R9j4pkf6:" popovertarget=":R9j4pkf6:" style="anchor-name:--popover-R9j4pkf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/introduction-to-graph-databasespdf/261296417"><span class="sr-only">Introduction to Graph Databases.pdf</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:5" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Introduction to Graph Databases.pdf" src="https://cdn.slidesharecdn.com/ss_thumbnails/introductiontographdatabases-230922161549-2d65a621-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Introduction to Graph Databases.pdf" src="https://cdn.slidesharecdn.com/ss_thumbnails/introductiontographdatabases-230922161549-2d65a621-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Introduction to Graph Databases.pdf</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Introduction to Graph Databases.pdf for later" role="switch" aria-haspopup="dialog" aria-controls=":R2r9j4pkf6:" popovertarget=":R2r9j4pkf6:" style="anchor-name:--popover-R2r9j4pkf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2r9j4pkf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2r9j4pkf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/neo4j">Neo4j</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">This document discusses graph databases and their components. It defines nodes and relationships as the basic elements, and how they can have labels and properties. It introduces the Cypher query language used for graph pattern matching. It also discusses the difference between native and non-native graph databases, where native databases directly store and query relationships without needing indexes.</span></div></div><div class="" id=":R9j4pkf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-R9j4pkf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="whatsHot-card-description-6" aria-haspopup="dialog" aria-controls=":R9r4pkf6:" popovertarget=":R9r4pkf6:" style="anchor-name:--popover-R9r4pkf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/data-modeling-with-neo4j/24210453"><span class="sr-only">Data Modeling with Neo4j</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:6" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Data Modeling with Neo4j" src="https://cdn.slidesharecdn.com/ss_thumbnails/webinardatamodeling-130713191849-phpapp01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Data Modeling with Neo4j" src="https://cdn.slidesharecdn.com/ss_thumbnails/webinardatamodeling-130713191849-phpapp01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Data Modeling with Neo4j</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Data Modeling with Neo4j for later" role="switch" aria-haspopup="dialog" aria-controls=":R2r9r4pkf6:" popovertarget=":R2r9r4pkf6:" style="anchor-name:--popover-R2r9r4pkf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2r9r4pkf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2r9r4pkf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/neo4j">Neo4j</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">This presentation covers several aspects of modeling data and domains with a graph database like Neo4j. The graph data model allows high fidelity modeling. Using the first class relationships of the graph model allow to use much higher forms of normalization than you would use in a relational database. Video here: https://vimeo.com/67371996</span></div></div><div class="" id=":R9r4pkf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-R9r4pkf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="whatsHot-card-description-7" aria-haspopup="dialog" aria-controls=":Ra34pkf6:" popovertarget=":Ra34pkf6:" style="anchor-name:--popover-Ra34pkf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/graph-databases-43380162/43380162"><span class="sr-only">Graph database</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:7" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Graph database" src="https://cdn.slidesharecdn.com/ss_thumbnails/graphdatabases-150110050756-conversion-gate02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Graph database" src="https://cdn.slidesharecdn.com/ss_thumbnails/graphdatabases-150110050756-conversion-gate02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Graph database</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Graph database for later" role="switch" aria-haspopup="dialog" aria-controls=":R2ra34pkf6:" popovertarget=":R2ra34pkf6:" style="anchor-name:--popover-R2ra34pkf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2ra34pkf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2ra34pkf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/allerintech">Achintya Kumar</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">Graph databases are well-suited for storing and querying multi-relational data. They provide better performance, flexibility, and agility than relational databases for such data. Tests showed graph databases like Neo4j outperforming relational databases by returning results faster and for more records as depth and complexity of queries increased. Cypher is the query language for Neo4j that allows starting queries, matching patterns, returning and filtering results through clauses like START, MATCH, RETURN, and WHERE. Graph databases are used successfully by many large companies needing to handle complex relationships in data.</span></div></div><div class="" id=":Ra34pkf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Ra34pkf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="whatsHot-card-description-8" aria-haspopup="dialog" aria-controls=":Rab4pkf6:" popovertarget=":Rab4pkf6:" style="anchor-name:--popover-Rab4pkf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://fr.slideshare.net/BorisGuarisma/base-de-donnes-graphe-et-neo4j"><span class="sr-only">Base de données graphe et Neo4j</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:8" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Base de données graphe et Neo4j" src="https://cdn.slidesharecdn.com/ss_thumbnails/prsentationbdgraphes-draft6-160120072438-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Base de données graphe et Neo4j" src="https://cdn.slidesharecdn.com/ss_thumbnails/prsentationbdgraphes-draft6-160120072438-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Base de données graphe et Neo4j</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Base de données graphe et Neo4j for later" role="switch" aria-haspopup="dialog" aria-controls=":R2rab4pkf6:" popovertarget=":R2rab4pkf6:" style="anchor-name:--popover-R2rab4pkf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2rab4pkf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2rab4pkf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/BorisGuarisma">Boris Guarisma</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">Présentation CNAM 19 janvier 2016</span></div></div><div class="" id=":Rab4pkf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rab4pkf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="whatsHot-card-description-9" aria-haspopup="dialog" aria-controls=":Raj4pkf6:" popovertarget=":Raj4pkf6:" style="anchor-name:--popover-Raj4pkf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/intro-to-neo4j/78307694"><span class="sr-only">Intro to Neo4j</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:9" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Intro to Neo4j" src="https://cdn.slidesharecdn.com/ss_thumbnails/whatwedo-2017finalversion22217-170727120456-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Intro to Neo4j" src="https://cdn.slidesharecdn.com/ss_thumbnails/whatwedo-2017finalversion22217-170727120456-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Intro to Neo4j</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Intro to Neo4j for later" role="switch" aria-haspopup="dialog" aria-controls=":R2raj4pkf6:" popovertarget=":R2raj4pkf6:" style="anchor-name:--popover-R2raj4pkf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2raj4pkf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2raj4pkf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/neo4j">Neo4j</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">Neo4j is a native graph database that allows organizations to leverage connections in data to create value in real-time. Unlike traditional databases, Neo4j connects data as it stores it, enabling lightning-fast retrieval of relationships. With over 200 customers including Walmart, UBS, and adidas, Neo4j is the number one database for connected data by providing a highly scalable and flexible platform to power use cases like recommendations, fraud detection, and supply chain management through relationship queries and analytics.</span></div></div><div class="" id=":Raj4pkf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Raj4pkf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="whatsHot-card-description-10" aria-haspopup="dialog" aria-controls=":Rar4pkf6:" popovertarget=":Rar4pkf6:" style="anchor-name:--popover-Rar4pkf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/building-applications-with-a-graph-database/26629522"><span class="sr-only">Building Applications with a Graph Database</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:10" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Building Applications with a Graph Database" src="https://cdn.slidesharecdn.com/ss_thumbnails/buildingapplicationswithagraphdatabase-130927150303-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Building Applications with a Graph Database" src="https://cdn.slidesharecdn.com/ss_thumbnails/buildingapplicationswithagraphdatabase-130927150303-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Building Applications with a Graph Database</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Building Applications with a Graph Database for later" role="switch" aria-haspopup="dialog" aria-controls=":R2rar4pkf6:" popovertarget=":R2rar4pkf6:" style="anchor-name:--popover-R2rar4pkf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2rar4pkf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2rar4pkf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/thobe">Tobias Lindaaker</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">Presented at JavaOne 2013, Tuesday September 24. "Data Modeling Patterns" co-created with Ian Robinson. "Pitfalls and Anti-Patterns" created by Ian Robinson.</span></div></div><div class="" id=":Rar4pkf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rar4pkf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="whatsHot-card-description-11" aria-haspopup="dialog" aria-controls=":Rb34pkf6:" popovertarget=":Rb34pkf6:" style="anchor-name:--popover-Rb34pkf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/nosql-graph-databases-why-when-and-where/41759026"><span class="sr-only">NoSQL Graph Databases - Why, When and Where</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:11" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="NoSQL Graph Databases - Why, When and Where" src="https://cdn.slidesharecdn.com/ss_thumbnails/graphdb-nosql-eugene-hanikblum-141119093955-conversion-gate01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="NoSQL Graph Databases - Why, When and Where" src="https://cdn.slidesharecdn.com/ss_thumbnails/graphdb-nosql-eugene-hanikblum-141119093955-conversion-gate01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">NoSQL Graph Databases - Why, When and Where</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save NoSQL Graph Databases - Why, When and Where for later" role="switch" aria-haspopup="dialog" aria-controls=":R2rb34pkf6:" popovertarget=":R2rb34pkf6:" style="anchor-name:--popover-R2rb34pkf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2rb34pkf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2rb34pkf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/eugeneh">Eugene Hanikblum</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">NoSQL Graph Databases - Why, When And Where should we use it. Graph DB - The new era of understanding data</span></div></div><div class="" id=":Rb34pkf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rb34pkf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="whatsHot-card-description-12" aria-haspopup="dialog" aria-controls=":Rbb4pkf6:" popovertarget=":Rbb4pkf6:" style="anchor-name:--popover-Rbb4pkf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/sparql-cheat-sheet/1589776"><span class="sr-only">SPARQL Cheat Sheet</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:12" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="SPARQL Cheat Sheet" src="https://cdn.slidesharecdn.com/ss_thumbnails/sparql-cheat-sheet-090616011306-phpapp01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="SPARQL Cheat Sheet" src="https://cdn.slidesharecdn.com/ss_thumbnails/sparql-cheat-sheet-090616011306-phpapp01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">SPARQL Cheat Sheet</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save SPARQL Cheat Sheet for later" role="switch" aria-haspopup="dialog" aria-controls=":R2rbb4pkf6:" popovertarget=":R2rbb4pkf6:" style="anchor-name:--popover-R2rbb4pkf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2rbb4pkf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2rbb4pkf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/LeeFeigenbaum">LeeFeigenbaum</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">"SPARQL Cheat Sheet" is a short collection of slides intended to act as a guide to SPARQL developers. It includes the syntax and structure of SPARQL queries, common SPARQL prefixes and functions, and help with RDF datasets. The "SPARQL Cheat Sheet" is intended to accompany the SPARQL By Example slides available at http://www.cambridgesemantics.com/2008/09/sparql-by-example/ .</span></div></div><div class="" id=":Rbb4pkf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rbb4pkf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="whatsHot-card-description-13" aria-haspopup="dialog" aria-controls=":Rbj4pkf6:" popovertarget=":Rbj4pkf6:" style="anchor-name:--popover-Rbj4pkf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/shacl-shaping-the-big-ball-of-data-mud/69293562"><span class="sr-only">SHACL: Shaping the Big Ball of Data Mud</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:13" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="SHACL: Shaping the Big Ball of Data Mud" src="https://cdn.slidesharecdn.com/ss_thumbnails/shacl-shapingthebigballofdatamud-161119104603-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="SHACL: Shaping the Big Ball of Data Mud" src="https://cdn.slidesharecdn.com/ss_thumbnails/shacl-shapingthebigballofdatamud-161119104603-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">SHACL: Shaping the Big Ball of Data Mud</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save SHACL: Shaping the Big Ball of Data Mud for later" role="switch" aria-haspopup="dialog" aria-controls=":R2rbj4pkf6:" popovertarget=":R2rbj4pkf6:" style="anchor-name:--popover-R2rbj4pkf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2rbj4pkf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2rbj4pkf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/cygri">Richard Cyganiak</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">Semantic Web technologies (such as RDF and SPARQL) excel at bringing together diverse data in a world of independent data publishers and consumers. Common ontologies help to arrive at a shared understanding of the intended meaning of data. However, they don’t address one critically important issue: What does it mean for data to be complete and/or valid? Semantic knowledge graphs without a shared notion of completeness and validity quickly turn into a Big Ball of Data Mud. The Shapes Constraint Language (SHACL), an upcoming W3C standard, promises to help solve this problem. By keeping semantics separate from validity, SHACL makes it possible to resolve a slew of data quality and data exchange issues. Presented at the Lotico Berlin Semantic Web Meetup.</span></div></div><div class="" id=":Rbj4pkf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rbj4pkf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="whatsHot-card-description-14" aria-haspopup="dialog" aria-controls=":Rbr4pkf6:" popovertarget=":Rbr4pkf6:" style="anchor-name:--popover-Rbr4pkf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/the-opencypher-project-an-open-graph-query-language/58371127"><span class="sr-only">The openCypher Project - An Open Graph Query Language</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:14" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="The openCypher Project - An Open Graph Query Language" src="https://cdn.slidesharecdn.com/ss_thumbnails/opencypher-160217121816-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="The openCypher Project - An Open Graph Query Language" src="https://cdn.slidesharecdn.com/ss_thumbnails/opencypher-160217121816-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">The openCypher Project - An Open Graph Query Language</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save The openCypher Project - An Open Graph Query Language for later" role="switch" aria-haspopup="dialog" aria-controls=":R2rbr4pkf6:" popovertarget=":R2rbr4pkf6:" style="anchor-name:--popover-R2rbr4pkf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2rbr4pkf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2rbr4pkf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/neo4j">Neo4j</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">We want to present the openCypher project, whose purpose is to make Cypher available to everyone – every data store, every tooling provider, every application developer. openCypher is a continual work in progress. Over the next few months, we will move more and more of the language artifacts over to GitHub to make it available for everyone. openCypher is an open source project that delivers four key artifacts released under a permissive license: (i) the Cypher reference documentation, (ii) a Technology compatibility kit (TCK), (iii) Reference implementation (a fully functional implementation of key parts of the stack needed to support Cypher inside a data platform or tool) and (iv) the Cypher language specification. We are also seeking to make the process of specifying and evolving the Cypher query language as open as possible, and are actively seeking comments and suggestions on how to improve the Cypher query language. The purpose of this talk is to provide more details regarding the above-mentioned aspects. We want to present the openCypher project, whose purpose is to make Cypher available to everyone – every data store, every tooling provider, every application developer. openCypher is a continual work in progress. Over the next few months, we will move more and more of the language artifacts over to GitHub to make it available for everyone. openCypher is an open source project that delivers four key artifacts released under a permissive license: (i) the Cypher reference documentation, (ii) a Technology compatibility kit (TCK), (iii) Reference implementation (a fully functional implementation of key parts of the stack needed to support Cypher inside a data platform or tool) and (iv) the Cypher language specification. We are also seeking to make the process of specifying and evolving the Cypher query language as open as possible, and are actively seeking comments and suggestions on how to improve the Cypher query language. The purpose of this talk is to provide more details regarding the above-mentioned aspects.</span></div></div><div class="" id=":Rbr4pkf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rbr4pkf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="whatsHot-card-description-15" aria-haspopup="dialog" aria-controls=":Rc34pkf6:" popovertarget=":Rc34pkf6:" style="anchor-name:--popover-Rc34pkf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/training-week-introduction-to-neo4j/250183108"><span class="sr-only">Training Week: Introduction to Neo4j</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:15" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Training Week: Introduction to Neo4j" src="https://cdn.slidesharecdn.com/ss_thumbnails/introductiontoneo4j-ahands-oncrashcourse2-210913150256-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Training Week: Introduction to Neo4j" src="https://cdn.slidesharecdn.com/ss_thumbnails/introductiontoneo4j-ahands-oncrashcourse2-210913150256-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Training Week: Introduction to Neo4j</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Training Week: Introduction to Neo4j for later" role="switch" aria-haspopup="dialog" aria-controls=":R2rc34pkf6:" popovertarget=":R2rc34pkf6:" style="anchor-name:--popover-R2rc34pkf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2rc34pkf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2rc34pkf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/neo4j">Neo4j</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">This document provides an introduction to Neo4j and graph databases. It discusses what a graph is, why graphs are useful, examples of graph scenarios, the components of a property graph database including nodes, relationships and properties, and how to query graphs using Cypher. It also promotes additional Neo4j training resources and encourages continuing the user's graph journey.</span></div></div><div class="" id=":Rc34pkf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rc34pkf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="whatsHot-card-description-16" aria-haspopup="dialog" aria-controls=":Rcb4pkf6:" popovertarget=":Rcb4pkf6:" style="anchor-name:--popover-Rcb4pkf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/introduction-to-graph-database/31330223"><span class="sr-only">Introduction to Graph Database</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:16" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Introduction to Graph Database" src="https://cdn.slidesharecdn.com/ss_thumbnails/lsm3241-gdbms-140218033708-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Introduction to Graph Database" src="https://cdn.slidesharecdn.com/ss_thumbnails/lsm3241-gdbms-140218033708-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Introduction to Graph Database</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Introduction to Graph Database for later" role="switch" aria-haspopup="dialog" aria-controls=":R2rcb4pkf6:" popovertarget=":R2rcb4pkf6:" style="anchor-name:--popover-R2rcb4pkf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2rcb4pkf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2rcb4pkf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/leezhenyu">Eric Lee</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">Introduction to Graph database, using K-pop as a database modelling case. From the idea of graph database, Neo4j installation, modelling, Cypher to business application.</span></div></div><div class="" id=":Rcb4pkf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rcb4pkf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="whatsHot-card-description-17" aria-haspopup="dialog" aria-controls=":Rcj4pkf6:" popovertarget=":Rcj4pkf6:" style="anchor-name:--popover-Rcj4pkf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/introduction-to-neo4j-for-the-emirates-bahrain/242255825"><span class="sr-only">Introduction to Neo4j for the Emirates & Bahrain</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:17" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Introduction to Neo4j for the Emirates & Bahrain" src="https://cdn.slidesharecdn.com/ss_thumbnails/introductiontoneo4juaebaharain-210204094723-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Introduction to Neo4j for the Emirates & Bahrain" src="https://cdn.slidesharecdn.com/ss_thumbnails/introductiontoneo4juaebaharain-210204094723-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Introduction to Neo4j for the Emirates & Bahrain</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Introduction to Neo4j for the Emirates & Bahrain for later" role="switch" aria-haspopup="dialog" aria-controls=":R2rcj4pkf6:" popovertarget=":R2rcj4pkf6:" style="anchor-name:--popover-R2rcj4pkf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2rcj4pkf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2rcj4pkf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/neo4j">Neo4j</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">This document provides an agenda and overview of a Neo4j presentation. It discusses Neo4j as the leading native graph database, its graph data science capabilities, and deployment options like Neo4j Aura and Cloud Managed Services. Success stories are highlighted like Minka using Neo4j Aura to power Colombia's new real-time ACH payments system. The presentation aims to demonstrate Neo4j's technology, use cases, and how it can drive business value through connecting data.</span></div></div><div class="" id=":Rcj4pkf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rcj4pkf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="whatsHot-card-description-18" aria-haspopup="dialog" aria-controls=":Rcr4pkf6:" popovertarget=":Rcr4pkf6:" style="anchor-name:--popover-Rcr4pkf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/jena-193716/193716"><span class="sr-only">Jena</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:18" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Jena" src="https://cdn.slidesharecdn.com/ss_thumbnails/jena-1196913303282065-3-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Jena" src="https://cdn.slidesharecdn.com/ss_thumbnails/jena-1196913303282065-3-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Jena</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Jena for later" role="switch" aria-haspopup="dialog" aria-controls=":R2rcr4pkf6:" popovertarget=":R2rcr4pkf6:" style="anchor-name:--popover-R2rcr4pkf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2rcr4pkf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2rcr4pkf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/yuhana">yuhana</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">This document provides instructions for installing and running Jena, a Java framework for building semantic web and linked data applications. 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A native graph database like Neo4j naturally stores, manages, analyzes, and uses data within the context of connections meaning Neo4j provides faster query performance and vastly improved flexibility in handling complex hierarchies than SQL.</span></div></div><div class="" id=":Rd34pkf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rd34pkf6"></div></div><div class="desktop-recs"><div class="Slider_root__c0Jo8"><div class="Slider_scroller__KHjw4"><div class="BottomRecommendationCard_root__gffTk SlideshowCard_root__pD8t4 slideshow-card"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/intro-to-neo4j-and-dot-net2/49471265"><span class="sr-only">Introduction to Neo4j and .Net</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:16 / 9;--index:0" data-testid="card-thumbnail"><img 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Computing</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:0" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Quantum Processes in Graph Computing" src="https://cdn.slidesharecdn.com/ss_thumbnails/quantum-gremlin-graphday-160114154937-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Quantum Processes in Graph Computing" src="https://cdn.slidesharecdn.com/ss_thumbnails/quantum-gremlin-graphday-160114154937-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Quantum Processes in Graph Computing</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Quantum Processes in Graph Computing for later" role="switch" aria-haspopup="dialog" aria-controls=":R2r8b59kf6:" popovertarget=":R2r8b59kf6:" style="anchor-name:--popover-R2r8b59kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2r8b59kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2r8b59kf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/slidarko">Marko Rodriguez</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">This presentation was given on January 17, 2016 at the GraphDay conference in Austin, Texas. The slides demonstrate the use of wave dynamics in graph structures. Moreover, they demonstrate how to implement quantum processes on graph structures. There is an associated article available at http://arxiv.org/abs/1511.06278 (Quantum Walks with Gremlin).</span></div></div><div class="" id=":R8b59kf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-R8b59kf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="alsoLiked-card-description-1" aria-haspopup="dialog" aria-controls=":R8j59kf6:" popovertarget=":R8j59kf6:" style="anchor-name:--popover-R8j59kf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/gremlin-a-graphbased-programming-language-3876581/3876581"><span class="sr-only">Gremlin: A Graph-Based Programming Language</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:1" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Gremlin: A Graph-Based Programming Language" src="https://cdn.slidesharecdn.com/ss_thumbnails/cnls-gremlin-2010-100427185653-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Gremlin: A Graph-Based Programming Language" src="https://cdn.slidesharecdn.com/ss_thumbnails/cnls-gremlin-2010-100427185653-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Gremlin: A Graph-Based Programming Language</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Gremlin: A Graph-Based Programming Language for later" role="switch" aria-haspopup="dialog" aria-controls=":R2r8j59kf6:" popovertarget=":R2r8j59kf6:" style="anchor-name:--popover-R2r8j59kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2r8j59kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2r8j59kf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/slidarko">Marko Rodriguez</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">Gremlin is a Turing-complete, graph-based programming language developed for key/value-pair multi-relational graphs called property graphs. Gremlin makes extensive use of XPath 1.0 to support complex graph traversals. Connectors exist to various graph databases and frameworks. This language has application in the areas of graph query, analysis, and manipulation.</span></div></div><div class="" id=":R8j59kf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-R8j59kf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="alsoLiked-card-description-2" aria-haspopup="dialog" aria-controls=":R8r59kf6:" popovertarget=":R8r59kf6:" style="anchor-name:--popover-R8r59kf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/tinkerpopfinal/53171958"><span class="sr-only">Cassandra Summit - What's New In Apache TinkerPop?</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:2" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Cassandra Summit - What's New In Apache TinkerPop?" src="https://cdn.slidesharecdn.com/ss_thumbnails/0af6712c-b24a-4dec-be9d-bae8f3c3be0b-150924214013-lva1-app6892-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Cassandra Summit - What's New In Apache TinkerPop?" src="https://cdn.slidesharecdn.com/ss_thumbnails/0af6712c-b24a-4dec-be9d-bae8f3c3be0b-150924214013-lva1-app6892-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Cassandra Summit - What's New In Apache TinkerPop?</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Cassandra Summit - What's New In Apache TinkerPop? for later" role="switch" aria-haspopup="dialog" aria-controls=":R2r8r59kf6:" popovertarget=":R2r8r59kf6:" style="anchor-name:--popover-R2r8r59kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2r8r59kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2r8r59kf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/StephenMallette">Stephen Mallette</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">The document provides an overview of Apache TinkerPop, an open source graph computing framework. It discusses new features in recent versions of TinkerPop, including support for both imperative and declarative querying in Gremlin 3.0. It also demonstrates how to load and query graph data stored in HDFS using TinkerPop and Spark, and how to visualize subgraphs in Gephi.</span></div></div><div class="" id=":R8r59kf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-R8r59kf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="alsoLiked-card-description-3" aria-haspopup="dialog" aria-controls=":R9359kf6:" popovertarget=":R9359kf6:" style="anchor-name:--popover-R9359kf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/traversing-graph-databases-with-gremlin/8019871"><span class="sr-only">Traversing Graph Databases with Gremlin</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:3" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Traversing Graph Databases with Gremlin" src="https://cdn.slidesharecdn.com/ss_thumbnails/gremlin-nyc2011-110518211741-phpapp01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Traversing Graph Databases with Gremlin" src="https://cdn.slidesharecdn.com/ss_thumbnails/gremlin-nyc2011-110518211741-phpapp01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Traversing Graph Databases with Gremlin</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Traversing Graph Databases with Gremlin for later" role="switch" aria-haspopup="dialog" aria-controls=":R2r9359kf6:" popovertarget=":R2r9359kf6:" style="anchor-name:--popover-R2r9359kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2r9359kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2r9359kf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/slidarko">Marko Rodriguez</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">A discussion of Blueprints, Pipes, and Gremlin. The presentation's second half was a live Gremlin tutorial/demo.</span></div></div><div class="" id=":R9359kf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-R9359kf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="alsoLiked-card-description-4" aria-haspopup="dialog" aria-controls=":R9b59kf6:" popovertarget=":R9b59kf6:" style="anchor-name:--popover-R9b59kf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/calebwjones/intro-to-graph-databases-using-tinkerpops-titandb-and-gremlin"><span class="sr-only">Intro to Graph Databases Using Tinkerpop, TitanDB, and Gremlin</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:4" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Intro to Graph Databases Using Tinkerpop, TitanDB, and Gremlin" src="https://cdn.slidesharecdn.com/ss_thumbnails/titan-tinkerpop-gremlin-140401235331-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Intro to Graph Databases Using Tinkerpop, TitanDB, and Gremlin" src="https://cdn.slidesharecdn.com/ss_thumbnails/titan-tinkerpop-gremlin-140401235331-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Intro to Graph Databases Using Tinkerpop, TitanDB, and Gremlin</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Intro to Graph Databases Using Tinkerpop, TitanDB, and Gremlin for later" role="switch" aria-haspopup="dialog" aria-controls=":R2r9b59kf6:" popovertarget=":R2r9b59kf6:" style="anchor-name:--popover-R2r9b59kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2r9b59kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2r9b59kf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/calebwjones">Caleb Jones</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">A quick overview of the history, motivation, and uses of graph modeling and graph databases in various industries. Covers a brief introduction to graph databases with an emphasis on the Tinkerpop stack and Gremlin query language. These concepts are then solidified through a hands-on lab modeling a blog engine using Titan and Gremlin. See more at http://allthingsgraphed.com.</span></div></div><div class="" id=":R9b59kf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-R9b59kf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="alsoLiked-card-description-5" aria-haspopup="dialog" aria-controls=":R9j59kf6:" popovertarget=":R9j59kf6:" style="anchor-name:--popover-R9j59kf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/the-path-forward/42481383"><span class="sr-only">The Path Forward</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:5" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="The Path Forward" src="https://cdn.slidesharecdn.com/ss_thumbnails/the-path-forward-2014-141208115804-conversion-gate02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="The Path Forward" src="https://cdn.slidesharecdn.com/ss_thumbnails/the-path-forward-2014-141208115804-conversion-gate02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">The Path Forward</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save The Path Forward for later" role="switch" aria-haspopup="dialog" aria-controls=":R2r9j59kf6:" popovertarget=":R2r9j59kf6:" style="anchor-name:--popover-R2r9j59kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2r9j59kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2r9j59kf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/slidarko">Marko Rodriguez</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">This document discusses graph-based computing and traversal using Gremlin and Titan. It provides examples of querying a graph about relationships between characters in Greek mythology like Hercules. Traversal operations are demonstrated to find other characters Hercules may know or which actor played him in a movie. The value of graph analysis for insights and recommendations is also discussed.</span></div></div><div class="" id=":R9j59kf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-R9j59kf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="alsoLiked-card-description-6" aria-haspopup="dialog" aria-controls=":R9r59kf6:" popovertarget=":R9r59kf6:" style="anchor-name:--popover-R9r59kf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/the-gremlin-in-the-graph/6835536"><span class="sr-only">The Gremlin in the Graph</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:6" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="The Gremlin in the Graph" src="https://cdn.slidesharecdn.com/ss_thumbnails/gremlin-uim-2011-110207003951-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="The Gremlin in the Graph" src="https://cdn.slidesharecdn.com/ss_thumbnails/gremlin-uim-2011-110207003951-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">The Gremlin in the Graph</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save The Gremlin in the Graph for later" role="switch" aria-haspopup="dialog" aria-controls=":R2r9r59kf6:" popovertarget=":R2r9r59kf6:" style="anchor-name:--popover-R2r9r59kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2r9r59kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2r9r59kf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/slidarko">Marko Rodriguez</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">This tutorial/lecture addresses various aspects of the graph traversal language Gremlin. In particular, the presentation focuses on Gremlin 0.7 and its application to graph analysis and manipulation.</span></div></div><div class="" id=":R9r59kf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-R9r59kf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="alsoLiked-card-description-7" aria-haspopup="dialog" aria-controls=":Ra359kf6:" popovertarget=":Ra359kf6:" style="anchor-name:--popover-Ra359kf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/titan-big-graph-data-with-cassandra/13914564"><span class="sr-only">Titan: Big Graph Data with Cassandra</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:7" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Titan: Big Graph Data with Cassandra" src="https://cdn.slidesharecdn.com/ss_thumbnails/titancassandra-120808134054-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Titan: Big Graph Data with Cassandra" src="https://cdn.slidesharecdn.com/ss_thumbnails/titancassandra-120808134054-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Titan: Big Graph Data with Cassandra</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Titan: Big Graph Data with Cassandra for later" role="switch" aria-haspopup="dialog" aria-controls=":R2ra359kf6:" popovertarget=":R2ra359kf6:" style="anchor-name:--popover-R2ra359kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2ra359kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2ra359kf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/knowfrominfo">Matthias Broecheler</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">Titan is an open source distributed graph database build on top of Cassandra that can power real-time applications with thousands of concurrent users over graphs with billions of edges. Graphs are a versatile data model for capturing and analyzing rich relational structures. Graphs are an increasingly popular way to represent data in a wide range of domains such as social networking, recommendation engines, advertisement optimization, knowledge representation, health care, education, and security. This presentation discusses Titan's data model, query language, and novel techniques in edge compression, data layout, and vertex-centric indices which facilitate the representation and processing of Big Graph Data across a Cassandra cluster. We demonstrate Titan's performance on a large scale benchmark evaluation using Twitter data. Presented at the Cassandra 2012 Summit. </span></div></div><div class="" id=":Ra359kf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Ra359kf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="alsoLiked-card-description-8" aria-haspopup="dialog" aria-controls=":Rab59kf6:" popovertarget=":Rab59kf6:" style="anchor-name:--popover-Rab59kf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/yow-australia2012/15459071"><span class="sr-only">Solving Problems with Graphs</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:8" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Solving Problems with Graphs" src="https://cdn.slidesharecdn.com/ss_thumbnails/yow-australia-2012-121202224618-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Solving Problems with Graphs" src="https://cdn.slidesharecdn.com/ss_thumbnails/yow-australia-2012-121202224618-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Solving Problems with Graphs</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Solving Problems with Graphs for later" role="switch" aria-haspopup="dialog" aria-controls=":R2rab59kf6:" popovertarget=":R2rab59kf6:" style="anchor-name:--popover-R2rab59kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2rab59kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2rab59kf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/slidarko">Marko Rodriguez</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">Who am I and why do I feel that the world is not infinitely perfect? Which technologies should I use to rectify this situation? Enter the graph and the graph traversal.</span></div></div><div class="" id=":Rab59kf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rab59kf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="alsoLiked-card-description-9" aria-haspopup="dialog" aria-controls=":Raj59kf6:" popovertarget=":Raj59kf6:" style="anchor-name:--popover-Raj59kf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/cassandra-virtual-node-talk/16561245"><span class="sr-only">Cassandra Virtual Node talk</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:9" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Cassandra Virtual Node talk" src="https://cdn.slidesharecdn.com/ss_thumbnails/visforvnodes-130215230441-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Cassandra Virtual Node talk" src="https://cdn.slidesharecdn.com/ss_thumbnails/visforvnodes-130215230441-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Cassandra Virtual Node talk</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Cassandra Virtual Node talk for later" role="switch" aria-haspopup="dialog" aria-controls=":R2raj59kf6:" popovertarget=":R2raj59kf6:" style="anchor-name:--popover-R2raj59kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2raj59kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2raj59kf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/patrickmcfadin">Patrick McFadin</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">The document discusses the introduction of virtual nodes in Cassandra 1.2. It explains that virtual nodes allow a single server to handle multiple token ranges, improving hardware utilization and simplifying operations. The transition involves changing configuration settings to enable multiple tokens per node and initiating a shuffling process to redistribute data. Virtual nodes provide benefits like faster rebuilds and adding new nodes without complex token management.</span></div></div><div class="" id=":Raj59kf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Raj59kf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="alsoLiked-card-description-10" aria-haspopup="dialog" aria-controls=":Rar59kf6:" popovertarget=":Rar59kf6:" style="anchor-name:--popover-Rar59kf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/temporal-dynamics-of-human-behavior-in-social-networks-i/47718822"><span class="sr-only">Temporal dynamics of human behavior in social networks (i)</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:10" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Temporal dynamics of human behavior in social networks (i)" src="https://cdn.slidesharecdn.com/ss_thumbnails/temporaldynamicsofhumanbehaviorinsocialnetworksi-150504040905-conversion-gate01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Temporal dynamics of human behavior in social networks (i)" src="https://cdn.slidesharecdn.com/ss_thumbnails/temporaldynamicsofhumanbehaviorinsocialnetworksi-150504040905-conversion-gate01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Temporal dynamics of human behavior in social networks (i)</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Temporal dynamics of human behavior in social networks (i) for later" role="switch" aria-haspopup="dialog" aria-controls=":R2rar59kf6:" popovertarget=":R2rar59kf6:" style="anchor-name:--popover-R2rar59kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2rar59kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2rar59kf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/emoro">Esteban Moro</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">First Lecture on Temporal Dynamics given at 2014 Les Houches School on Complex Networks http://leshouches2014.weebly.com/lecturers.html</span></div></div><div class="" id=":Rar59kf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rar59kf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="alsoLiked-card-description-11" aria-haspopup="dialog" aria-controls=":Rb359kf6:" popovertarget=":Rb359kf6:" style="anchor-name:--popover-Rb359kf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/bell-smith-tyrusamigospresentation-26472430/26472430"><span class="sr-only">Putting the Dance Theatre of Harlem Archives Back Together</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:11" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Putting the Dance Theatre of Harlem Archives Back Together" src="https://cdn.slidesharecdn.com/ss_thumbnails/bellsmithtyrusamigospresentation-130923155831-phpapp01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Putting the Dance Theatre of Harlem Archives Back Together" src="https://cdn.slidesharecdn.com/ss_thumbnails/bellsmithtyrusamigospresentation-130923155831-phpapp01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Putting the Dance Theatre of Harlem Archives Back Together</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Putting the Dance Theatre of Harlem Archives Back Together for later" role="switch" aria-haspopup="dialog" aria-controls=":R2rb359kf6:" popovertarget=":R2rb359kf6:" style="anchor-name:--popover-R2rb359kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2rb359kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2rb359kf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/danceheritage">danceheritage</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">How the Dance Heritage Coalition aided in the creation of an archival system for the Dance Theatre of Harlem. The organizers share lessons learned and their next steps!</span></div></div><div class="" id=":Rb359kf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rb359kf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="alsoLiked-card-description-12" aria-haspopup="dialog" aria-controls=":Rbb59kf6:" popovertarget=":Rbb59kf6:" style="anchor-name:--popover-Rbb59kf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/european-government-bond-correlation-dynamics-taming-contagion-risks/52699882"><span class="sr-only">European Government Bond Correlation Dynamics: Taming Contagion Risks</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:12" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="European Government Bond Correlation Dynamics: Taming Contagion Risks" src="https://cdn.slidesharecdn.com/ss_thumbnails/schwendnereurozone20150909-150912111634-lva1-app6892-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="European Government Bond Correlation Dynamics: Taming Contagion Risks" src="https://cdn.slidesharecdn.com/ss_thumbnails/schwendnereurozone20150909-150912111634-lva1-app6892-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">European Government Bond Correlation Dynamics: Taming Contagion Risks</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save European Government Bond Correlation Dynamics: Taming Contagion Risks for later" role="switch" aria-haspopup="dialog" aria-controls=":R2rbb59kf6:" popovertarget=":R2rbb59kf6:" style="anchor-name:--popover-R2rbb59kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2rbb59kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2rbb59kf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/PeterSchwendner">Peter Schwendner</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">The document analyzes the dynamics of European government bond yields and correlations between countries from 2004-2015. It finds that bond yield correlations increased during the Eurozone crisis but have since stabilized, with positive correlations mainly between core countries and negative correlations between core and peripheral countries. A filtered partial correlation method is used to analyze dominant influences between bond markets while filtering out noise. Case studies on the Greek debt crisis find that negotiations implied increasing contagion risks beyond just Greece.</span></div></div><div class="" id=":Rbb59kf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rbb59kf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="alsoLiked-card-description-13" aria-haspopup="dialog" aria-controls=":Rbj59kf6:" popovertarget=":Rbj59kf6:" style="anchor-name:--popover-Rbj59kf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/titan-the-rise-of-big-graph-data/13328271"><span class="sr-only">Titan: The Rise of Big Graph Data</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:13" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Titan: The Rise of Big Graph Data" src="https://cdn.slidesharecdn.com/ss_thumbnails/titan-biggraphdata-2012-120614135441-phpapp01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Titan: The Rise of Big Graph Data" src="https://cdn.slidesharecdn.com/ss_thumbnails/titan-biggraphdata-2012-120614135441-phpapp01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Titan: The Rise of Big Graph Data</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Titan: The Rise of Big Graph Data for later" role="switch" aria-haspopup="dialog" aria-controls=":R2rbj59kf6:" popovertarget=":R2rbj59kf6:" style="anchor-name:--popover-R2rbj59kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2rbj59kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2rbj59kf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/slidarko">Marko Rodriguez</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">The document discusses graphs and graph databases. It introduces the concept of property graphs and how they can intuitively model complex relationships between entities. It discusses how graph traversal enables expressive querying and numerous analyses of graph data. The document uses examples involving Greek mythology to illustrate graph concepts and traversal queries.</span></div></div><div class="" id=":Rbj59kf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rbj59kf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="alsoLiked-card-description-14" aria-haspopup="dialog" aria-controls=":Rbr59kf6:" popovertarget=":Rbr59kf6:" style="anchor-name:--popover-Rbr59kf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/130530-interbankmarketscastellon/22304974"><span class="sr-only">Network Approaches for Interbank Markets</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:14" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Network Approaches for Interbank Markets" src="https://cdn.slidesharecdn.com/ss_thumbnails/130530-interbank-marketscastellon-130601151348-phpapp01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Network Approaches for Interbank Markets" src="https://cdn.slidesharecdn.com/ss_thumbnails/130530-interbank-marketscastellon-130601151348-phpapp01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Network Approaches for Interbank Markets</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Network Approaches for Interbank Markets for later" role="switch" aria-haspopup="dialog" aria-controls=":R2rbr59kf6:" popovertarget=":R2rbr59kf6:" style="anchor-name:--popover-R2rbr59kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2rbr59kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2rbr59kf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/soramaki">Kimmo Soramaki</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">This document summarizes Dr. Kimmo Soramäki's invited talk on applying network theory to interbank markets. The talk discusses (1) how network theory can provide insights into systemic risk by mapping interlinkages between financial institutions, (2) empirical analysis of interbank payment networks that show their scale-free structure, and (3) new network-based models and metrics for analyzing contagion risk and identifying systematically important institutions. The talk prioritizes further research in measuring interconnectedness, modeling contagion processes, developing systemic risk metrics, and network visualization techniques.</span></div></div><div class="" id=":Rbr59kf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rbr59kf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="alsoLiked-card-description-15" aria-haspopup="dialog" aria-controls=":Rc359kf6:" popovertarget=":Rc359kf6:" style="anchor-name:--popover-Rc359kf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/datastax-whats-new-in-apache-tinkerpop-the-graph-computing-framework/53500812"><span class="sr-only">DataStax: What's New in Apache TinkerPop - the Graph Computing Framework</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:15" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="DataStax: What's New in Apache TinkerPop - the Graph Computing Framework" src="https://cdn.slidesharecdn.com/ss_thumbnails/tinkerpop-151003202022-lva1-app6892-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="DataStax: What's New in Apache TinkerPop - the Graph Computing Framework" src="https://cdn.slidesharecdn.com/ss_thumbnails/tinkerpop-151003202022-lva1-app6892-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">DataStax: What's New in Apache TinkerPop - the Graph Computing Framework</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save DataStax: What's New in Apache TinkerPop - the Graph Computing Framework for later" role="switch" aria-haspopup="dialog" aria-controls=":R2rc359kf6:" popovertarget=":R2rc359kf6:" style="anchor-name:--popover-R2rc359kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2rc359kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2rc359kf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/planetcassandra">DataStax Academy</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">Apache TinkerPop is an open source graph computing framework, which centralizes around the Gremlin graph traversal language. It provides a number of libraries and utilities that help simplify the development of graph-related applications. Apache TinkerPop has always provided a vendor-agnostic way to work with different graph databases, like Titan and Neo4j, but now, under TinkerPop3, provides similar capabilities for scalable computation frameworks, like Hadoop and Spark. TinkerPop3 introduces many reinvented concepts from earlier versions of the TinkerPop stack and provides new capabilities that together will require those familiar with TinkerPop to adjust their thinking and those new to the ecosystem to be aware of the important features it presents. This talk will provide an overview of "what's new" in TinkerPop3 and provide detail on the Gremlin query language and supporting utilities, like Gremlin Console and Gremlin Server, which help support analysis and application development. </span></div></div><div class="" id=":Rc359kf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rc359kf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="alsoLiked-card-description-16" aria-haspopup="dialog" aria-controls=":Rcb59kf6:" popovertarget=":Rcb59kf6:" style="anchor-name:--popover-Rcb59kf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/f8-tech-talkpinterestv4/34490460"><span class="sr-only">F8 tech talk_pinterest_v4</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:16" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="F8 tech talk_pinterest_v4" src="https://cdn.slidesharecdn.com/ss_thumbnails/f8techtalkpinterestv4-140509125147-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="F8 tech talk_pinterest_v4" src="https://cdn.slidesharecdn.com/ss_thumbnails/f8techtalkpinterestv4-140509125147-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">F8 tech talk_pinterest_v4</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save F8 tech talk_pinterest_v4 for later" role="switch" aria-haspopup="dialog" aria-controls=":R2rcb59kf6:" popovertarget=":R2rcb59kf6:" style="anchor-name:--popover-R2rcb59kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2rcb59kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2rcb59kf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/malorie_pinterest">malorie_pinterest</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">This document summarizes an agenda for a Pinterest Engineering meeting. It includes discussions on mobile growth and monetization, deploying and shipping code. Specific topics that will be covered include scaling user education on mobile, growth strategies like user education, monetization through data, and how Pinterest deploys and ships code. Speakers will discuss mobile features, how user growth is driven through education, monetizing user data, and ensuring smooth code deployment.</span></div></div><div class="" id=":Rcb59kf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rcb59kf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="alsoLiked-card-description-17" aria-haspopup="dialog" aria-controls=":Rcj59kf6:" popovertarget=":Rcj59kf6:" style="anchor-name:--popover-Rcj59kf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/seda-an-architecture-for-wellconditioned-scalable-internet-services/55019251"><span class="sr-only">Seda an architecture for well-conditioned scalable internet services</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:17" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Seda an architecture for well-conditioned scalable internet services" src="https://cdn.slidesharecdn.com/ss_thumbnails/seda-anarchitectureforwell-conditionedscalableinternetservices-151112004107-lva1-app6892-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Seda an architecture for well-conditioned scalable internet services" src="https://cdn.slidesharecdn.com/ss_thumbnails/seda-anarchitectureforwell-conditionedscalableinternetservices-151112004107-lva1-app6892-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Seda an architecture for well-conditioned scalable internet services</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Seda an architecture for well-conditioned scalable internet services for later" role="switch" aria-haspopup="dialog" aria-controls=":R2rcj59kf6:" popovertarget=":R2rcj59kf6:" style="anchor-name:--popover-R2rcj59kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2rcj59kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2rcj59kf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/bdemchak">bdemchak</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">The document describes the SEDA (Staged Event-Driven Architecture) framework. SEDA divides applications into stages connected by queues. Each stage has a thread pool and dynamic resource controllers that adjust thread allocation to meet performance targets. This allows applications built with SEDA to scale responsive and robustly handle varying load. SEDA was implemented in a system called Sandstorm that provides APIs for building networked services using asynchronous I/O and event-driven programming. 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style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2r8b5pkf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2r8b5pkf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/msfclipper">Mahmoud Samir Fayed</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">The document describes running multiple threads that print output. Thread 1 prints numbers from 1 to 5. Thread 2 prints strings with asterisks and numbers. Thread 3 prints strings with exclamation marks and numbers. The output shows the interleaved output from the three threads running concurrently, demonstrating thread synchronization in Ring.</span></div></div><div class="" id=":R8b5pkf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-R8b5pkf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="similarTo-card-description-1" aria-haspopup="dialog" aria-controls=":R8j5pkf6:" popovertarget=":R8j5pkf6:" style="anchor-name:--popover-R8j5pkf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/simulator-customizing-testing-for-xcode-9/84130213"><span class="sr-only">Simulator customizing & testing for Xcode 9</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:1" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Simulator customizing & testing for Xcode 9" src="https://cdn.slidesharecdn.com/ss_thumbnails/simulatorcustomizingtesting-171215043146-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Simulator customizing & testing for Xcode 9" src="https://cdn.slidesharecdn.com/ss_thumbnails/simulatorcustomizingtesting-171215043146-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Simulator customizing & testing for Xcode 9</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Simulator customizing & testing for Xcode 9 for later" role="switch" aria-haspopup="dialog" aria-controls=":R2r8j5pkf6:" popovertarget=":R2r8j5pkf6:" style="anchor-name:--popover-R2r8j5pkf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2r8j5pkf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2r8j5pkf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/itpersons">Bongwon Lee</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">Simulator allows you to rapidly prototype and test builds of your app during development. It provides tools to manage simulator devices, install and launch apps, pass arguments, and test in different configurations and languages. The simctl command can be used to control simulators, while Xcode builds and deploys apps to the simulator.</span></div></div><div class="" id=":R8j5pkf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-R8j5pkf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="similarTo-card-description-2" aria-haspopup="dialog" aria-controls=":R8r5pkf6:" popovertarget=":R8r5pkf6:" style="anchor-name:--popover-R8r5pkf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/a-gentle-introduction-to-functional-programming-through-music-and-clojure/55501861"><span class="sr-only">A gentle introduction to functional programming through music and clojure</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:2" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="A gentle introduction to functional programming through music and clojure" src="https://cdn.slidesharecdn.com/ss_thumbnails/agentleintroductiontofunctionalprogrammingthroughmusicandclojure-151125111603-lva1-app6892-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="A gentle introduction to functional programming through music and clojure" src="https://cdn.slidesharecdn.com/ss_thumbnails/agentleintroductiontofunctionalprogrammingthroughmusicandclojure-151125111603-lva1-app6892-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">A gentle introduction to functional programming through music and clojure</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save A gentle introduction to functional programming through music and clojure for later" role="switch" aria-haspopup="dialog" aria-controls=":R2r8r5pkf6:" popovertarget=":R2r8r5pkf6:" style="anchor-name:--popover-R2r8r5pkf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2r8r5pkf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2r8r5pkf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/quantisan">Paul Lam</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">This document introduces functional programming concepts through the Clojure programming language and the Overtone music library. It provides an overview of Clojure data types and collections, installing Leiningen and interacting with the Clojure REPL. Examples are given for working with lists, maps, sets and Java interop. The benefits of functional programming are listed as easier reasoning, composability, separation of concerns. Contact details are provided for further information.</span></div></div><div class="" id=":R8r5pkf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-R8r5pkf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="similarTo-card-description-3" aria-haspopup="dialog" aria-controls=":R935pkf6:" popovertarget=":R935pkf6:" style="anchor-name:--popover-R935pkf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/fffp/38338903"><span class="sr-only">Fact, Fiction, and FP</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:3" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Fact, Fiction, and FP" src="https://cdn.slidesharecdn.com/ss_thumbnails/fffp-140825134133-phpapp01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Fact, Fiction, and FP" src="https://cdn.slidesharecdn.com/ss_thumbnails/fffp-140825134133-phpapp01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Fact, Fiction, and FP</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Fact, Fiction, and FP for later" role="switch" aria-haspopup="dialog" aria-controls=":R2r935pkf6:" popovertarget=":R2r935pkf6:" style="anchor-name:--popover-R2r935pkf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2r935pkf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2r935pkf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/drboolean">Brian Lonsdorf</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">This document provides examples of functional JavaScript code using point-free style and typeclasses. It includes code snippets demonstrating: - Composing functions using point-free style to remove unnecessary variables - Implementing common typeclass methods like map, chain, and ap for a Container type - Deriving typeclass instances for custom types to gain functionality like Functor, Applicative, Foldable - Using typeclasses to compose functions operating on different container types in a uniform way The document provides code samples but does not explain concepts in detail. It focuses on demonstrating point-free code and typeclass patterns through examples rather than performing in-depth explanations or performance analysis. Questions are provided at the end to prompt</span></div></div><div class="" id=":R935pkf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-R935pkf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="similarTo-card-description-4" aria-haspopup="dialog" aria-controls=":R9b5pkf6:" popovertarget=":R9b5pkf6:" style="anchor-name:--popover-R9b5pkf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/msfclipper/the-ring-programming-language-version-153-book-part-10-of-184"><span class="sr-only">The Ring programming language version 1.5.3 book - Part 10 of 184</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:4" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="The Ring programming language version 1.5.3 book - Part 10 of 184" src="https://cdn.slidesharecdn.com/ss_thumbnails/91fayedringdoc1-180327101359-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="The Ring programming language version 1.5.3 book - Part 10 of 184" src="https://cdn.slidesharecdn.com/ss_thumbnails/91fayedringdoc1-180327101359-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">The Ring programming language version 1.5.3 book - Part 10 of 184</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save The Ring programming language version 1.5.3 book - Part 10 of 184 for later" role="switch" aria-haspopup="dialog" aria-controls=":R2r9b5pkf6:" popovertarget=":R2r9b5pkf6:" style="anchor-name:--popover-R2r9b5pkf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2r9b5pkf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2r9b5pkf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/msfclipper">Mahmoud Samir Fayed</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">This document summarizes the key features and changes in Ring 1.5.3, including: - The trace library allows tracing function calls and opening an interactive debugger. An example uses a breakpoint. - The type hints library allows adding type information to improve code editors and static analysis. It supports user-defined types. - Overall the documentation and quality of Ring 1.5 has improved based on real-world usage. </span></div></div><div class="" id=":R9b5pkf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-R9b5pkf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="similarTo-card-description-5" aria-haspopup="dialog" aria-controls=":R9j5pkf6:" popovertarget=":R9j5pkf6:" style="anchor-name:--popover-R9j5pkf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/imager-package-in-r-and-examples/66734544"><span class="sr-only">imager package in R and examples..</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:5" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="imager package in R and examples.." src="https://cdn.slidesharecdn.com/ss_thumbnails/imager-161004191212-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="imager package in R and examples.." src="https://cdn.slidesharecdn.com/ss_thumbnails/imager-161004191212-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">imager package in R and examples..</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save imager package in R and examples.. for later" role="switch" aria-haspopup="dialog" aria-controls=":R2r9j5pkf6:" popovertarget=":R2r9j5pkf6:" style="anchor-name:--popover-R2r9j5pkf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2r9j5pkf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2r9j5pkf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/VolkanOBANMsc">Dr. Volkan OBAN</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">imager package in R and example References: http://dahtah.github.io/imager/ http://dahtah.github.io/imager/imager.html https://cran.r-project.org/web/packages/imager/imager.pdf</span></div></div><div class="" id=":R9j5pkf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-R9j5pkf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="similarTo-card-description-6" aria-haspopup="dialog" aria-controls=":R9r5pkf6:" popovertarget=":R9r5pkf6:" style="anchor-name:--popover-R9r5pkf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/groovy-and-grails-talk/279074"><span class="sr-only">Groovy and Grails talk</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:6" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Groovy and Grails talk" src="https://cdn.slidesharecdn.com/ss_thumbnails/groovy-and-grails-talk-1203798962226065-5-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Groovy and Grails talk" src="https://cdn.slidesharecdn.com/ss_thumbnails/groovy-and-grails-talk-1203798962226065-5-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Groovy and Grails talk</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Groovy and Grails talk for later" role="switch" aria-haspopup="dialog" aria-controls=":R2r9r5pkf6:" popovertarget=":R2r9r5pkf6:" style="anchor-name:--popover-R2r9r5pkf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2r9r5pkf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2r9r5pkf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/desistartups">desistartups</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">The document discusses Groovy and Grails. Groovy is a dynamic language for the JVM that is inspired by languages like Python and Ruby. It allows seamless integration with Java classes and libraries. Grails is a web framework for Groovy that is inspired by Ruby on Rails. It uses Spring MVC, Hibernate, and other technologies to provide features like auto-generation of code and integration with databases. 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save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save dplyr for later" role="switch" aria-haspopup="dialog" aria-controls=":R2rbj5pkf6:" popovertarget=":R2rbj5pkf6:" style="anchor-name:--popover-R2rbj5pkf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2rbj5pkf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2rbj5pkf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/romainfrancois">Romain Francois</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">The document discusses the dplyr package for R. It provides examples of using dplyr verbs like filter, select, mutate, and summarise to subset and transform data frames. It also demonstrates grouping data with group_by and joining data with inner_join. The key features of dplyr are its simple verbs for filtering, modifying, arranging and summarizing data, its use of piping with %>%, and its convenience for working with tabular data.</span></div></div><div class="" id=":Rbj5pkf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rbj5pkf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="similarTo-card-description-14" aria-haspopup="dialog" aria-controls=":Rbr5pkf6:" popovertarget=":Rbr5pkf6:" style="anchor-name:--popover-Rbr5pkf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/murtaugh-2022-appl-comp-genomics-tidyverse-lecture-pptx-1-pptx/273825362"><span 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data-cy="slideshow-title">R programming language</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save R programming language for later" role="switch" aria-haspopup="dialog" aria-controls=":R2rc35pkf6:" popovertarget=":R2rc35pkf6:" style="anchor-name:--popover-R2rc35pkf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2rc35pkf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2rc35pkf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/bangirasu">Alberto Minetti</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">This document provides an overview of the R programming language. It describes R as a functional programming language for statistical computing and graphics that is open source and has over 6000 packages. Key features of R discussed include matrix calculation, data visualization, statistical analysis, machine learning, and data manipulation. The document also covers using R Studio as an IDE, reading and writing different data types, programming features like flow control and functions, and examples of correlation, regression, and plotting in R.</span></div></div><div class="" id=":Rc35pkf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rc35pkf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="similarTo-card-description-16" aria-haspopup="dialog" aria-controls=":Rcb5pkf6:" popovertarget=":Rcb5pkf6:" style="anchor-name:--popover-Rcb5pkf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/introduction-to-gremlin/12738258"><span class="sr-only">Introduction to Gremlin</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:16" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Introduction to Gremlin" src="https://cdn.slidesharecdn.com/ss_thumbnails/introductiontogremlin-120429165042-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Introduction to Gremlin" src="https://cdn.slidesharecdn.com/ss_thumbnails/introductiontogremlin-120429165042-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Introduction to Gremlin</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Introduction to Gremlin for later" role="switch" aria-haspopup="dialog" aria-controls=":R2rcb5pkf6:" popovertarget=":R2rcb5pkf6:" style="anchor-name:--popover-R2rcb5pkf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2rcb5pkf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2rcb5pkf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/maxdemarzi">Max De Marzi</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">Max De Marzi gave a presentation on Gremlin, a graph traversal language used for traversing property graphs. 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Finally, he presented a Gremlin script for providing movie recommendations based on a user's genres and ratings.</span></div></div><div class="" id=":Rcb5pkf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rcb5pkf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="similarTo-card-description-17" aria-haspopup="dialog" aria-controls=":Rcj5pkf6:" popovertarget=":Rcj5pkf6:" style="anchor-name:--popover-Rcj5pkf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/the-ring-programming-language-version-154-book-part-10-of-185/95016515"><span class="sr-only">The Ring programming language version 1.5.4 book - Part 10 of 185</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:17" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="The Ring programming language version 1.5.4 book - Part 10 of 185" src="https://cdn.slidesharecdn.com/ss_thumbnails/91ringfayedringdoc1-180425181042-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="The Ring programming language version 1.5.4 book - Part 10 of 185" src="https://cdn.slidesharecdn.com/ss_thumbnails/91ringfayedringdoc1-180425181042-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">The Ring programming language version 1.5.4 book - Part 10 of 185</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save The Ring programming language version 1.5.4 book - Part 10 of 185 for later" role="switch" aria-haspopup="dialog" aria-controls=":R2rcj5pkf6:" popovertarget=":R2rcj5pkf6:" style="anchor-name:--popover-R2rcj5pkf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2rcj5pkf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2rcj5pkf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/msfclipper">Mahmoud Samir Fayed</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">This document summarizes the key features and changes in Ring 1.5.2, including updates to the documentation, Ring Notepad, Form Designer, and sample applications. It provides code examples demonstrating new capabilities in the trace library, type hints library, OpenGL graphics, and event handling.</span></div></div><div class="" id=":Rcj5pkf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rcj5pkf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="similarTo-card-description-18" aria-haspopup="dialog" aria-controls=":Rcr5pkf6:" popovertarget=":Rcr5pkf6:" style="anchor-name:--popover-Rcr5pkf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/the-ring-programming-language-version-19-book-part-56-of-210/122719224"><span class="sr-only">The Ring programming language version 1.9 book - Part 56 of 210</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:18" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="The Ring programming language version 1.9 book - Part 56 of 210" src="https://cdn.slidesharecdn.com/ss_thumbnails/551ring-181111125622-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="The Ring programming language version 1.9 book - Part 56 of 210" src="https://cdn.slidesharecdn.com/ss_thumbnails/551ring-181111125622-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">The Ring programming language version 1.9 book - Part 56 of 210</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save The Ring programming language version 1.9 book - Part 56 of 210 for later" role="switch" aria-haspopup="dialog" aria-controls=":R2rcr5pkf6:" popovertarget=":R2rcr5pkf6:" style="anchor-name:--popover-R2rcr5pkf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2rcr5pkf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2rcr5pkf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/msfclipper">Mahmoud Samir Fayed</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">The document discusses using TrueType fonts, playing sound files, scaling and rotating images, displaying transparent images, and using threads in Ring using the Allegro library. 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BottomRecommendation_root__7aU9w"><h3 class="BottomRecommendation_title__SRj68">More from Marko Rodriguez <span class="BottomRecommendation_count__4HpLo">(20)</span></h3><div class="BottomRecommendationContent_root__2qm4_"><div class="mobile-recs"><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="moreFromUser-card-description-0" aria-haspopup="dialog" aria-controls=":R8b69kf6:" popovertarget=":R8b69kf6:" style="anchor-name:--popover-R8b69kf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/mmadt-a-virtual-machinean-economic-machine/224411576"><span class="sr-only">mm-ADT: A Virtual Machine/An Economic Machine</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:0" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="mm-ADT: A Virtual Machine/An Economic Machine" src="https://cdn.slidesharecdn.com/ss_thumbnails/datadays-2020-200125222428-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="mm-ADT: A Virtual Machine/An Economic Machine" src="https://cdn.slidesharecdn.com/ss_thumbnails/datadays-2020-200125222428-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">mm-ADT: A Virtual Machine/An Economic Machine</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save mm-ADT: A Virtual Machine/An Economic Machine for later" role="switch" aria-haspopup="dialog" aria-controls=":R2r8b69kf6:" popovertarget=":R2r8b69kf6:" style="anchor-name:--popover-R2r8b69kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2r8b69kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2r8b69kf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/slidarko">Marko Rodriguez</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">The mm-ADT virtual machine is looking to be an economic engine for our open source developers in the data technologies landscape. </span></div></div><div class="" id=":R8b69kf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-R8b69kf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="moreFromUser-card-description-1" aria-haspopup="dialog" aria-controls=":R8j69kf6:" popovertarget=":R8j69kf6:" style="anchor-name:--popover-R8j69kf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/mmadt-a-multimodel-abstract-data-type/170928548"><span class="sr-only">mm-ADT: A Multi-Model Abstract Data Type</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:1" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="mm-ADT: A Multi-Model Abstract Data Type" src="https://cdn.slidesharecdn.com/ss_thumbnails/apachecon-2019-190911190011-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="mm-ADT: A Multi-Model Abstract Data Type" src="https://cdn.slidesharecdn.com/ss_thumbnails/apachecon-2019-190911190011-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">mm-ADT: A Multi-Model Abstract Data Type</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save mm-ADT: A Multi-Model Abstract Data Type for later" role="switch" aria-haspopup="dialog" aria-controls=":R2r8j69kf6:" popovertarget=":R2r8j69kf6:" style="anchor-name:--popover-R2r8j69kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2r8j69kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2r8j69kf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/slidarko">Marko Rodriguez</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">The document describes mm-ADT, a proposed multi-model abstract datatype that aims to provide a universal data structure, processing model, and instruction set that can support various database models like graph, document, relational etc. in a common framework. Key goals are to release a stable mm-ADT specification, compiler and virtual machine, as well as a basic reference implementation by early 2020. The presentation focuses on the universal data structure component, describing how mm-ADT would define custom datatypes, instances, access paths and more using a bytecode language.</span></div></div><div class="" id=":R8j69kf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-R8j69kf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="moreFromUser-card-description-2" aria-haspopup="dialog" aria-controls=":R8r69kf6:" popovertarget=":R8r69kf6:" style="anchor-name:--popover-R8r69kf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/open-problems-in-the-universal-graph-theory/77013277"><span class="sr-only">Open Problems in the Universal Graph Theory</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:2" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Open Problems in the Universal Graph Theory" src="https://cdn.slidesharecdn.com/ss_thumbnails/the-universal-graph-170616182527-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Open Problems in the Universal Graph Theory" src="https://cdn.slidesharecdn.com/ss_thumbnails/the-universal-graph-170616182527-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Open Problems in the Universal Graph Theory</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Open Problems in the Universal Graph Theory for later" role="switch" aria-haspopup="dialog" aria-controls=":R2r8r69kf6:" popovertarget=":R2r8r69kf6:" style="anchor-name:--popover-R2r8r69kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2r8r69kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2r8r69kf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/slidarko">Marko Rodriguez</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">The document discusses the idea of the universal graph - that everything can be modeled as a graph of vertices and edges. It proposes some open problems regarding how to model processes and qualia as part of the universal graph structure, and how one might manipulate the laws of physics by altering the processes that govern the evolution of the physical world graph.</span></div></div><div class="" id=":R8r69kf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-R8r69kf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="moreFromUser-card-description-3" aria-haspopup="dialog" aria-controls=":R9369kf6:" popovertarget=":R9369kf6:" style="anchor-name:--popover-R9369kf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slidarko/gremlin-1013-on-your-fm-dial"><span class="sr-only">Gremlin 101.3 On Your FM Dial</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:3" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Gremlin 101.3 On Your FM Dial" src="https://cdn.slidesharecdn.com/ss_thumbnails/gremlin-workshop-2017-170427195932-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Gremlin 101.3 On Your FM Dial" src="https://cdn.slidesharecdn.com/ss_thumbnails/gremlin-workshop-2017-170427195932-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Gremlin 101.3 On Your FM Dial</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Gremlin 101.3 On Your FM Dial for later" role="switch" aria-haspopup="dialog" aria-controls=":R2r9369kf6:" popovertarget=":R2r9369kf6:" style="anchor-name:--popover-R2r9369kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2r9369kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2r9369kf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/slidarko">Marko Rodriguez</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">The Gremlin traversal machine is composed of three components: a graph, a traversal, and a set of traversers. Learn how these components interact to enable distributed, vendor-agnostic, OLTP/OLAP-based graph computing. This talk was presented live at DataStax's Support Summit in Carmel, CA (April 2017) and Engineering Summit in Las Vegas, NV (May 2017).</span></div></div><div class="" id=":R9369kf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-R9369kf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="moreFromUser-card-description-4" aria-haspopup="dialog" aria-controls=":R9b69kf6:" popovertarget=":R9b69kf6:" style="anchor-name:--popover-R9b69kf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/faunus-graph-analytics-engine/21219108"><span class="sr-only">Faunus: Graph Analytics Engine</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:4" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Faunus: Graph Analytics Engine" src="https://cdn.slidesharecdn.com/ss_thumbnails/faunus-graph-analytics-engine-130515151807-phpapp01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Faunus: Graph Analytics Engine" src="https://cdn.slidesharecdn.com/ss_thumbnails/faunus-graph-analytics-engine-130515151807-phpapp01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Faunus: Graph Analytics Engine</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Faunus: Graph Analytics Engine for later" role="switch" aria-haspopup="dialog" aria-controls=":R2r9b69kf6:" popovertarget=":R2r9b69kf6:" style="anchor-name:--popover-R2r9b69kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2r9b69kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2r9b69kf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/slidarko">Marko Rodriguez</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">Faunus is a graph analytics engine built atop the Hadoop distributed computing platform. The graph representation is a distributed adjacency list, whereby a vertex and its incident edges are co-located on the same machine. Querying a Faunus graph is possible with a MapReduce-variant of the Gremlin graph traversal language. A Gremlin expression compiles down to a series of MapReduce-steps that are sequence optimized and then executed by Hadoop. Results are stored as transformations to the input graph (graph derivations) or computational side-effects such as aggregates (graph statistics). Beyond querying, a collection of input/output formats are supported which enable Faunus to load/store graphs in the distributed graph database Titan, various graph formats stored in HDFS, and via arbitrary user-defined functions. This presentation will focus primarily on Faunus, but will also review the satellite technologies that enable it.</span></div></div><div class="" id=":R9b69kf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-R9b69kf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="moreFromUser-card-description-5" aria-haspopup="dialog" aria-controls=":R9j69kf6:" popovertarget=":R9j69kf6:" style="anchor-name:--popover-R9j69kf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/the-pathology-of-graph-databases/8422170"><span class="sr-only">The Pathology of Graph Databases</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:5" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="The Pathology of Graph Databases" src="https://cdn.slidesharecdn.com/ss_thumbnails/windycitydb-2011-110625100704-phpapp01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="The Pathology of Graph Databases" src="https://cdn.slidesharecdn.com/ss_thumbnails/windycitydb-2011-110625100704-phpapp01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">The Pathology of Graph Databases</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save The Pathology of Graph Databases for later" role="switch" aria-haspopup="dialog" aria-controls=":R2r9j69kf6:" popovertarget=":R2r9j69kf6:" style="anchor-name:--popover-R2r9j69kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2r9j69kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2r9j69kf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/slidarko">Marko Rodriguez</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">There is nothing more fascinating and utterly mind-bending than traversing a graph. Those who succumb to this data processing pattern euphorically suffer from graph pathology. This is a case study of the Graph Addict.</span></div></div><div class="" id=":R9j69kf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-R9j69kf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="moreFromUser-card-description-6" aria-haspopup="dialog" aria-controls=":R9r69kf6:" popovertarget=":R9r69kf6:" style="anchor-name:--popover-R9r69kf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/the-pathological-gremlin/7640601"><span class="sr-only">The Path-o-Logical Gremlin</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:6" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="The Path-o-Logical Gremlin" src="https://cdn.slidesharecdn.com/ss_thumbnails/gremlin-gdm2011-110415101933-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="The Path-o-Logical Gremlin" src="https://cdn.slidesharecdn.com/ss_thumbnails/gremlin-gdm2011-110415101933-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">The Path-o-Logical Gremlin</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save The Path-o-Logical Gremlin for later" role="switch" aria-haspopup="dialog" aria-controls=":R2r9r69kf6:" popovertarget=":R2r9r69kf6:" style="anchor-name:--popover-R2r9r69kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2r9r69kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2r9r69kf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/slidarko">Marko Rodriguez</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">Gremlin is a graph traversal language that connects to various graph databases/frameworks. * Neo4j [http://neo4j.org] * OrientDB [http://orientechnologies.com] * DEX [http://www.sparsity-technologies.com/dex] * OpenRDF Sail [http://openrdf.org] * JUNG [http://jung.sourceforge.net] This lecture addresses the state of Gremlin as of the 0.9 (April 16, 2011).</span></div></div><div class="" id=":R9r69kf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-R9r69kf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="moreFromUser-card-description-7" aria-haspopup="dialog" aria-controls=":Ra369kf6:" popovertarget=":Ra369kf6:" style="anchor-name:--popover-Ra369kf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/memoirs-of-a-graph-addict-despair-to-redemption/6490042"><span class="sr-only">Memoirs of a Graph Addict: Despair to Redemption</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:7" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Memoirs of a Graph Addict: Despair to Redemption" src="https://cdn.slidesharecdn.com/ss_thumbnails/whirlwind-tour-2011-110108171503-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Memoirs of a Graph Addict: Despair to Redemption" src="https://cdn.slidesharecdn.com/ss_thumbnails/whirlwind-tour-2011-110108171503-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Memoirs of a Graph Addict: Despair to Redemption</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Memoirs of a Graph Addict: Despair to Redemption for later" role="switch" aria-haspopup="dialog" aria-controls=":R2ra369kf6:" popovertarget=":R2ra369kf6:" style="anchor-name:--popover-R2ra369kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2ra369kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2ra369kf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/slidarko">Marko Rodriguez</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">This document summarizes a lecture about graph databases and graph structures. It discusses graph databases as an alternative to relational databases that allows for direct linking of objects without joins. It then describes the speaker's 10 years of experience working with graph structures and applications. Finally, it outlines the TinkerPop product suite for working with graph databases.</span></div></div><div class="" id=":Ra369kf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Ra369kf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="moreFromUser-card-description-8" aria-haspopup="dialog" aria-controls=":Rab69kf6:" popovertarget=":Rab69kf6:" style="anchor-name:--popover-Rab69kf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/graph-databases-trends-in-the-web-of-data/5228110"><span class="sr-only">Graph Databases: Trends in the Web of Data</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:8" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Graph Databases: Trends in the Web of Data" src="https://cdn.slidesharecdn.com/ss_thumbnails/krdb-graphdb-2010-100918034109-phpapp01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Graph Databases: Trends in the Web of Data" src="https://cdn.slidesharecdn.com/ss_thumbnails/krdb-graphdb-2010-100918034109-phpapp01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Graph Databases: Trends in the Web of Data</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Graph Databases: Trends in the Web of Data for later" role="switch" aria-haspopup="dialog" aria-controls=":R2rab69kf6:" popovertarget=":R2rab69kf6:" style="anchor-name:--popover-R2rab69kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2rab69kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2rab69kf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/slidarko">Marko Rodriguez</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only"> Aanswers · Aanswers ◦ n(I) π etc...15 15 I is the identity matrix. The Multi-Relational Path Algebra: - Allows single-relational algorithms to be applied to multi-relational graphs - Provides a universal framework for defining paths through a multi-relational graph - Enables the computation of multiple primary eigenvectors, each corresponding to a different path definition - In effect, provides multiple definitions of centrality for a multi-relational network - Is Turing complete—any computable path can be expressed - Is a general framework—applies to any multi-relational data model</span></div></div><div class="" id=":Rab69kf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rab69kf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="moreFromUser-card-description-9" aria-haspopup="dialog" aria-controls=":Raj69kf6:" popovertarget=":Raj69kf6:" style="anchor-name:--popover-Raj69kf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/problemsolving-using-graph-traversals-searching-scoring-ranking-and-recommendation/4833581"><span class="sr-only">Problem-Solving using Graph Traversals: Searching, Scoring, Ranking, and Reco...</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:9" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Problem-Solving using Graph Traversals: Searching, Scoring, Ranking, and Reco..." src="https://cdn.slidesharecdn.com/ss_thumbnails/atti-ps-graphs-100725105805-phpapp01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Problem-Solving using Graph Traversals: Searching, Scoring, Ranking, and Reco..." src="https://cdn.slidesharecdn.com/ss_thumbnails/atti-ps-graphs-100725105805-phpapp01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Problem-Solving using Graph Traversals: Searching, Scoring, Ranking, and Reco...</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Problem-Solving using Graph Traversals: Searching, Scoring, Ranking, and Reco... for later" role="switch" aria-haspopup="dialog" aria-controls=":R2raj69kf6:" popovertarget=":R2raj69kf6:" style="anchor-name:--popover-R2raj69kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2raj69kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2raj69kf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/slidarko">Marko Rodriguez</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">A graph is a data structure that links a set of vertices by a set of edges. Modern graph databases support multi-relational graph structures, where there exist different types of vertices (e.g. people, places, items) and different types of edges (e.g. friend, lives at, purchased). By means of index-free adjacency, graph databases are optimized for graph traversals and are interacted with through a graph traversal engine. A graph traversal is defined as an abstract path whose instance is realized on a graph dataset. Graph databases and traversals can be used for searching, scoring, ranking, and in concert, recommendation. This presentation will explore graph structures, algorithms, traversal algebras, graph-related software suites, and a host of examples demonstrating how to solve real-world problems, in real-time, with graphs. This is a whirlwind tour of the theory and application of graphs.</span></div></div><div class="" id=":Raj69kf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Raj69kf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="moreFromUser-card-description-10" aria-haspopup="dialog" aria-controls=":Rar69kf6:" popovertarget=":Rar69kf6:" style="anchor-name:--popover-Rar69kf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/a-perspective-on-graph-theory-and-network-science/4685485"><span class="sr-only">A Perspective on Graph Theory and Network Science</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:10" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="A Perspective on Graph Theory and Network Science" src="https://cdn.slidesharecdn.com/ss_thumbnails/network-graph-sf2010-100705130759-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="A Perspective on Graph Theory and Network Science" src="https://cdn.slidesharecdn.com/ss_thumbnails/network-graph-sf2010-100705130759-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">A Perspective on Graph Theory and Network Science</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save A Perspective on Graph Theory and Network Science for later" role="switch" aria-haspopup="dialog" aria-controls=":R2rar69kf6:" popovertarget=":R2rar69kf6:" style="anchor-name:--popover-R2rar69kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2rar69kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2rar69kf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/slidarko">Marko Rodriguez</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">The graph/network domain has been driven by the creativity of numerous individuals from disparate areas of the academic and the commercial sector. Examples of contributing academic disciplines include mathematics, physics, sociology, and computer science. Given the interdisciplinary nature of the domain, it is difficult for any single individual to objectively realize and speak about the space as a whole. Any presentation of the ideas is ultimately biased by the formal training and expertise of the individual. For this reason, I will simply present on the domain from my perspective---from my personal experiences. More specifically, from my perspective biased by cognitive and computer science. This is an autobiographical lecture on my life (so far) with graphs/networks.</span></div></div><div class="" id=":Rar69kf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rar69kf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="moreFromUser-card-description-11" aria-haspopup="dialog" aria-controls=":Rb369kf6:" popovertarget=":Rb369kf6:" style="anchor-name:--popover-Rb369kf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/graph-windycitydb2010/4618573"><span class="sr-only">The Graph Traversal Programming Pattern</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:11" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="The Graph Traversal Programming Pattern" src="https://cdn.slidesharecdn.com/ss_thumbnails/graph-windycitydb-2010-100625223624-phpapp01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="The Graph Traversal Programming Pattern" src="https://cdn.slidesharecdn.com/ss_thumbnails/graph-windycitydb-2010-100625223624-phpapp01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">The Graph Traversal Programming Pattern</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save The Graph Traversal Programming Pattern for later" role="switch" aria-haspopup="dialog" aria-controls=":R2rb369kf6:" popovertarget=":R2rb369kf6:" style="anchor-name:--popover-R2rb369kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2rb369kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2rb369kf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/slidarko">Marko Rodriguez</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">A graph is a structure composed of a set of vertices (i.e.~nodes, dots) connected to one another by a set of edges (i.e.~links, lines). The concept of a graph has been around since the late 19th century, however, only in recent decades has there been a strong resurgence in the development of both graph theories and applications. In applied computing, since the late 1960s, the interlinked table structure of the relational database has been the predominant information storage and retrieval paradigm. With the growth of graph/network-based data and the need to efficiently process such data, new data management systems have been developed. In contrast to the index-intensive, set-theoretic operations of relational databases, graph databases make use of index-free traversals. This presentation will discuss the graph traversal programming pattern and its application to problem-solving with graph databases.</span></div></div><div class="" id=":Rb369kf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rb369kf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="moreFromUser-card-description-12" aria-haspopup="dialog" aria-controls=":Rbb69kf6:" popovertarget=":Rbb69kf6:" style="anchor-name:--popover-Rbb69kf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/the-network-data-structure-in-computing/3884767"><span class="sr-only">The Network Data Structure in Computing</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:12" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="The Network Data Structure in Computing" src="https://cdn.slidesharecdn.com/ss_thumbnails/super-computer-100428102426-phpapp01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="The Network Data Structure in Computing" src="https://cdn.slidesharecdn.com/ss_thumbnails/super-computer-100428102426-phpapp01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">The Network Data Structure in Computing</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save The Network Data Structure in Computing for later" role="switch" aria-haspopup="dialog" aria-controls=":R2rbb69kf6:" popovertarget=":R2rbb69kf6:" style="anchor-name:--popover-R2rbb69kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2rbb69kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2rbb69kf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/slidarko">Marko Rodriguez</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">The document discusses network data structures and semantic networks. It provides examples of undirected, directed, and semantic networks. It describes how PageRank can be applied to semantic networks using grammar-based random walkers that follow the relationships between nodes defined in an ontology. It also lists related publications by the author on modeling systems and computations as semantic networks.</span></div></div><div class="" id=":Rbb69kf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rbb69kf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="moreFromUser-card-description-13" aria-haspopup="dialog" aria-controls=":Rbj69kf6:" popovertarget=":Rbj69kf6:" style="anchor-name:--popover-Rbj69kf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/a-model-of-the-scholarly-community/3884646"><span class="sr-only">A Model of the Scholarly Community</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:13" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="A Model of the Scholarly Community" src="https://cdn.slidesharecdn.com/ss_thumbnails/sfi-talk-100428101606-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="A Model of the Scholarly Community" src="https://cdn.slidesharecdn.com/ss_thumbnails/sfi-talk-100428101606-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">A Model of the Scholarly Community</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save A Model of the Scholarly Community for later" role="switch" aria-haspopup="dialog" aria-controls=":R2rbj69kf6:" popovertarget=":R2rbj69kf6:" style="anchor-name:--popover-R2rbj69kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2rbj69kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2rbj69kf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/slidarko">Marko Rodriguez</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">The document summarizes a two-year project to develop an ontology and data model to represent scholarly works and their usage. It will analyze bibliographic data and usage data from sources like journals, papers, and online usage logs to develop metrics to quantify the scholarly community. The first year will focus on developing the ontology and algorithms while the second year will analyze the results and report findings.</span></div></div><div class="" id=":Rbj69kf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rbj69kf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="moreFromUser-card-description-14" aria-haspopup="dialog" aria-controls=":Rbr69kf6:" popovertarget=":Rbr69kf6:" style="anchor-name:--popover-Rbr69kf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/generalpurpose-internetscale-distributed-computing-with-linked-process-3880087/3880087"><span class="sr-only">General-Purpose, Internet-Scale Distributed Computing with Linked Process</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:14" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="General-Purpose, Internet-Scale Distributed Computing with Linked Process" src="https://cdn.slidesharecdn.com/ss_thumbnails/cnls-linkedprocess2009-100428013149-phpapp01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="General-Purpose, Internet-Scale Distributed Computing with Linked Process" src="https://cdn.slidesharecdn.com/ss_thumbnails/cnls-linkedprocess2009-100428013149-phpapp01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">General-Purpose, Internet-Scale Distributed Computing with Linked Process</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save General-Purpose, Internet-Scale Distributed Computing with Linked Process for later" role="switch" aria-haspopup="dialog" aria-controls=":R2rbr69kf6:" popovertarget=":R2rbr69kf6:" style="anchor-name:--popover-R2rbr69kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2rbr69kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2rbr69kf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/slidarko">Marko Rodriguez</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">There are many distributed computing protocols in existence today. Some serve as a solution for scientific computing, some as a middleware solution to large- scale systems engineering, and others as an “easy-to-use” service solution on the Web. What most of these protocols have in common is that they require a strong “handshake” between the machines utilizing each other’s resources. This coupling has rendered many distributed protocols to only be useful for a collection of machines owned and operated by a single organization (e.g. MPI/PVM computing) or for use by foreign machines with a very specific use case (e.g. RPC/Web Services computing). The former allows for general-purpose distributed computing and the latter allows for Internet-scale distributed computing. What if both types of functionality were to be merged? What does a general-purpose, Internet-scale distributed computing protocol look like? Linked Process [ http://linkedprocess.org ]</span></div></div><div class="" id=":Rbr69kf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rbr69kf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="moreFromUser-card-description-15" aria-haspopup="dialog" aria-controls=":Rc369kf6:" popovertarget=":Rc369kf6:" style="anchor-name:--popover-Rc369kf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/collective-decision-making-systems-from-the-ideal-state-to-human-eudaimonia-3880075/3880075"><span class="sr-only">Collective Decision Making Systems: From the Ideal State to Human Eudaimonia</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:15" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Collective Decision Making Systems: From the Ideal State to Human Eudaimonia" src="https://cdn.slidesharecdn.com/ss_thumbnails/cnls-cdms-review-100428013055-phpapp01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Collective Decision Making Systems: From the Ideal State to Human Eudaimonia" src="https://cdn.slidesharecdn.com/ss_thumbnails/cnls-cdms-review-100428013055-phpapp01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Collective Decision Making Systems: From the Ideal State to Human Eudaimonia</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Collective Decision Making Systems: From the Ideal State to Human Eudaimonia for later" role="switch" aria-haspopup="dialog" aria-controls=":R2rc369kf6:" popovertarget=":R2rc369kf6:" style="anchor-name:--popover-R2rc369kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2rc369kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2rc369kf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/slidarko">Marko Rodriguez</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">Few scholastic disciplines have within them an explicit ideal beyond the production of knowledge. With computer science and engineering, the implicit ideal is to ensure better living through circuitry. Personally, my motivation is driven by the sense that social algorithms will lead to a greater human experience. </span></div></div><div class="" id=":Rc369kf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rc369kf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="moreFromUser-card-description-16" aria-haspopup="dialog" aria-controls=":Rcb69kf6:" popovertarget=":Rcb69kf6:" style="anchor-name:--popover-Rcb69kf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/distributed-graph-databases-and-the-emerging-web-of-data/3880066"><span class="sr-only">Distributed Graph Databases and the Emerging Web of Data</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:16" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Distributed Graph Databases and the Emerging Web of Data" src="https://cdn.slidesharecdn.com/ss_thumbnails/unm-colloquium2009-100428011205-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Distributed Graph Databases and the Emerging Web of Data" src="https://cdn.slidesharecdn.com/ss_thumbnails/unm-colloquium2009-100428011205-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Distributed Graph Databases and the Emerging Web of Data</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Distributed Graph Databases and the Emerging Web of Data for later" role="switch" aria-haspopup="dialog" aria-controls=":R2rcb69kf6:" popovertarget=":R2rcb69kf6:" style="anchor-name:--popover-R2rcb69kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2rcb69kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2rcb69kf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/slidarko">Marko Rodriguez</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">The World Wide Web is the defacto medium for publicly exposing a corpus of interrelated documents. In its current form, the World Wide Web is the Web of Documents. The next generation of the World Wide Web will support the Web of Data. The Web of Data utilizes the same Uniform Resource Identifier (URI) address space as the Web of Documents, but instead of a exposing a graph of documents, the Web of Data exposes a graph of data. Given that the URI address space of the Web is distributed and infinite, the Web of Data provides a single unified space by which the worlds data can be publicly exposed and interrelated. The Web of Data is supported by both graph databases (which structure the data) and distributed computing mechanism (which process the data). This presentation will discuss the Web of Data, graph databases, and models of computing in this emerging space.</span></div></div><div class="" id=":Rcb69kf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rcb69kf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="moreFromUser-card-description-17" aria-haspopup="dialog" aria-controls=":Rcj69kf6:" popovertarget=":Rcj69kf6:" style="anchor-name:--popover-Rcj69kf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slidarko/an-overview-of-data-management-paradigms-relational-document-and-graph-3880059"><span class="sr-only">An Overview of Data Management Paradigms: Relational, Document, and Graph</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:17" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="An Overview of Data Management Paradigms: Relational, Document, and Graph" src="https://cdn.slidesharecdn.com/ss_thumbnails/datamanagement-2010-100428010914-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="An Overview of Data Management Paradigms: Relational, Document, and Graph" src="https://cdn.slidesharecdn.com/ss_thumbnails/datamanagement-2010-100428010914-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">An Overview of Data Management Paradigms: Relational, Document, and Graph</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save An Overview of Data Management Paradigms: Relational, Document, and Graph for later" role="switch" aria-haspopup="dialog" aria-controls=":R2rcj69kf6:" popovertarget=":R2rcj69kf6:" style="anchor-name:--popover-R2rcj69kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2rcj69kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2rcj69kf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/slidarko">Marko Rodriguez</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only"> Here are the key steps: 1. Create vertex for each band member with properties like name, etc 2. Create vertex for each song with properties like title 3. Create edge between band member and song to indicate they performed it 4. Add properties to edges like number of performances This models the relationships between band members and songs they played in a graph structure optimized for traversal.</span></div></div><div class="" id=":Rcj69kf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rcj69kf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="moreFromUser-card-description-18" aria-haspopup="dialog" aria-controls=":Rcr69kf6:" popovertarget=":Rcr69kf6:" style="anchor-name:--popover-Rcr69kf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slidarko/graph-databases-and-the-future-of-largescale-knowledge-management"><span class="sr-only">Graph Databases and the Future of Large-Scale Knowledge Management</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:18" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Graph Databases and the Future of Large-Scale Knowledge Management" src="https://cdn.slidesharecdn.com/ss_thumbnails/risk-symposium2009-100428010546-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Graph Databases and the Future of Large-Scale Knowledge Management" src="https://cdn.slidesharecdn.com/ss_thumbnails/risk-symposium2009-100428010546-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Graph Databases and the Future of Large-Scale Knowledge Management</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Graph Databases and the Future of Large-Scale Knowledge Management for later" role="switch" aria-haspopup="dialog" aria-controls=":R2rcr69kf6:" popovertarget=":R2rcr69kf6:" style="anchor-name:--popover-R2rcr69kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2rcr69kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2rcr69kf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/slidarko">Marko Rodriguez</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">The document discusses how modern graph databases can store billions of relationships and are practical for large-scale knowledge management. It also describes how graph databases can be interlinked using Linked Data standards to create a giant global knowledge structure on the web. The talk will cover graph databases, their data model, querying mechanisms, and benefits for modeling and analysis compared to relational databases.</span></div></div><div class="" id=":Rcr69kf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rcr69kf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="moreFromUser-card-description-19" aria-haspopup="dialog" aria-controls=":Rd369kf6:" popovertarget=":Rd369kf6:" style="anchor-name:--popover-Rd369kf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/automatic-metadata-generation-using-associative-networks/3880025"><span class="sr-only">Automatic Metadata Generation using Associative Networks</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:19" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Automatic Metadata Generation using Associative Networks" src="https://cdn.slidesharecdn.com/ss_thumbnails/metadata-generation-100428010008-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Automatic Metadata Generation using Associative Networks" src="https://cdn.slidesharecdn.com/ss_thumbnails/metadata-generation-100428010008-phpapp02-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Automatic Metadata Generation using Associative Networks</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Automatic Metadata Generation using Associative Networks for later" role="switch" aria-haspopup="dialog" aria-controls=":R2rd369kf6:" popovertarget=":R2rd369kf6:" style="anchor-name:--popover-R2rd369kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2rd369kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2rd369kf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/slidarko">Marko Rodriguez</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">In spite of its tremendous value, metadata is generally sparse and incomplete, thereby hampering the effectiveness of digital information services. Many of the existing mechanisms for the automated creation of metadata rely primarily on content analysis which can be costly and inefficient. The automatic metadata generation system proposed in this article leverages resource relationships generated from existing metadata as a medium for propagation from metadata-rich to metadata-poor resources. Because of its independence from content analysis, it can be applied to a wide variety of resource media types and is shown to be computationally inexpensive. The proposed method operates through two distinct phases. Occurrence and co-occurrence algorithms first generate an associative network of repository resources leveraging existing repository metadata. Second, using the associative network as a substrate, metadata associated with metadata-rich resources is propagated to metadata-poor resources by means of a discrete-form spreading activation algorithm. This article discusses the general framework for building associative networks, an algorithm for disseminating metadata through such networks, and the results of an experiment and validation of the proposed method using a standard bibliographic dataset. </span></div></div><div class="" id=":Rd369kf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rd369kf6"></div></div><div class="desktop-recs"><div class="Slider_root__c0Jo8"><div class="Slider_scroller__KHjw4"><div class="BottomRecommendationCard_root__gffTk SlideshowCard_root__pD8t4 slideshow-card"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/mmadt-a-virtual-machinean-economic-machine/224411576"><span class="sr-only">mm-ADT: A Virtual Machine/An Economic Machine</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:16 / 9;--index:0" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="mm-ADT: A Virtual Machine/An Economic Machine" src="https://cdn.slidesharecdn.com/ss_thumbnails/datadays-2020-200125222428-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="mm-ADT: A Virtual Machine/An Economic Machine" src="https://cdn.slidesharecdn.com/ss_thumbnails/datadays-2020-200125222428-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">mm-ADT: A Virtual Machine/An Economic Machine</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save mm-ADT: A Virtual Machine/An Economic Machine for later" role="switch" aria-haspopup="dialog" aria-controls=":Rb1d69kf6:" popovertarget=":Rb1d69kf6:" style="anchor-name:--popover-Rb1d69kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":Rb1d69kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-Rb1d69kf6"></div><a class="SlideshowAuthor_root__IkT1_ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/slidarko">Marko Rodriguez</a><div class="slideshow-stats SlideshowStats_root__EQOR1"> </div></div></div><div class="BottomRecommendationCard_root__gffTk SlideshowCard_root__pD8t4 slideshow-card"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/mmadt-a-multimodel-abstract-data-type/170928548"><span class="sr-only">mm-ADT: A Multi-Model Abstract Data Type</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:16 / 9;--index:1" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="mm-ADT: A Multi-Model Abstract Data Type" src="https://cdn.slidesharecdn.com/ss_thumbnails/apachecon-2019-190911190011-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="mm-ADT: A Multi-Model Abstract Data Type" src="https://cdn.slidesharecdn.com/ss_thumbnails/apachecon-2019-190911190011-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">mm-ADT: A Multi-Model Abstract Data Type</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save mm-ADT: A Multi-Model Abstract Data Type for later" role="switch" aria-haspopup="dialog" aria-controls=":Rb2d69kf6:" popovertarget=":Rb2d69kf6:" style="anchor-name:--popover-Rb2d69kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":Rb2d69kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-Rb2d69kf6"></div><a class="SlideshowAuthor_root__IkT1_ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/slidarko">Marko Rodriguez</a><div class="slideshow-stats SlideshowStats_root__EQOR1"> </div></div></div><div class="BottomRecommendationCard_root__gffTk SlideshowCard_root__pD8t4 slideshow-card"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/open-problems-in-the-universal-graph-theory/77013277"><span class="sr-only">Open Problems in the Universal Graph Theory</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:16 / 9;--index:2" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Open Problems in the Universal Graph Theory" src="https://cdn.slidesharecdn.com/ss_thumbnails/the-universal-graph-170616182527-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Open Problems in the Universal Graph Theory" src="https://cdn.slidesharecdn.com/ss_thumbnails/the-universal-graph-170616182527-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Open Problems in the Universal Graph Theory</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Open Problems in the Universal Graph Theory for later" role="switch" aria-haspopup="dialog" aria-controls=":Rb3d69kf6:" popovertarget=":Rb3d69kf6:" style="anchor-name:--popover-Rb3d69kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":Rb3d69kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-Rb3d69kf6"></div><a class="SlideshowAuthor_root__IkT1_ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/slidarko">Marko Rodriguez</a><div class="slideshow-stats SlideshowStats_root__EQOR1"> </div></div></div><div class="BottomRecommendationCard_root__gffTk SlideshowCard_root__pD8t4 slideshow-card"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slidarko/gremlin-1013-on-your-fm-dial"><span class="sr-only">Gremlin 101.3 On Your FM Dial</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:16 / 9;--index:3" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Gremlin 101.3 On Your FM Dial" src="https://cdn.slidesharecdn.com/ss_thumbnails/gremlin-workshop-2017-170427195932-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Gremlin 101.3 On Your FM Dial" src="https://cdn.slidesharecdn.com/ss_thumbnails/gremlin-workshop-2017-170427195932-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Gremlin 101.3 On Your FM Dial</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Gremlin 101.3 On Your FM Dial for later" role="switch" aria-haspopup="dialog" aria-controls=":Rb4d69kf6:" popovertarget=":Rb4d69kf6:" style="anchor-name:--popover-Rb4d69kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":Rb4d69kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-Rb4d69kf6"></div><a class="SlideshowAuthor_root__IkT1_ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/slidarko">Marko Rodriguez</a><div class="slideshow-stats SlideshowStats_root__EQOR1"> </div></div></div><div class="BottomRecommendationCard_root__gffTk SlideshowCard_root__pD8t4 slideshow-card"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/faunus-graph-analytics-engine/21219108"><span class="sr-only">Faunus: Graph Analytics Engine</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:16 / 9;--index:4" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Faunus: Graph Analytics Engine" src="https://cdn.slidesharecdn.com/ss_thumbnails/faunus-graph-analytics-engine-130515151807-phpapp01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Faunus: Graph Analytics Engine" src="https://cdn.slidesharecdn.com/ss_thumbnails/faunus-graph-analytics-engine-130515151807-phpapp01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Faunus: Graph Analytics Engine</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Faunus: Graph Analytics Engine for later" role="switch" aria-haspopup="dialog" aria-controls=":Rb5d69kf6:" popovertarget=":Rb5d69kf6:" style="anchor-name:--popover-Rb5d69kf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":Rb5d69kf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-Rb5d69kf6"></div><a class="SlideshowAuthor_root__IkT1_ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/slidarko">Marko Rodriguez</a><div class="slideshow-stats SlideshowStats_root__EQOR1"> </div></div></div><div class="BottomRecommendationCard_root__gffTk SlideshowCard_root__pD8t4 slideshow-card"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/the-pathology-of-graph-databases/8422170"><span class="sr-only">The Pathology of Graph Databases</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:16 / 9;--index:5" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="The Pathology of Graph Databases" src="https://cdn.slidesharecdn.com/ss_thumbnails/windycitydb-2011-110625100704-phpapp01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="The Pathology of Graph Databases" src="https://cdn.slidesharecdn.com/ss_thumbnails/windycitydb-2011-110625100704-phpapp01-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">The Pathology of Graph Databases</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button 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like TDD (instead of hating it) - TED talk for later" role="switch" aria-haspopup="dialog" aria-controls=":R2r8b6pkf6:" popovertarget=":R2r8b6pkf6:" style="anchor-name:--popover-R2r8b6pkf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2r8b6pkf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2r8b6pkf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/icougil">Nacho Cougil</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">John, a typical developer, used to dread writing tests, finding them 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Test Driven Development (TDD)? Even worse—he couldn’t see how it worked outside of basic exercises. But something clicked. Through his journey, John discovered the magic of writing tests before the production code: fewer bugs, quicker feedback, and cleaner code. Now, he’s hooked and won’t code any other way. This is the story of how TDD turned a skeptic into a believer. 😅 PS: Think of John as a random person, as if he was even the speaker of this talk 😉! --- Presentation shared at Talent Arena '25 Feedback form: http://tiny.cc/how-john-tdd-feedback</span></div></div><div class="" id=":R8b6pkf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-R8b6pkf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="latest-card-description-1" aria-haspopup="dialog" aria-controls=":R8j6pkf6:" popovertarget=":R8j6pkf6:" style="anchor-name:--popover-R8j6pkf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/advance-website-helpdesk-customer-support-ticket-management-odoo/276219588"><span class="sr-only">Advance Website Helpdesk Customer Support Ticket Management Odoo</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:1" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Advance Website Helpdesk Customer Support Ticket Management Odoo" src="https://cdn.slidesharecdn.com/ss_thumbnails/adv-250303110550-98dad014-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Advance Website Helpdesk Customer Support Ticket Management Odoo" src="https://cdn.slidesharecdn.com/ss_thumbnails/adv-250303110550-98dad014-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Advance Website Helpdesk Customer Support Ticket Management Odoo</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Advance Website Helpdesk Customer Support Ticket Management Odoo for later" role="switch" aria-haspopup="dialog" aria-controls=":R2r8j6pkf6:" popovertarget=":R2r8j6pkf6:" style="anchor-name:--popover-R2r8j6pkf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2r8j6pkf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2r8j6pkf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/aagaminfotech">Aagam infotech </a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">Effortlessly manage tickets via email, admin, or website forms, and take advantage of features like merging, reopening, and assigning by type. 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He'll show its key features and learn how to leverage AI capabilities to drive automation and enhance decision-making.</span></div></div><div class="" id=":Rar6pkf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rar6pkf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="latest-card-description-11" aria-haspopup="dialog" aria-controls=":Rb36pkf6:" popovertarget=":Rb36pkf6:" style="anchor-name:--popover-Rb36pkf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/projects-panama-valhalla-and-babylon-java-is-the-new-python-v0-9/276363029"><span class="sr-only">Projects Panama, Valhalla, and Babylon: Java is the New Python v0.9</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:11" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Projects Panama, Valhalla, and Babylon: Java is the New Python v0.9" src="https://cdn.slidesharecdn.com/ss_thumbnails/javaisthenewpythonv0-250306233126-21776970-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Projects Panama, Valhalla, and Babylon: Java is the New Python v0.9" src="https://cdn.slidesharecdn.com/ss_thumbnails/javaisthenewpythonv0-250306233126-21776970-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Projects Panama, Valhalla, and Babylon: Java is the New Python v0.9</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Projects Panama, Valhalla, and Babylon: Java is the New Python v0.9 for later" role="switch" aria-haspopup="dialog" aria-controls=":R2rb36pkf6:" popovertarget=":R2rb36pkf6:" style="anchor-name:--popover-R2rb36pkf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2rb36pkf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2rb36pkf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/yanngaelgueheneuc">Yann-Gaël Guéhéneuc</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">Java has had a tremendous success and, in the last few years, has evolved quite significantly. However, it was still difficult to interface with libraries written in other programming language because of some complexity with JNI and some syntactic and semantic barriers. New projects to improve Java could help alleviate, even nullify, these barriers. Projects Panama, Valhalla, and Babylon exist to make it easier to use different programming and memory models in Java and to interface with foreign programming languages. This presentation describes the problem with the Java “isthmus” and the three projects in details, with real code examples. It shows how, combined, these three projects could make of Java the new Python.</span></div></div><div class="" id=":Rb36pkf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rb36pkf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="latest-card-description-12" aria-haspopup="dialog" aria-controls=":Rbb6pkf6:" popovertarget=":Rbb6pkf6:" style="anchor-name:--popover-Rbb6pkf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/computer-architecture-patterson-chapter-1-ppt/276216430"><span class="sr-only">Computer Architecture Patterson chapter 1 .ppt</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:12" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Computer Architecture Patterson chapter 1 .ppt" src="https://cdn.slidesharecdn.com/ss_thumbnails/codch1slides-250303091423-43c4887a-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Computer Architecture Patterson chapter 1 .ppt" src="https://cdn.slidesharecdn.com/ss_thumbnails/codch1slides-250303091423-43c4887a-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Computer Architecture Patterson chapter 1 .ppt</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Computer Architecture Patterson chapter 1 .ppt for later" role="switch" aria-haspopup="dialog" aria-controls=":R2rbb6pkf6:" popovertarget=":R2rbb6pkf6:" style="anchor-name:--popover-R2rbb6pkf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2rbb6pkf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2rbb6pkf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/jaysen110">jaysen110</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">Chapter 1 of Computer Organization and Architecture by Patterson and Hennessy, often referred to as the "Computer Organization and Design" (COD) book, serves as an introduction to the fundamental concepts of computer systems. It lays the groundwork for understanding how computers are designed and how they operate at both the hardware and software levels. The chapter begins by explaining the importance of abstraction in computer design, highlighting how layers of abstraction simplify the complexity of modern computing systems. Abstraction allows designers and programmers to focus on specific levels of a system without needing to understand every detail of the underlying layers, making it easier to build, optimize, and maintain complex systems. The authors introduce the concept of the stored-program computer, a revolutionary idea where instructions and data are stored in memory, and the CPU fetches, decodes, and executes these instructions. This forms the basis of the von Neumann architecture, a cornerstone of modern computing. The von Neumann model is characterized by its sequential execution of instructions and its unified memory space for both data and programs. The chapter explains how this architecture enables the flexibility and programmability that define modern computers. The chapter also discusses the roles of key components in a computer system, such as the CPU (Central Processing Unit), memory, and I/O (Input/Output) devices, and how they interact to execute programs. The CPU is described as the brain of the computer, responsible for performing arithmetic and logical operations, while memory stores data and instructions temporarily or permanently. I/O devices facilitate communication between the computer and the external world, enabling input from users and output to displays or other peripherals. A significant portion of the chapter is dedicated to the concept of performance in computer systems. The authors introduce metrics like response time (the time it takes to complete a task) and throughput (the number of tasks completed per unit of time). They explain how these metrics are influenced by hardware and software optimizations, such as faster processors, larger memory, and efficient algorithms. The chapter also touches on the trade-offs involved in improving performance, such as the cost, power consumption, and complexity of hardware components. The chapter emphasizes the importance of instruction set architecture (ISA), which serves as the interface between hardware and software. The ISA defines the set of instructions that a CPU can execute, as well as the registers, memory addressing modes, and data types it supports. Understanding the ISA is crucial for both hardware designers, who implement it, and software developers, who write programs that run on it. To illustrate these concepts, the chapter often uses real-world examples and analogies, making the material accessible to readers with varying levels of prior knowledge.</span></div></div><div class="" id=":Rbb6pkf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rbb6pkf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="latest-card-description-13" aria-haspopup="dialog" aria-controls=":Rbj6pkf6:" popovertarget=":Rbj6pkf6:" style="anchor-name:--popover-Rbj6pkf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/ai-ml-infra-meetup-building-production-platform-for-large-scale-recommendation-applications/276526938"><span class="sr-only">AI/ML Infra Meetup | Building Production Platform for Large-Scale Recommendat...</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:13" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="AI/ML Infra Meetup | Building Production Platform for Large-Scale Recommendat..." src="https://cdn.slidesharecdn.com/ss_thumbnails/4buildingproductionplatformforlarge-scalerecommendationapplications-250311004025-bf304596-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="AI/ML Infra Meetup | Building Production Platform for Large-Scale Recommendat..." src="https://cdn.slidesharecdn.com/ss_thumbnails/4buildingproductionplatformforlarge-scalerecommendationapplications-250311004025-bf304596-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">AI/ML Infra Meetup | Building Production Platform for Large-Scale Recommendat...</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save AI/ML Infra Meetup | Building Production Platform for Large-Scale Recommendat... for later" role="switch" aria-haspopup="dialog" aria-controls=":R2rbj6pkf6:" popovertarget=":R2rbj6pkf6:" style="anchor-name:--popover-R2rbj6pkf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2rbj6pkf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2rbj6pkf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/Alluxio">Alluxio, Inc.</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">AI/ML Infra Meetup Mar. 06, 2025 Organized by Alluxio For more Alluxio Events: https://www.alluxio.io/events/ Speaker: - Xu Ning (Director of Engineering, AI Platform @ Snap) In this talk, Xu Ning from Snap provides a comprehensive overview of the unique challenges in building and scaling recommendation systems compared to LLM applications.</span></div></div><div class="" id=":Rbj6pkf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rbj6pkf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="latest-card-description-14" aria-haspopup="dialog" aria-controls=":Rbr6pkf6:" popovertarget=":Rbr6pkf6:" style="anchor-name:--popover-Rbr6pkf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/devopsdays-la-platform-engineers-are-product-managers-pdf/276367378"><span class="sr-only">DevOpsDays LA - Platform Engineers are Product Managers.pdf</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:14" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="DevOpsDays LA - Platform Engineers are Product Managers.pdf" src="https://cdn.slidesharecdn.com/ss_thumbnails/devopsdaysla-platformengineersareproductmanagers-250307020522-4974428c-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="DevOpsDays LA - Platform Engineers are Product Managers.pdf" src="https://cdn.slidesharecdn.com/ss_thumbnails/devopsdaysla-platformengineersareproductmanagers-250307020522-4974428c-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">DevOpsDays LA - Platform Engineers are Product Managers.pdf</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save DevOpsDays LA - Platform Engineers are Product Managers.pdf for later" role="switch" aria-haspopup="dialog" aria-controls=":R2rbr6pkf6:" popovertarget=":R2rbr6pkf6:" style="anchor-name:--popover-R2rbr6pkf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2rbr6pkf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2rbr6pkf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/JustinReock">Justin Reock</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">Platform engineering is the foundation of modern software development, equipping teams with the tools and workflows they need to move faster. However, to truly drive impact, platform engineers must think like product managers—leveraging productivity metrics to guide decisions, prioritize investments, and measure success. By applying a data-driven approach, platform teams can optimize developer experience, streamline workflows, and demonstrate tangible ROI on platform initiatives. In this 15-minute session, Justin Reock, Deputy CTO at DX (getdx.com), will explore how platform engineers can use key developer productivity metrics—such as cycle time, deployment frequency, and developer satisfaction—to manage their platform as an internal product. By treating the platform with the same rigor as an external product launch, teams can accelerate adoption, improve efficiency, and create a frictionless developer experience. Join us to learn how adopting a metrics-driven, product management mindset can transform your platform engineering efforts into a strategic, high-impact function that unlocks engineering velocity and business success.</span></div></div><div class="" id=":Rbr6pkf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rbr6pkf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="latest-card-description-15" aria-haspopup="dialog" aria-controls=":Rc36pkf6:" popovertarget=":Rc36pkf6:" style="anchor-name:--popover-Rc36pkf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/ai-powered-chatbots-for-employee-support/276257255"><span class="sr-only">AI-Powered Chatbots for Employee Support</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:15" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="AI-Powered Chatbots for Employee Support" src="https://cdn.slidesharecdn.com/ss_thumbnails/ai-poweredchatbotsforemployeesupportslideshare-250304091347-cc7d4e52-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="AI-Powered Chatbots for Employee Support" src="https://cdn.slidesharecdn.com/ss_thumbnails/ai-poweredchatbotsforemployeesupportslideshare-250304091347-cc7d4e52-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">AI-Powered Chatbots for Employee Support</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save AI-Powered Chatbots for Employee Support for later" role="switch" aria-haspopup="dialog" aria-controls=":R2rc36pkf6:" popovertarget=":R2rc36pkf6:" style="anchor-name:--popover-R2rc36pkf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2rc36pkf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2rc36pkf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/automationedgetv">AutomationEdge Technologies</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">Discover how AI-powered chatbots enhance employee support by streamlining HR tasks, reducing administrative burdens, and providing real-time assistance. Learn about their integration with platforms like WhatsApp and MS Teams for a seamless experience.</span></div></div><div class="" id=":Rc36pkf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rc36pkf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 slideshow-card" aria-describedby="latest-card-description-16" aria-haspopup="dialog" aria-controls=":Rcb6pkf6:" popovertarget=":Rcb6pkf6:" style="anchor-name:--popover-Rcb6pkf6"><a class="SlideshowCardLink_root__p8KI7" data-cy="slideshow-card-link" data-testid="slideshow-card-link" href="https://www.slideshare.net/slideshow/consequences-and-principles-of-software-quality-v1-0/276362478"><span class="sr-only">Consequences and Principles of Software Quality v1.0</span></a><div class="slideshow-thumbnail Thumbnail_root__qLW0K SlideshowCard_thumb__86aJk" style="aspect-ratio:1.5;--index:16" data-testid="card-thumbnail"><img class="Thumbnail_thumb__UXO3a Thumbnail_blur__opK6A Thumbnail_cover__1zsIi" alt="Consequences and Principles of Software Quality v1.0" src="https://cdn.slidesharecdn.com/ss_thumbnails/softwarequalityv1-250306230526-90ad3014-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/><img class="Thumbnail_thumb__UXO3a Thumbnail_contain__K6M0d" alt="Consequences and Principles of Software Quality v1.0" src="https://cdn.slidesharecdn.com/ss_thumbnails/softwarequalityv1-250306230526-90ad3014-thumbnail.jpg?width=560&fit=bounds" loading="lazy"/></div><div class="SlideshowCard_content__xh7kV slideshow-card-content"><span class="slideshow-title SlideshowTitle_root__2VccW RailCard_title__Tvfiv ellipsis" style="-webkit-line-clamp:2" data-cy="slideshow-title">Consequences and Principles of Software Quality v1.0</span><button type="button" class="Button_root__i1yp0 Button_secondary__hHiHI Button_text__ZT_3O Button_small__sqsEx Button_icon__1C4qi save-slideshow-button SaveButton_root__b6zuu" data-testid="button" aria-checked="false" aria-label="Save Consequences and Principles of Software Quality v1.0 for later" role="switch" aria-haspopup="dialog" aria-controls=":R2rcb6pkf6:" popovertarget=":R2rcb6pkf6:" style="anchor-name:--popover-R2rcb6pkf6"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/save.ef1812e2.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><div class="Tooltip_root__7FS0Y" id=":R2rcb6pkf6:" popover="manual" data-popover-position="top" style="position-anchor:--popover-R2rcb6pkf6"></div><a class="SlideshowAuthor_root__IkT1_ RailCard_author__JYeYZ slideshow-author ellipsis" data-testid="slideshow-author" data-cy="slideshow-author" href="https://www.slideshare.net/yanngaelgueheneuc">Yann-Gaël Guéhéneuc</a><div class="slideshow-stats SlideshowStats_root__EQOR1 RailCard_stats__ZvZms"> </div><span aria-hidden="true" class="seo-only">Examples of (bad) consequences of a lack of software quality and some solutions. This presentation presents some examples of (bad) consequences of a lack of software quality, in particular how poor software quality led to the direct deaths of 89 people. It then provides some background on software quality, especially the concept of Quality Without a Name. It then discusses many principles, their usefulness, and their positive consequences on software quality. Some of these principles are well-known in object-oriented programming while many others are taken from the book 97 Programmers. They include: abstraction, encapsulation, inheritance, types, polymorphism, SOLID, GRASP, YAGNI, KISS, DRY, Do Not Reinvent the Wheel, Law of Demeter, Beware of Assumptions, Deletable Code, coding with reason, and functional programming. They pertain to dependencies, domains, and tools. Concrete application on a real-world software systems, with examples and discussions. (In details: Beautify is Simplicity, The Boy Scout Rule, You Gotta Care About the Code, The Longevity of Interim Solutions, Beware the Share, Encapsulate Behaviour not Just State, Single Responsibility Principle, WET Dilutes Performance Bottlenecks, Convenience Is Not an -ility, Code in the Language of the Domain, Comment Only What the Code Cannot Say, Distinguish Business Exception from Technical, Prefer Domain-specific Types to Primitive Types, Automate Your Coding Standards, Code Layout Matters, Before You Refactor, Improve Code by Removing It, Put the Mouse Down and Step Away from the Keyboard)</span></div></div><div class="" id=":Rcb6pkf6:" popover="manual" data-popover-position="bottom-start" style="position-anchor:--popover-Rcb6pkf6"></div><div class="separator Separator_root__70Ime Separator_horizontal__czVEa" style="--color:var(--blue-gray-200);--size:1px" role="separator"></div><div class="RailCard_root__rZUGY RailCard_hasDescription__MjSgf SlideshowCard_root__pD8t4 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Pereira</a><div class="slideshow-stats SlideshowStats_root__EQOR1"> </div></div></div></div><button aria-label="Previous" type="button" class="Slider_arrow__8LCca Slider_prev__YMssa Slider_hidden__rs7nK"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/chevron-left.50b146c0.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button><button aria-label="Next" type="button" class="Slider_arrow__8LCca Slider_next__fa9IO"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/chevron-right.9b30ad08.svg);background-color:currentColor"></span><span class="sr-only"></span></span></button></div></div></div></div></div></div><div class="Transcript_root__Vrf6Q"><h2 class="Transcript_title__YgAka"><span class="icon Icon_root__AjZyv" style="--size:24px"><span class="Icon_icon__4zzsG" style="mask-image:url(https://public.slidesharecdn.com/_next/static/media/file.5db1ba24.svg);background-color:currentColor"></span><span class="sr-only"></span></span>The Gremlin Graph Traversal Language</h2><div><ul class="Transcript_list__faItj"><div><li>1. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#1">The Gremlin Graph </a> Traversal Language Marko A. Rodriguez and Daniel Kuppitz http://tinkerpop.incubator.apache.org </li></div><div><li>2. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#2">user movie categoryoccupation occupation </a> rated category name:String gender:[M,F] age:integer name:String year:integer name:String stars:[1,2,3,4,5] http://grouplens.org/datasets/movielens/ MovieLens Dataset </li></div><div><li>3. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#3">user |Vuser| = 6040 |Vmovie| </a> = 3883 movie |Vcategory| = 18 category |Voccupation| = 21 occupation occupation |Eoccupation| = 6040 rated |Erated| = 1000209 category |Ecategory| = 6408 name:String gender:[M,F] age:integer name:String year:integer name:String stars:[1,2,3,4,5] http://grouplens.org/datasets/movielens/ G = (V, E) MovieLens Dataset </li></div><div><li>4. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#4">~/tinkerpop3$ bin/gremlin.sh gremlin> </a></li></div><div><li>5. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#5">~/tinkerpop3$ bin/gremlin.sh ,,,/ (o o) -----oOOo-(3)-oOOo----- plugin </a> activated: tinkerpop.server plugin activated: tinkerpop.utilities plugin activated: tinkerpop.tinkergraph gremlin> </li></div><div><li>6. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#6">~/tinkerpop3$ bin/gremlin.sh ,,,/ (o o) -----oOOo-(3)-oOOo----- plugin </a> activated: tinkerpop.server plugin activated: tinkerpop.utilities plugin activated: tinkerpop.tinkergraph gremlin> Gremlin-Java8 Gremlin-Groovy* Gremlin-Scala Gremlin-Clojure Gremlin-JavaScript Gremlin-Python Gremlin-PHP ... </li></div><div><li>7. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#7">~/tinkerpop3$ bin/gremlin.sh ,,,/ (o o) -----oOOo-(3)-oOOo----- plugin </a> activated: tinkerpop.server plugin activated: tinkerpop.utilities plugin activated: tinkerpop.tinkergraph gremlin> graph = TinkerGraph.open() ==>tinkergraph[vertices:0 edges:0] gremlin> "Create a new TinkerGraph." </li></div><div><li>8. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#8">~/tinkerpop3$ bin/gremlin.sh ,,,/ (o o) -----oOOo-(3)-oOOo----- plugin </a> activated: tinkerpop.server plugin activated: tinkerpop.utilities plugin activated: tinkerpop.tinkergraph gremlin> graph = TinkerGraph.open() ==>tinkergraph[vertices:0 edges:0] gremlin> "Create a new TinkerGraph." G = (V = ∅, E = ∅) G The graph is a set of vertices and edges V The set of vertices in the graph E The set of edges in the graph ∅ The empty set -- no elements </li></div><div><li>9. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#9">~/tinkerpop3$ bin/gremlin.sh ,,,/ (o o) -----oOOo-(3)-oOOo----- plugin </a> activated: tinkerpop.server plugin activated: tinkerpop.utilities plugin activated: tinkerpop.tinkergraph gremlin> graph = TinkerGraph.open() ==>tinkergraph[vertices:0 edges:0] gremlin> "Create a new TinkerGraph." G = (V = ∅, E = ∅) TitanGraph.open(…) Neo4jGraph.open(…) OrientGraph.open(…) SqlgGraph.open(…) HadoopGraph.open(…) GiraphGraphComputer SparkGraphComputer ElasticGraph.open(…) ... </li></div><div><li>10. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#10">G = (V </a> = ∅, E ⊆ (V × V )) ~/tinkerpop3$ bin/gremlin.sh ,,,/ (o o) -----oOOo-(3)-oOOo----- plugin activated: tinkerpop.server plugin activated: tinkerpop.utilities plugin activated: tinkerpop.tinkergraph gremlin> graph = TinkerGraph.open() ==>tinkergraph[vertices:0 edges:0] gremlin> graph.io(gryo()).readGraph('/tmp/movie-lens.kryo') ==>null gremlin> "Load the MovieLens dataset into the newly created TinkerGraph." Set A is a subset of (or equal to) set B The set of all ordered pairs of vertices (directed binary edges) A ⊆ B (V × V ) </li></div><div><li>11. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#11">~/tinkerpop3$ bin/gremlin.sh ,,,/ (o o) -----oOOo-(3)-oOOo----- plugin </a> activated: tinkerpop.server plugin activated: tinkerpop.utilities plugin activated: tinkerpop.tinkergraph gremlin> graph = TinkerGraph.open() ==>tinkergraph[vertices:0 edges:0] gremlin> graph.io(gryo()).readGraph('/tmp/movie-lens.kryo') ==>null gremlin> g = graph.traversal() ==>graphtraversalsource[tinkergraph[vertices:9962 edges:1012657], standard] gremlin> "Create a graph traversal source for spawning graph traversals over the MovieLens graph." </li></div><div><li>12. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#12">~/tinkerpop3$ bin/gremlin.sh ,,,/ (o o) -----oOOo-(3)-oOOo----- plugin </a> activated: tinkerpop.server plugin activated: tinkerpop.utilities plugin activated: tinkerpop.tinkergraph gremlin> graph = TinkerGraph.open() ==>tinkergraph[vertices:0 edges:0] gremlin> graph.io(gryo()).readGraph('/tmp/movie-lens.kryo') ==>null gremlin> g = graph.traversal() ==>graphtraversalsource[tinkergraph[vertices:9962 edges:1012657], standard] gremlin> g.V().count() ==>9962 gremlin> "Count the number of vertices in the graph." |V | = 9962 </li></div><div><li>13. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#13">~/tinkerpop3$ bin/gremlin.sh ,,,/ (o o) -----oOOo-(3)-oOOo----- plugin </a> activated: tinkerpop.server plugin activated: tinkerpop.utilities plugin activated: tinkerpop.tinkergraph gremlin> graph = TinkerGraph.open() ==>tinkergraph[vertices:0 edges:0] gremlin> graph.io(gryo()).readGraph('/tmp/movie-lens.kryo') ==>null gremlin> g = graph.traversal() ==>graphtraversalsource[tinkergraph[vertices:9962 edges:1012657], standard] gremlin> g.V().count() ==>9962 gremlin> "Count the number of vertices in the graph." |V | = 9962 Vertex map 9962 reducing barrier Long seed=0 value=seed binary operator: value -> value+1 count() { "m any-to-one" </li></div><div><li>14. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#14">Edge map 1012657 reducing barrier Long |E| </a> = 1012657 ~/tinkerpop3$ bin/gremlin.sh ,,,/ (o o) -----oOOo-(3)-oOOo----- plugin activated: tinkerpop.server plugin activated: tinkerpop.utilities plugin activated: tinkerpop.tinkergraph gremlin> graph = TinkerGraph.open() ==>tinkergraph[vertices:0 edges:0] gremlin> graph.io(gryo()).readGraph('/tmp/movie-lens.kryo') ==>null gremlin> g = graph.traversal() ==>graphtraversalsource[tinkergraph[vertices:9962 edges:1012657], standard] gremlin> g.V().count() ==>9962 gremlin> g.E().count() ==>1012657 gremlin> "Count the number of edges in the graph." count() { "m any-to-one" </li></div><div><li>15. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#15">~/tinkerpop3$ bin/gremlin.sh ,,,/ (o o) -----oOOo-(3)-oOOo----- plugin </a> activated: tinkerpop.server plugin activated: tinkerpop.utilities plugin activated: tinkerpop.tinkergraph gremlin> graph = TinkerGraph.open() ==>tinkergraph[vertices:0 edges:0] gremlin> graph.io(gryo()).readGraph('/tmp/movie-lens.kryo') ==>null gremlin> g = graph.traversal() ==>graphtraversalsource[tinkergraph[vertices:9962 edges:1012657], standard] gremlin> g.V().count() ==>9962 gremlin> g.E().count() ==>1012657 gremlin> g.V().label().groupCount() ==>[occupation:21, movie:3883, category:18, user:6040] gremlin> "For each vertex in the graph, emit its label, then group and count each distinct label." user user movie category ... Vertex String Map<String,Long> user user movie category map map reducing barrier [ occupation=21, movie=3883, category=18, user=6040 ] label() groupCount(){"one-to-one" "many-to-one" </li></div><div><li>16. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#16">~/tinkerpop3$ bin/gremlin.sh ,,,/ (o o) -----oOOo-(3)-oOOo----- plugin </a> activated: tinkerpop.server plugin activated: tinkerpop.utilities plugin activated: tinkerpop.tinkergraph gremlin> graph = TinkerGraph.open() ==>tinkergraph[vertices:0 edges:0] gremlin> graph.io(gryo()).readGraph('/tmp/movie-lens.kryo') ==>null gremlin> g = graph.traversal() ==>graphtraversalsource[tinkergraph[vertices:9962 edges:1012657], standard] gremlin> g.V().count() ==>9962 gremlin> g.E().count() ==>1012657 gremlin> g.V().label().groupCount() ==>[occupation:21, movie:3883, category:18, user:6040] gremlin> g.E().hasLabel('rated').values('stars').mean() ==>3.581564453029317 gremlin> "For each rated-edge in the graph, emit its stars property value and compute the average value." </li></div><div><li>17. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#17">~/tinkerpop3$ bin/gremlin.sh ,,,/ (o o) -----oOOo-(3)-oOOo----- plugin </a> activated: tinkerpop.server plugin activated: tinkerpop.utilities plugin activated: tinkerpop.tinkergraph gremlin> graph = TinkerGraph.open() ==>tinkergraph[vertices:0 edges:0] gremlin> graph.io(gryo()).readGraph('/tmp/movie-lens.kryo') ==>null gremlin> g = graph.traversal() ==>graphtraversalsource[tinkergraph[vertices:9962 edges:1012657], standard] gremlin> g.V().count() ==>9962 gremlin> g.E().count() ==>1012657 gremlin> g.V().label().groupCount() ==>[occupation:21, movie:3883, category:18, user:6040] gremlin> g.E().hasLabel('rated').values('stars').mean() ==>3.581564453029317 gremlin> g.V().hasLabel('user').map(outE('rated').count()).max() ==>2314 gremlin> "What is the maximum number of movies a single user rated?" </li></div><div><li>18. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#18">~/tinkerpop3$ bin/gremlin.sh ,,,/ (o o) -----oOOo-(3)-oOOo----- plugin </a> activated: tinkerpop.server plugin activated: tinkerpop.utilities plugin activated: tinkerpop.tinkergraph gremlin> graph = TinkerGraph.open() ==>tinkergraph[vertices:0 edges:0] gremlin> graph.io(gryo()).readGraph('/tmp/movie-lens.kryo') ==>null gremlin> g = graph.traversal() ==>graphtraversalsource[tinkergraph[vertices:9962 edges:1012657], standard] gremlin> g.V().count() ==>9962 gremlin> g.E().count() ==>1012657 gremlin> g.V().label().groupCount() ==>[occupation:21, movie:3883, category:18, user:6040] gremlin> g.E().hasLabel('rated').values('stars').mean() ==>3.581564453029317 gremlin> g.V().hasLabel('user').map(outE('rated').count()).max() ==>2314 gremlin> g.V().hasLabel('movie').values('year').min() ==>1919 gremlin> "What year was the oldest movie made?" </li></div><div><li>19. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#19">gremlin> g.V().hasLabel('category').values('name') ==>Animation ==>Children's ==>Comedy ==>Adventure ==>Fantasy ==>Romance ==>Drama ==>Action ==>Crime ==>Thriller ==>Horror ==>Sci-Fi ==>Documentary ==>War ==>Musical ==>Mystery ==>Film-Noir ==>Western "For each </a> vertex that is labeled 'category,' emit the name property value of that vertex." category user user movie category Vertex category category category category category categorycategory category Vertex Animation Children's Comedy Adventure Western ... String ﬁlter map hasLabel('category') values('name') "one-to-[one-or-none]" "one-to-one" </li></div><div><li>20. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#20">gremlin> g.V().hasLabel('category').as('a','b'). select('a','b'). by('name'). by(inE('category').count()) "For each </a> category vertex, emit a map of its name and the number of movies it represents." </li></div><div><li>21. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#21">hasLabelcategory : V </a> ∗ → V ∗ gremlin> g.V().hasLabel('category').as('a','b'). select('a','b'). by('name'). by(inE('category').count()) "For each category vertex, emit a map of its name and the number of movies it represents." V : G → V ∗ asa,b : V ∗ → (V × V )∗ G The set of all graphs f : A → B The function f maps values of type A to values of type B A∗ A stream of values of type A (A × B) The set of all pairs of values from A and B (cross product) N The set of all natural numbers (1, 2, 3, 4, …) The set of all strings (a, b, aa, ab, bb, …) selecta,b : (V × V )∗ → a valuesname : V ∗ → S b (inEcategory : V ∗ → E∗ ) ◦ (count : E∗ → N) → (S × N)∗ S Σ∗ typically denoted </li></div><div><li>22. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#22">gremlin> g.V().hasLabel('category').as('a','b'). select('a','b'). by('name'). by(inE('category').count()) ==>[a:Animation, b:105] ==>[a:Children's, </a> b:251] ==>[a:Comedy, b:1200] ==>[a:Adventure, b:283] ==>[a:Fantasy, b:68] ==>[a:Romance, b:471] ==>[a:Drama, b:1603] ==>[a:Action, b:503] ==>[a:Crime, b:211] ==>[a:Thriller, b:492] ==>[a:Horror, b:343] ==>[a:Sci-Fi, b:276] ==>[a:Documentary, b:127] ==>[a:War, b:143] ==>[a:Musical, b:114] ==>[a:Mystery, b:106] ==>[a:Film-Noir, b:44] ==>[a:Western, b:68] "For each category vertex, emit a map of its name and the number of movies it represents." category user user movie category Vertex category category category category category categorycategory category Vertex [a:Animation, b:105] [a:Children's, b:251] [a:Comedy, b:1200] [a:Adventure, b:283] … [a:Western, b:68] Map<String,Long> ﬁlter map category name:Animation category category category ... category map map reducing barrier 105 Vertex Edge Long category name:Animation Vertex String map Animationa b map ﬂatMap {"one-to-m any" "one-to-one" </li></div><div><li>23. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#23">gremlin> g.V().hasLabel('movie').as('a','b'). select('a','b'). by('name'). by(inE('rated').values('stars').mean()). order().by(select('b'),decr). limit(10) "For each </a> movie, emit a map of its name and average rating. Sort the maps in decreasing order by their average rating. Emit the ﬁrst 10 maps (i.e. top 10)." </li></div><div><li>24. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#24">gremlin> g.V().hasLabel('movie').as('a','b'). select('a','b'). by('name'). by(inE('rated').values('stars').mean()). order().by(select('b'),decr). limit(10) ==>[a:Charm's Incidents, </a> b:NaN] ==>[a:Prerokbe Ognja, b:NaN] ==>[a:Leopard Son, The, b:NaN] ==>[a:Bird of Prey, b:NaN] ==>[a:Plutonium Circus, b:NaN] ==>[a:Hustler White, b:NaN] ==>[a:Curtis's Charm, b:NaN] ==>[a:Three Lives and Only One Death, b:NaN] ==>[a:Hoogste tijd, b:NaN] ==>[a:Entertaining Angels: The Dorothy Day Story, b:NaN] category user user movie category Vertex movie movie movie movie movie moviemovie movie Vertex [a:Charm's Incidents, b:NaN] [a:Prerokbe Ognja, b:NaN] [a:Leopard Son, The, b:NaN] [a:Bird of Prey, b:NaN] ... [a:Entertaining Angels, b:NaN] Map<String,Double> ﬁlter map movie name:Charm's Incidents map reducing barrier NaN Vertex Edge Double movie name:Charm's Incidents Vertex String map Charm's Incidentsa b map map Integer ... "For each movie, emit a map of its name and average rating. Sort the maps in decreasing order by their average rating. Emit the ﬁrst 10 maps (i.e. top 10)." ﬂatMap </li></div><div><li>25. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#25">gremlin> g.V().hasLabel('movie').as('a','b'). select('a','b'). by('name'). by(coalesce( inE('rated').values('stars'), constant(0)).mean()). order().by(select('b'),decr). limit(10) ==>[a:Lured, b:5.0] ==>[a:One </a> Little Indian, b:5.0] ==>[a:Bittersweet Motel, b:5.0] ==>[a:Gate of Heavenly Peace, The, b:5.0] ==>[a:Follow the Bitch, b:5.0] ==>[a:Schlafes Bruder (Brother of Sleep), b:5.0] ==>[a:Ulysses (Ulisse), b:5.0] ==>[a:Song of Freedom, b:5.0] ==>[a:Smashing Time, b:5.0] ==>[a:Baby, The, b:5.0] "For each movie, get its name and mean rating (or 0 if no ratings). Order by average rating and emit top 10." user user movie category Vertex movie movie movie movie moviemovie movie Vertex Map<String,Double> ﬁlter map movie name:Charm's Incidents map map reducing barrier 0.0 Vertex Integer Double movie name:Charm's Incidents Vertex String map Charm's Incidentsa b map 0 [a:Lured, b:5.0] [a:One Little Indian, b:5.0] [a:Bittersweet Motel, b:5.0] [a:Gate of Heavenly Peace, b:5.0] ... [a:Baby, The, b:5.0] Map<String,Double> map [a:Charm's Incidents, b:NaN] [a:Prerokbe Ognja, b:NaN] [a:Leopard Son, The, b:NaN] [a:Bird of Prey, b:NaN] ... [a:Entertaining Angels, b:NaN] collecting barrier </li></div><div><li>26. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#26">gremlin> g.V().hasLabel('movie').as('a','b'). where(inE('rated').count().is(gt(10))). select('a','b'). by('name'). by(inE('rated').values('stars').mean()). order().by(select('b'),decr). limit(10) "For each </a> movie with at least 11 ratings, emit a map of its name and average rating. Sort the maps in decreasing order by their average rating. Emit the ﬁrst 10 maps (i.e. top 10)." </li></div><div><li>27. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#27">gremlin> g.V().hasLabel('movie').as('a','b'). where(inE('rated').count().is(gt(10))). select('a','b'). by('name'). by(inE('rated').values('stars').mean()). order().by(select('b'),decr). limit(10) ==>[a:Sanjuro, b:4.608695652173913] ==>[a:Seven </a> Samurai (The Magnificent Seven), b:4.560509554140127] ==>[a:Shawshank Redemption, The, b:4.554557700942973] ==>[a:Godfather, The, b:4.524966261808367] ==>[a:Close Shave, A, b:4.52054794520548] ==>[a:Usual Suspects, The, b:4.517106001121705] ==>[a:Schindler's List, b:4.510416666666667] ==>[a:Wrong Trousers, The, b:4.507936507936508] ==>[a:Sunset Blvd. (a.k.a. Sunset Boulevard), b:4.491489361702127] ==>[a:Raiders of the Lost Ark, b:4.47772] "For each movie with at least 11 ratings, emit a map of its name and average rating. Sort the maps in decreasing order by their average rating. Emit the ﬁrst 10 maps (i.e. top 10)." map movie name:Sanjuro rated rated rated ... rated map reducing barrier 4.60 Vertex Edge Double movie name:Sanjuro Vertex String map Sanjuroa b map map Integer user user movie category Vertex movie movie movie movie moviemovie movie Vertex ﬁlter movie rated rated rated ... rated reducing barrier Vertex Edge map Long 69 name:Sanjuro ﬁlter movie movie movie movie movie Vertex 5 4 … 5 [[a:Sanjuro, b:4.60] [a:Seven Samurai, b:4.56] [a:Shawshank Redemption, b:4.55] [a:Godfather, The, b:4.52] ... [a:Raiders of the Lost Ark, b:4.47] […] […] […] […] … […] Map<String,Double> Map<String,Double> map collecting barrier ﬂatMap ﬂatMap { { </li></div><div><li>28. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#28">gremlin> g.V().hasLabel('movie'). where(inE('rated').count().is(gt(10))). toString() ==>[GraphStep([],vertex), HasStep([~label.eq(movie)]), TraversalFilterStep([ VertexStep(IN,[rated],edge), CountGlobalStep, IsStep(gt(10))])] "What </a> is the execution plan for the traversal prior to compiler optimizations being applied?" V : G → V ∗ hasLabelmovie : V ∗ → V ∗ where : V ∗ → inErated : V ∗ → E∗ count : E∗ → N isgt(10) : N → (N ∪ ∅) → V ∗ "true orfalse" </li></div><div><li>29. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#29">gremlin> g.V().hasLabel('movie'). where(inE('rated').count().is(gt(10))). iterate().toString() ==>[TinkerGraphStep(vertex,[~label.eq(movie)]), TraversalFilterStep([ VertexStep(IN,[rated],edge), RangeGlobalStep(0,11), CountGlobalStep, IsStep(gt(10))])] "What is </a> the execution plan for the traversal after compiler optimizations have been applied?" * TinkerGraphStragegy: Access vendor-speciﬁc vertex partition by label. * RangeByIsCountStrategy: Only iterate 1 more than required count. where : V ∗ → inErated : V ∗ → E∗ count : E∗ → N isgt(10) : N → (N ∪ ∅) limit11 : E∗ → E∗ Vlabel=movie : G → V ∗ → V ∗ "true orfalse" </li></div><div><li>30. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#30">gremlin> g.getStrategies() ==>ConjunctionStrategy a.and().b => </a> and(a,b) a.or().b => or(a,b) a.or().b.and().c => or(a,and(b,c)) a.and().b.or().c => or(and(a,b),c) ==>IncidentToAdjacentStrategy a.outE().inV().b => a.out().b ==>AdjacentToIncidentStrategy a.in().count().b => a.inE().count().b a.where(out()).b => a.where(outE()).b a.and(in(),out()).b => a.and(inE(),outE()).b ==>IdentityRemovalStrategy a.identity().b => a.b ==>FilterRankingStrategy a.order().dedup().b => a.dedup().order().b a.and(c,d).has().b => a.has().and(c,d).b a.simplePath().where().b => b.where().simplePath().a ==>MatchPredicateStrategy a.match(c,d).where(e).b => a.match(c,d,e) a.match(has(),c,d).b => a.has().match(c,d).b ==>RangeByIsCountStrategy a.count().is(0) => a.limit(1).count().is(0) ==>TinkerGraphStepStrategy V.has().has().b => V[has,has].b ==>ProfileStrategy a.b.c.profile() => a.profile().b.profile().c.profile() ==>ComputerVerificationStrategy a.order.b => IllegalStateException a.local(out().out()).b => IllegalStateException "What compilation strategies are associated with the graph traversal source?" </li></div><div><li>31. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#31">gremlin> g.V().has('movie','name','Die Hard'). inE('rated').values('stars').mean() ==>4.121848739495798 "What </a> is Die Hard's average rating?" </li></div><div><li>32. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#32">gremlin> g.V().has('movie','name','Die Hard'). inE('rated').values('stars').mean() ==>4.121848739495798 "What </a> is Die Hard's average rating?" movie movie movie Vertex movie Vertex ﬁlter name:Die Hard ﬂatMap rated rated rated ... rated Edge map 3 5 5 … 4 Integer map Double 4.1218 reducing barrier V : G → V ∗ hasLabelmovie : V ∗ → V ∗ hasname=Die Hard : V ∗ → V ∗ inErated : V ∗ → E∗ mean : N∗ → R valuesstars : E∗ → N∗ user user movie user Vertex ﬁlter { "one-to-[one-or-none]" "one-to-[one-or-none]" "one-to-many" "one-to-one" "many-to-one" </li></div><div><li>33. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#33">gremlin> g.V().has('movie','name','Die Hard').as('a'). inE('rated').has('stars',5).outV(). where(out('occupation').has('name','programmer')). outE('rated').has('stars',5).inV(). where(neq('a')). groupCount().by('name'). order(local).by(valueDecr). limit(local,10). unfold() </a> // so its not printed on a single line "Which programmers like Die Hard and what other movies do they like? Group and count the movies by their name. Sort the group count map in decreasing order by the count. Clip the map to the top 10 entries and stream out the map's entries (for display purposes)." </li></div><div><li>34. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#34">gremlin> g.V().has('movie','name','Die Hard').as('a'). inE('rated').has('stars',5).outV(). where(out('occupation').has('name','programmer')). outE('rated').has('stars',5).inV(). where(neq('a')). groupCount().by('name'). order(local).by(valueDecr). limit(local,10). unfold() </a> // so its not printed on a single line "Which programmers like Die Hard and what other movies do they like? Group and count the movies by their name. Sort the group count map in decreasing order by the count. Clip the map to the top 10 entries and stream out the map's entries (for display purposes)." user user movie user Vertex movie Vertex ﬁlter ﬁlter name:Die Hard ﬂatMap rated rated rated ... rated Edge ﬁlter rated ... rated Edge map Vertex user user user useruser user Vertex Vertex occupationﬂatMap Vertex ﬁlter rated rated rated ... rated Edge ﬁlter rated ... rated Edge map Vertex movie movie moviemovie movie Vertex Vertex user user user ﬂatMap ﬁlter movie Vertex ﬁlter Vertex movie movie movie map reducing barrier [ Aliens=105, Braveheart=24, … Pulp Fiction=19 ] Map<String,Long> map collecting barrier [ Raider of the Lost Ark=36, Star Wars: Episode V=24, Star Wars: Episode IV=34 … Airplane II: The Sequel=1 ] Map<String,Long> [ Raider of the Lost Ark=36, Star Wars: Episode V=24, Star Wars: Episode IV=34 … Alien=22 ] Map<String,Long> map occupation programmer not Die Hard </li></div><div><li>35. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#35">gremlin> g.V().has('movie','name','Die Hard').as('a'). inE('rated').has('stars',5).outV(). where(out('occupation').has('name','programmer')). outE('rated').has('stars',5).inV(). where(neq('a')). groupCount().by('name'). order(local).by(valueDecr). limit(local,10). unfold() </a> // so its not printed on a single line ==>Raiders of the Lost Ark=36 ==>Star Wars: Episode V - The Empire Strikes Back=36 ==>Star Wars: Episode IV - A New Hope=34 ==>Matrix, The=32 ==>Terminator, The=29 ==>Star Wars: Episode VI - Return of the Jedi=26 ==>Sixth Sense, The=26 ==>Braveheart=24 ==>Aliens=23 ==>Alien=22 gremlin> "Which programmers like Die Hard and what other movies do they like? Group and count the movies by their name. Sort the group count map in decreasing order by the count. Clip the map to the top 10 entries and stream out the map's entries (for display purposes)." </li></div><div><li>36. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#36">gremlin> g.V(). match( __.as('a').hasLabel('movie'), __.as('a').out('category').has('name','Action'), __.as('a').has('year',between(1980,1990)), __.as('a').inE('rated').as('b'), __.as('b').has('stars',5), __.as('b').outV().as('c'), __.as('c').out('occupation').has('name','programmer'), __.as('c').has('age',between(30,40))). select('a').groupCount().by('name'). order(local).by(valueDecr). limit(local,10). unfold() // </a> so its not printed on a single line "What 80's action movies do 30-something programmers like? Group count the movies by their name and sort the group count map in decreasing order by value. Clip the map to the top 10 and emit the map entries." </li></div><div><li>37. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#37">"What 80's action </a> movies do 30-something programmers like? Group count the movies by their name and sort the group count map in decreasing order by value. Clip the map to the top 10 and emit the map entries." gremlin> g.V(). match( __.as('a').hasLabel('movie'), __.as('a').out('category').has('name','Action'), __.as('a').has('year',between(1980,1990)), __.as('a').inE('rated').as('b'), __.as('b').has('stars',5), __.as('b').outV().as('c'), __.as('c').out('occupation').has('name','programmer'), __.as('c').has('age',between(30,40))). select('a').groupCount().by('name'). order(local).by(valueDecr). limit(local,10). unfold() // so its not printed on a single line ==>Raiders of the Lost Ark=26 ==>Star Wars: Episode V - The Empire Strikes Back=26 ==>Terminator, The=23 ==>Star Wars: Episode VI - Return of the Jedi=22 ==>Princess Bride, The=19 ==>Aliens=18 ==>Boat, The (Das Boot)=11 ==>Indiana Jones and the Last Crusade=11 ==>Star Trek: The Wrath of Khan=10 ==>Abyss, The=9 gremlin> </li></div><div><li>38. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#38">MatchStep GraphTraversal.match(Traversal... traversalPatterns) x.match( a...b a...c c... or( a...c a...b ) c.repeat(...).b not(c...a) b...count().e c...count().e ).dedup(a,b).y a,b,c,e : </a> once a variable is set, it must hold equal for all patterns c... : "predicate patterns" simply check for the existence of a result or()/and() : nested conjunctive patterns supported repeat(...) : recursive patterns supported not(...) : not'ing of patterns supported count() : barrier patterns supported dedup(a,b) : internal de-duplication of variable values supported x.match().y : possible to go from imperative to declarative, etc. Plug and Play MatchAlgorithms GreedyMatchAlgorithm : try each pattern in the order provided by the user CountMatchAlgorithm : continually re-sort patterns by the cardinality of their set reductions </li></div><div><li>39. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#39">// CountMatchAlgorithm (default) gremlin> </a> clockWithResult(50){ g.V().match( __.as('a').out('rated').as('b'), __.as('a').out('occupation').has('name','farmer')). select('a','b').count().next()} ==>66.31955294 // time in milliseconds ==>2706 // number of results // GreedyMatchAlgorithm gremlin> g = graph.traversal(GraphTraversalSource.build(). with(MatchAlgorithmStrategy.build(). algorithm(MatchStep.GreedyMatchAlgorithm).create())) ==>graphtraversalsource[tinkergraph[vertices:9962 edges:1012657], standard] gremlin> clockWithResult(50){ g.V().match( __.as('a').out('rated').as('b'), __.as('a').out('occupation').has('name','farmer')). select('a','b').count().next()} ==>1902.6290871599997 // time in milliseconds ==>2706 // number of results "Which movies did each farmer rate? -- benchmark CountMatchAlgorithm vs. GreedyMatchAlgorithm." farmermoviesusers 1000209 2706 farmer moviesusers 17 2706 </li></div><div><li>40. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#40">gremlin> g.V().hasLabel('movie'). where(inE('rated').count().is(gt(10))). group(). by{((int)(it.value('year') / </a> 10)) * 10}. by(). by(unfold().order(). by(inE('rated').values('stars').mean(),decr). values('name'). limit(1)). order(local).by(keyIncr). unfold() // so its not printed on a single line "What is the most liked movie in each decade?" </li></div><div><li>41. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#41">gremlin> g.V().hasLabel('movie'). where(inE('rated').count().is(gt(10))). group(). by{((int)(it.value('year') / </a> 10)) * 10}. by(). by(unfold().order(). by(inE('rated').values('stars').mean(),decr). values('name'). limit(1)). order(local).by(keyIncr). unfold() // so its not printed on a single line "What is the most liked movie in each decade?" λ λ Nearly every step that takes a traversal argument can also take a lambda. It is recommended that users do not use lambdas as they are not subject to traversal strategy (i.e. compiler) optimization. However, they are useful when no provided step yields the desired computation. </li></div><div><li>42. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#42">gremlin> g.V().hasLabel('movie'). where(inE('rated').count().is(gt(10))). group(). by{((int)(it.value('year') / </a> 10)) * 10}. by(). by(unfold().order(). by(inE('rated').values('stars').mean(),decr). values('name'). limit(1)). order(local).by(keyIncr). unfold() // so its not printed on a single line ==>1910=Daddy Long Legs ==>1920=General, The ==>1930=City Lights ==>1940=Third Man, The ==>1950=Seven Samurai (The Magnificent Seven) ==>1960=Sanjuro ==>1970=Godfather, The ==>1980=Raiders of the Lost Ark ==>1990=Shawshank Redemption, The ==>2000=Almost Famous gremlin> "What is the most liked movie in each decade?" </li></div><div><li>43. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#43">gremlin> graph = </a> HadoopGraph.open('conf/hadoop/movie-lens.properties') ==>hadoopgraph[gryoinputformat->gryooutputformat] gremlin> g = graph.traversal(computer(SparkGraphComputer)) ==>graphtraversalsource [hadoopgraph[gryoinputformat->gryooutputformat], sparkgraphcomputer] gremlin> "Which movies are most central in the implicit 5-stars graph?" </li></div><div><li>44. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#44">gremlin> graph = </a> HadoopGraph.open('conf/hadoop/movie-lens.properties') ==>hadoopgraph[gryoinputformat->gryooutputformat] gremlin> g = graph.traversal(computer(SparkGraphComputer)) ==>graphtraversalsource [hadoopgraph[gryoinputformat->gryooutputformat], sparkgraphcomputer] gremlin> g.V().repeat(outE('rated').has('stars', 5).inV(). groupCount('m').by('name'). inE('rated').has('stars', 5).outV()). times(4).cap('m') "Which movies are most central in the implicit 5-stars graph?" user movie user ratedrated m 4x cap('m') repeat(…).times(4) g.V() stars=5 stars=5 </li></div><div><li>45. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#45">gremlin> graph = </a> HadoopGraph.open('conf/hadoop/movie-lens.properties') ==>hadoopgraph[gryoinputformat->gryooutputformat] gremlin> g = graph.traversal(computer(SparkGraphComputer)) ==>graphtraversalsource [hadoopgraph[gryoinputformat->gryooutputformat], sparkgraphcomputer] gremlin> g.V().repeat(outE('rated').has('stars', 5).inV(). groupCount('m').by('name'). inE('rated').has('stars', 5).outV()). times(4).cap('m') ==>Fantasia 2000=2676505178171564 ==>Pale Rider=1369969000295362 ==>Crucible, The=401712993698149 ==>About Adam=37981148456999 ==>Akira=3659939409345918 ... gremlin> "Which movies are most central in the implicit 5-stars graph?" </li></div><div><li>46. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#46">gremlin> graph = </a> HadoopGraph.open('conf/hadoop/movie-lens.properties') ==>hadoopgraph[gryoinputformat->gryooutputformat] gremlin> g = graph.traversal(computer(SparkGraphComputer)) ==>graphtraversalsource [hadoopgraph[gryoinputformat->gryooutputformat], sparkgraphcomputer] gremlin> g.V().repeat(outE('rated').has('stars', 5).inV(). groupCount('m').by('name'). inE('rated').has('stars', 5).outV()). times(4).cap('m') ==>Fantasia 2000=2676505178171564 ==>Pale Rider=1369969000295362 ==>Crucible, The=401712993698149 ==>About Adam=37981148456999 ==>Akira=3659939409345918 ... gremlin> hdfs.ls('output/m') ==>rw-r--r-- daniel supergroup 0 _SUCCESS ==>rw-r--r-- daniel supergroup 245314 part-r-00000 gremlin> hdfs.head('output/m', ObjectWritable).sort {-it.value}.take(10) ==>Star Wars: Episode IV - A New Hope 35405394353105332 ==>American Beauty 31943228282020585 ==>Raiders of the Lost Ark 31224779793238499 ==>Star Wars: Episode V - The Empire Strikes Back 30434677119726223 ==>Godfather, The 30258518523013057 ==>Shawshank Redemption, The 28297717387901031 ==>Schindler's List 27539336654199309 ==>Silence of the Lambs, The 26736276376806173 ==>Fargo 26531050311325270 ==>Matrix, The 26395118239203191 "Which movies are most central in the implicit 5-stars graph?" </li></div><div><li>47. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#47">gremlin> :plugin use </a> tinkerpop.gephi ==>tinkerpop.gephi activated gremlin> :remote connect tinkerpop.gephi ==>Connection to Gephi - http://localhost:8080/workspace0 with stepDelay:1000, startRGBColor:[0.0, 1.0, 0.5], colorToFade:g, colorFadeRate:0.7, startSize: 20.0,sizeDecrementRate:0.33 gremlin> </li></div><div><li>48. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#48">gremlin> :plugin use </a> tinkerpop.gephi ==>tinkerpop.gephi activated gremlin> :remote connect tinkerpop.gephi ==>Connection to Gephi - http://localhost:8080/workspace0 with stepDelay:1000, startRGBColor:[0.0, 1.0, 0.5], colorToFade:g, colorFadeRate:0.7, startSize: 20.0,sizeDecrementRate:0.33 gremlin> :> g.V().hasLabel('user'). order(). by(outE('rated').count(), decr).limit(10).as('a'). local(outE('rated').order(). by('stars', decr). // first by stars by(inV().inE('rated').count(), decr). // then by ratings limit(10)). subgraph('sg').inV().outE('category'). subgraph('sg').select('a').outE('occupation'). subgraph('sg').cap('sg').next() ==>tinkergraph[vertices:82 edges:233] gremlin> "Which users rated the most movies? For each user, display their 10 favorite movies, the categories of those movies, and their occupation. "moviebuffs" </li></div><div></div><div><li>50. <a class="Transcript_link__MLbGS" href="https://www.slideshare.net/slideshow/the-gremlin-traversal-language/51792873#50">Thanks for listening… </a> </li></div></ul></div></div><dialog class="Modal_root__TYkzh FullscreenModal_root__efM9m" id=":R2kf6:"><div class="Modal_wrapper__4UTGq"><div class="modal-content Modal_content__R1F4d FullscreenModal_content__bQ6mt"></div></div></dialog><div class="ad textads banner-ads banner_ads ad-unit ad-zone ad-space adsbox ads prebid" style="position:absolute;height:1px"></div><footer class="Footer_footer__N3WmV"><div class="Footer_top__y0vfl" data-testid="footer-top"><div class="Footer_links__F2xFZ"><a class="Link_root__vn3ab Link_light__mcUPh Link_size-medium__ZLo12 Link_weight-bold__me4nt" style="order:0" href="/about">About</a><a class="Link_root__vn3ab Link_light__mcUPh Link_size-medium__ZLo12 Link_weight-bold__me4nt" style="order:1" 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Rodriguez and Daniel Kuppitz\nhttp://tinkerpop.incubator.apache.org\n ","user movie categoryoccupation\noccupation rated category\nname:String\ngender:[M,F]\nage:integer\nname:String\nyear:integer\nname:String\nstars:[1,2,3,4,5]\nhttp://grouplens.org/datasets/movielens/\nMovieLens Dataset\n ","user\n|Vuser| = 6040\n|Vmovie| = 3883\nmovie\n|Vcategory| = 18\ncategory\n|Voccupation| = 21\noccupation\noccupation\n|Eoccupation| = 6040\nrated\n|Erated| = 1000209\ncategory\n|Ecategory| = 6408\nname:String\ngender:[M,F]\nage:integer\nname:String\nyear:integer\nname:String\nstars:[1,2,3,4,5]\nhttp://grouplens.org/datasets/movielens/\nG = (V, E)\nMovieLens Dataset\n ","~/tinkerpop3$ bin/gremlin.sh\ngremlin\u003e\n ","~/tinkerpop3$ bin/gremlin.sh\n,,,/\n(o o)\n-----oOOo-(3)-oOOo-----\nplugin activated: tinkerpop.server\nplugin activated: tinkerpop.utilities\nplugin activated: tinkerpop.tinkergraph\ngremlin\u003e\n ","~/tinkerpop3$ bin/gremlin.sh\n,,,/\n(o o)\n-----oOOo-(3)-oOOo-----\nplugin activated: tinkerpop.server\nplugin activated: tinkerpop.utilities\nplugin activated: tinkerpop.tinkergraph\ngremlin\u003e\nGremlin-Java8\nGremlin-Groovy*\nGremlin-Scala\nGremlin-Clojure\nGremlin-JavaScript\nGremlin-Python\nGremlin-PHP\n...\n ","~/tinkerpop3$ bin/gremlin.sh\n,,,/\n(o o)\n-----oOOo-(3)-oOOo-----\nplugin activated: tinkerpop.server\nplugin activated: tinkerpop.utilities\nplugin activated: tinkerpop.tinkergraph\ngremlin\u003e graph = TinkerGraph.open()\n==\u003etinkergraph[vertices:0 edges:0]\ngremlin\u003e\n\"Create a new TinkerGraph.\"\n ","~/tinkerpop3$ bin/gremlin.sh\n,,,/\n(o o)\n-----oOOo-(3)-oOOo-----\nplugin activated: tinkerpop.server\nplugin activated: tinkerpop.utilities\nplugin activated: tinkerpop.tinkergraph\ngremlin\u003e graph = TinkerGraph.open()\n==\u003etinkergraph[vertices:0 edges:0]\ngremlin\u003e\n\"Create a new TinkerGraph.\"\nG = (V = ∅, E = ∅)\nG The graph is a set of vertices and edges\nV The set of vertices in the graph\nE The set of edges in the graph\n∅ The empty set -- no elements\n ","~/tinkerpop3$ bin/gremlin.sh\n,,,/\n(o o)\n-----oOOo-(3)-oOOo-----\nplugin activated: tinkerpop.server\nplugin activated: tinkerpop.utilities\nplugin activated: tinkerpop.tinkergraph\ngremlin\u003e graph = TinkerGraph.open()\n==\u003etinkergraph[vertices:0 edges:0]\ngremlin\u003e\n\"Create a new TinkerGraph.\"\nG = (V = ∅, E = ∅)\nTitanGraph.open(…)\nNeo4jGraph.open(…)\nOrientGraph.open(…)\nSqlgGraph.open(…)\nHadoopGraph.open(…)\nGiraphGraphComputer\nSparkGraphComputer\nElasticGraph.open(…)\n...\n ","G = (V = ∅, E ⊆ (V × V ))\n~/tinkerpop3$ bin/gremlin.sh\n,,,/\n(o o)\n-----oOOo-(3)-oOOo-----\nplugin activated: tinkerpop.server\nplugin activated: tinkerpop.utilities\nplugin activated: tinkerpop.tinkergraph\ngremlin\u003e graph = TinkerGraph.open()\n==\u003etinkergraph[vertices:0 edges:0]\ngremlin\u003e graph.io(gryo()).readGraph('/tmp/movie-lens.kryo')\n==\u003enull\ngremlin\u003e\n\"Load the MovieLens dataset into the newly created TinkerGraph.\"\nSet A is a subset of (or equal to) set B\nThe set of all ordered pairs of vertices (directed binary edges)\nA ⊆ B\n(V × V )\n ","~/tinkerpop3$ bin/gremlin.sh\n,,,/\n(o o)\n-----oOOo-(3)-oOOo-----\nplugin activated: tinkerpop.server\nplugin activated: tinkerpop.utilities\nplugin activated: tinkerpop.tinkergraph\ngremlin\u003e graph = TinkerGraph.open()\n==\u003etinkergraph[vertices:0 edges:0]\ngremlin\u003e graph.io(gryo()).readGraph('/tmp/movie-lens.kryo')\n==\u003enull\ngremlin\u003e g = graph.traversal()\n==\u003egraphtraversalsource[tinkergraph[vertices:9962 edges:1012657], standard]\ngremlin\u003e\n\"Create a graph traversal source for spawning graph traversals over the MovieLens graph.\"\n ","~/tinkerpop3$ bin/gremlin.sh\n,,,/\n(o o)\n-----oOOo-(3)-oOOo-----\nplugin activated: tinkerpop.server\nplugin activated: tinkerpop.utilities\nplugin activated: tinkerpop.tinkergraph\ngremlin\u003e graph = TinkerGraph.open()\n==\u003etinkergraph[vertices:0 edges:0]\ngremlin\u003e graph.io(gryo()).readGraph('/tmp/movie-lens.kryo')\n==\u003enull\ngremlin\u003e g = graph.traversal()\n==\u003egraphtraversalsource[tinkergraph[vertices:9962 edges:1012657], standard]\ngremlin\u003e g.V().count()\n==\u003e9962\ngremlin\u003e\n\"Count the number of vertices in the graph.\"\n|V | = 9962\n ","~/tinkerpop3$ bin/gremlin.sh\n,,,/\n(o o)\n-----oOOo-(3)-oOOo-----\nplugin activated: tinkerpop.server\nplugin activated: tinkerpop.utilities\nplugin activated: tinkerpop.tinkergraph\ngremlin\u003e graph = TinkerGraph.open()\n==\u003etinkergraph[vertices:0 edges:0]\ngremlin\u003e graph.io(gryo()).readGraph('/tmp/movie-lens.kryo')\n==\u003enull\ngremlin\u003e g = graph.traversal()\n==\u003egraphtraversalsource[tinkergraph[vertices:9962 edges:1012657], standard]\ngremlin\u003e g.V().count()\n==\u003e9962\ngremlin\u003e\n\"Count the number of vertices in the graph.\"\n|V | = 9962\nVertex\nmap 9962\nreducing barrier\nLong\nseed=0\nvalue=seed\nbinary operator: value -\u003e value+1\ncount()\n{ \"m\nany-to-one\"\n ","Edge\nmap 1012657\nreducing barrier\nLong\n|E| = 1012657\n~/tinkerpop3$ bin/gremlin.sh\n,,,/\n(o o)\n-----oOOo-(3)-oOOo-----\nplugin activated: tinkerpop.server\nplugin activated: tinkerpop.utilities\nplugin activated: tinkerpop.tinkergraph\ngremlin\u003e graph = TinkerGraph.open()\n==\u003etinkergraph[vertices:0 edges:0]\ngremlin\u003e graph.io(gryo()).readGraph('/tmp/movie-lens.kryo')\n==\u003enull\ngremlin\u003e g = graph.traversal()\n==\u003egraphtraversalsource[tinkergraph[vertices:9962 edges:1012657], standard]\ngremlin\u003e g.V().count()\n==\u003e9962\ngremlin\u003e g.E().count()\n==\u003e1012657\ngremlin\u003e\n\"Count the number of edges in the graph.\"\ncount()\n{ \"m\nany-to-one\"\n ","~/tinkerpop3$ bin/gremlin.sh\n,,,/\n(o o)\n-----oOOo-(3)-oOOo-----\nplugin activated: tinkerpop.server\nplugin activated: tinkerpop.utilities\nplugin activated: tinkerpop.tinkergraph\ngremlin\u003e graph = TinkerGraph.open()\n==\u003etinkergraph[vertices:0 edges:0]\ngremlin\u003e graph.io(gryo()).readGraph('/tmp/movie-lens.kryo')\n==\u003enull\ngremlin\u003e g = graph.traversal()\n==\u003egraphtraversalsource[tinkergraph[vertices:9962 edges:1012657], standard]\ngremlin\u003e g.V().count()\n==\u003e9962\ngremlin\u003e g.E().count()\n==\u003e1012657\ngremlin\u003e g.V().label().groupCount()\n==\u003e[occupation:21, movie:3883, category:18, user:6040]\ngremlin\u003e\n\"For each vertex in the graph, emit its label, then group and count each distinct label.\"\nuser\nuser\nmovie\ncategory\n...\nVertex String Map\u003cString,Long\u003e\nuser\nuser\nmovie\ncategory\nmap map\nreducing\nbarrier\n[\noccupation=21,\nmovie=3883,\ncategory=18,\nuser=6040\n]\nlabel() groupCount(){\"one-to-one\" \"many-to-one\"\n ","~/tinkerpop3$ bin/gremlin.sh\n,,,/\n(o o)\n-----oOOo-(3)-oOOo-----\nplugin activated: tinkerpop.server\nplugin activated: tinkerpop.utilities\nplugin activated: tinkerpop.tinkergraph\ngremlin\u003e graph = TinkerGraph.open()\n==\u003etinkergraph[vertices:0 edges:0]\ngremlin\u003e graph.io(gryo()).readGraph('/tmp/movie-lens.kryo')\n==\u003enull\ngremlin\u003e g = graph.traversal()\n==\u003egraphtraversalsource[tinkergraph[vertices:9962 edges:1012657], standard]\ngremlin\u003e g.V().count()\n==\u003e9962\ngremlin\u003e g.E().count()\n==\u003e1012657\ngremlin\u003e g.V().label().groupCount()\n==\u003e[occupation:21, movie:3883, category:18, user:6040]\ngremlin\u003e g.E().hasLabel('rated').values('stars').mean()\n==\u003e3.581564453029317\ngremlin\u003e\n\"For each rated-edge in the graph, emit its stars property value and compute the average value.\"\n ","~/tinkerpop3$ bin/gremlin.sh\n,,,/\n(o o)\n-----oOOo-(3)-oOOo-----\nplugin activated: tinkerpop.server\nplugin activated: tinkerpop.utilities\nplugin activated: tinkerpop.tinkergraph\ngremlin\u003e graph = TinkerGraph.open()\n==\u003etinkergraph[vertices:0 edges:0]\ngremlin\u003e graph.io(gryo()).readGraph('/tmp/movie-lens.kryo')\n==\u003enull\ngremlin\u003e g = graph.traversal()\n==\u003egraphtraversalsource[tinkergraph[vertices:9962 edges:1012657], standard]\ngremlin\u003e g.V().count()\n==\u003e9962\ngremlin\u003e g.E().count()\n==\u003e1012657\ngremlin\u003e g.V().label().groupCount()\n==\u003e[occupation:21, movie:3883, category:18, user:6040]\ngremlin\u003e g.E().hasLabel('rated').values('stars').mean()\n==\u003e3.581564453029317\ngremlin\u003e g.V().hasLabel('user').map(outE('rated').count()).max()\n==\u003e2314\ngremlin\u003e\n\"What is the maximum number of movies a single user rated?\"\n ","~/tinkerpop3$ bin/gremlin.sh\n,,,/\n(o o)\n-----oOOo-(3)-oOOo-----\nplugin activated: tinkerpop.server\nplugin activated: tinkerpop.utilities\nplugin activated: tinkerpop.tinkergraph\ngremlin\u003e graph = TinkerGraph.open()\n==\u003etinkergraph[vertices:0 edges:0]\ngremlin\u003e graph.io(gryo()).readGraph('/tmp/movie-lens.kryo')\n==\u003enull\ngremlin\u003e g = graph.traversal()\n==\u003egraphtraversalsource[tinkergraph[vertices:9962 edges:1012657], standard]\ngremlin\u003e g.V().count()\n==\u003e9962\ngremlin\u003e g.E().count()\n==\u003e1012657\ngremlin\u003e g.V().label().groupCount()\n==\u003e[occupation:21, movie:3883, category:18, user:6040]\ngremlin\u003e g.E().hasLabel('rated').values('stars').mean()\n==\u003e3.581564453029317\ngremlin\u003e g.V().hasLabel('user').map(outE('rated').count()).max()\n==\u003e2314\ngremlin\u003e g.V().hasLabel('movie').values('year').min()\n==\u003e1919\ngremlin\u003e\n\"What year was the oldest movie made?\"\n ","gremlin\u003e g.V().hasLabel('category').values('name')\n==\u003eAnimation\n==\u003eChildren's\n==\u003eComedy\n==\u003eAdventure\n==\u003eFantasy\n==\u003eRomance\n==\u003eDrama\n==\u003eAction\n==\u003eCrime\n==\u003eThriller\n==\u003eHorror\n==\u003eSci-Fi\n==\u003eDocumentary\n==\u003eWar\n==\u003eMusical\n==\u003eMystery\n==\u003eFilm-Noir\n==\u003eWestern\n\"For each vertex that is labeled 'category,' emit the name property value of that vertex.\"\ncategory\nuser\nuser\nmovie\ncategory\nVertex\ncategory\ncategory\ncategory\ncategory\ncategory\ncategorycategory\ncategory\nVertex\nAnimation\nChildren's\nComedy\nAdventure\nWestern\n...\nString\nﬁlter map\nhasLabel('category') values('name')\n\"one-to-[one-or-none]\" \"one-to-one\"\n ","gremlin\u003e g.V().hasLabel('category').as('a','b').\nselect('a','b').\nby('name').\nby(inE('category').count())\n\"For each category vertex, emit a map of its name and the number of movies it represents.\"\n ","hasLabelcategory : V ∗\n→ V ∗\ngremlin\u003e g.V().hasLabel('category').as('a','b').\nselect('a','b').\nby('name').\nby(inE('category').count())\n\"For each category vertex, emit a map of its name and the number of movies it represents.\"\nV : G → V ∗\nasa,b : V ∗\n→ (V × V )∗\nG The set of all graphs\nf : A → B The function f maps values of type A to values of type B\nA∗ A stream of values of type A\n(A × B) The set of all pairs of values from A and B (cross product)\nN The set of all natural numbers (1, 2, 3, 4, …)\nThe set of all strings (a, b, aa, ab, bb, …)\nselecta,b : (V × V )∗\n→\na valuesname : V ∗\n→ S\nb (inEcategory : V ∗\n→ E∗\n) ◦ (count : E∗\n→ N)\n→ (S × N)∗\nS Σ∗\ntypically denoted\n ","gremlin\u003e g.V().hasLabel('category').as('a','b').\nselect('a','b').\nby('name').\nby(inE('category').count())\n==\u003e[a:Animation, b:105]\n==\u003e[a:Children's, b:251]\n==\u003e[a:Comedy, b:1200]\n==\u003e[a:Adventure, b:283]\n==\u003e[a:Fantasy, b:68]\n==\u003e[a:Romance, b:471]\n==\u003e[a:Drama, b:1603]\n==\u003e[a:Action, b:503]\n==\u003e[a:Crime, b:211]\n==\u003e[a:Thriller, b:492]\n==\u003e[a:Horror, b:343]\n==\u003e[a:Sci-Fi, b:276]\n==\u003e[a:Documentary, b:127]\n==\u003e[a:War, b:143]\n==\u003e[a:Musical, b:114]\n==\u003e[a:Mystery, b:106]\n==\u003e[a:Film-Noir, b:44]\n==\u003e[a:Western, b:68]\n\"For each category vertex, emit a map of its name and the number of movies it represents.\"\ncategory\nuser\nuser\nmovie\ncategory\nVertex\ncategory\ncategory\ncategory\ncategory\ncategory\ncategorycategory\ncategory\nVertex\n[a:Animation, b:105]\n[a:Children's, b:251]\n[a:Comedy, b:1200]\n[a:Adventure, b:283]\n…\n[a:Western, b:68]\nMap\u003cString,Long\u003e\nﬁlter map\ncategory\nname:Animation\ncategory\ncategory\ncategory\n...\ncategory\nmap map\nreducing\nbarrier\n105\nVertex Edge Long\ncategory\nname:Animation\nVertex String\nmap Animationa\nb\nmap\nﬂatMap\n{\"one-to-m\nany\"\n\"one-to-one\"\n ","gremlin\u003e g.V().hasLabel('movie').as('a','b').\nselect('a','b').\nby('name').\nby(inE('rated').values('stars').mean()).\norder().by(select('b'),decr).\nlimit(10)\n\"For each movie, emit a map of its name and average rating.\nSort the maps in decreasing order by their average rating. Emit the ﬁrst 10 maps (i.e. top 10).\"\n ","gremlin\u003e g.V().hasLabel('movie').as('a','b').\nselect('a','b').\nby('name').\nby(inE('rated').values('stars').mean()).\norder().by(select('b'),decr).\nlimit(10)\n==\u003e[a:Charm's Incidents, b:NaN]\n==\u003e[a:Prerokbe Ognja, b:NaN]\n==\u003e[a:Leopard Son, The, b:NaN]\n==\u003e[a:Bird of Prey, b:NaN]\n==\u003e[a:Plutonium Circus, b:NaN]\n==\u003e[a:Hustler White, b:NaN]\n==\u003e[a:Curtis's Charm, b:NaN]\n==\u003e[a:Three Lives and Only One Death, b:NaN]\n==\u003e[a:Hoogste tijd, b:NaN]\n==\u003e[a:Entertaining Angels: The Dorothy Day Story, b:NaN]\ncategory\nuser\nuser\nmovie\ncategory\nVertex\nmovie\nmovie\nmovie\nmovie\nmovie\nmoviemovie\nmovie\nVertex\n[a:Charm's Incidents, b:NaN]\n[a:Prerokbe Ognja, b:NaN]\n[a:Leopard Son, The, b:NaN]\n[a:Bird of Prey, b:NaN]\n...\n[a:Entertaining Angels, b:NaN]\nMap\u003cString,Double\u003e\nﬁlter map\nmovie\nname:Charm's Incidents\nmap\nreducing\nbarrier\nNaN\nVertex Edge Double\nmovie\nname:Charm's Incidents\nVertex String\nmap Charm's Incidentsa\nb\nmap\nmap\nInteger\n...\n\"For each movie, emit a map of its name and average rating.\nSort the maps in decreasing order by their average rating. Emit the ﬁrst 10 maps (i.e. top 10).\"\nﬂatMap\n ","gremlin\u003e g.V().hasLabel('movie').as('a','b').\nselect('a','b').\nby('name').\nby(coalesce(\ninE('rated').values('stars'),\nconstant(0)).mean()).\norder().by(select('b'),decr).\nlimit(10)\n==\u003e[a:Lured, b:5.0]\n==\u003e[a:One Little Indian, b:5.0]\n==\u003e[a:Bittersweet Motel, b:5.0]\n==\u003e[a:Gate of Heavenly Peace, The, b:5.0]\n==\u003e[a:Follow the Bitch, b:5.0]\n==\u003e[a:Schlafes Bruder (Brother of Sleep), b:5.0]\n==\u003e[a:Ulysses (Ulisse), b:5.0]\n==\u003e[a:Song of Freedom, b:5.0]\n==\u003e[a:Smashing Time, b:5.0]\n==\u003e[a:Baby, The, b:5.0]\n\"For each movie, get its name and mean rating (or 0 if no ratings). Order by average rating and emit top 10.\"\nuser\nuser\nmovie\ncategory\nVertex\nmovie\nmovie\nmovie\nmovie\nmoviemovie\nmovie\nVertex Map\u003cString,Double\u003e\nﬁlter map\nmovie\nname:Charm's Incidents\nmap map\nreducing\nbarrier\n0.0\nVertex Integer Double\nmovie\nname:Charm's Incidents\nVertex String\nmap Charm's Incidentsa\nb\nmap\n0\n[a:Lured, b:5.0]\n[a:One Little Indian, b:5.0]\n[a:Bittersweet Motel, b:5.0]\n[a:Gate of Heavenly Peace, b:5.0]\n...\n[a:Baby, The, b:5.0]\nMap\u003cString,Double\u003e\nmap\n[a:Charm's Incidents, b:NaN]\n[a:Prerokbe Ognja, b:NaN]\n[a:Leopard Son, The, b:NaN]\n[a:Bird of Prey, b:NaN]\n...\n[a:Entertaining Angels, b:NaN]\ncollecting\nbarrier\n ","gremlin\u003e g.V().hasLabel('movie').as('a','b').\nwhere(inE('rated').count().is(gt(10))).\nselect('a','b').\nby('name').\nby(inE('rated').values('stars').mean()).\norder().by(select('b'),decr).\nlimit(10)\n\"For each movie with at least 11 ratings, emit a map of its name and average rating.\nSort the maps in decreasing order by their average rating. Emit the ﬁrst 10 maps (i.e. top 10).\"\n ","gremlin\u003e g.V().hasLabel('movie').as('a','b').\nwhere(inE('rated').count().is(gt(10))).\nselect('a','b').\nby('name').\nby(inE('rated').values('stars').mean()).\norder().by(select('b'),decr).\nlimit(10)\n==\u003e[a:Sanjuro, b:4.608695652173913]\n==\u003e[a:Seven Samurai (The Magnificent Seven), b:4.560509554140127]\n==\u003e[a:Shawshank Redemption, The, b:4.554557700942973]\n==\u003e[a:Godfather, The, b:4.524966261808367]\n==\u003e[a:Close Shave, A, b:4.52054794520548]\n==\u003e[a:Usual Suspects, The, b:4.517106001121705]\n==\u003e[a:Schindler's List, b:4.510416666666667]\n==\u003e[a:Wrong Trousers, The, b:4.507936507936508]\n==\u003e[a:Sunset Blvd. (a.k.a. Sunset Boulevard), b:4.491489361702127]\n==\u003e[a:Raiders of the Lost Ark, b:4.47772]\n\"For each movie with at least 11 ratings, emit a map of its name and average rating.\nSort the maps in decreasing order by their average rating. Emit the ﬁrst 10 maps (i.e. top 10).\"\nmap\nmovie\nname:Sanjuro\nrated\nrated\nrated\n...\nrated\nmap\nreducing\nbarrier\n4.60\nVertex Edge Double\nmovie\nname:Sanjuro\nVertex String\nmap Sanjuroa\nb\nmap\nmap\nInteger\nuser\nuser\nmovie\ncategory\nVertex\nmovie\nmovie\nmovie\nmovie\nmoviemovie\nmovie\nVertex\nﬁlter\nmovie\nrated\nrated\nrated\n...\nrated\nreducing\nbarrier\nVertex Edge\nmap\nLong\n69\nname:Sanjuro\nﬁlter\nmovie\nmovie\nmovie\nmovie\nmovie\nVertex\n5\n4\n…\n5\n[[a:Sanjuro, b:4.60]\n[a:Seven Samurai, b:4.56]\n[a:Shawshank Redemption, b:4.55]\n[a:Godfather, The, b:4.52]\n...\n[a:Raiders of the Lost Ark, b:4.47]\n[…]\n[…]\n[…]\n[…]\n…\n[…]\nMap\u003cString,Double\u003e Map\u003cString,Double\u003e\nmap\ncollecting\nbarrier\nﬂatMap\nﬂatMap\n{\n{\n ","gremlin\u003e g.V().hasLabel('movie').\nwhere(inE('rated').count().is(gt(10))).\ntoString()\n==\u003e[GraphStep([],vertex), HasStep([~label.eq(movie)]),\nTraversalFilterStep([\nVertexStep(IN,[rated],edge),\nCountGlobalStep,\nIsStep(gt(10))])]\n\"What is the execution plan for the traversal prior to compiler optimizations being applied?\"\nV : G → V ∗\nhasLabelmovie : V ∗\n→ V ∗\nwhere : V ∗\n→\ninErated : V ∗\n→ E∗\ncount : E∗\n→ N\nisgt(10) : N → (N ∪ ∅)\n→ V ∗\n\"true\norfalse\"\n ","gremlin\u003e g.V().hasLabel('movie').\nwhere(inE('rated').count().is(gt(10))).\niterate().toString()\n==\u003e[TinkerGraphStep(vertex,[~label.eq(movie)]),\nTraversalFilterStep([\nVertexStep(IN,[rated],edge),\nRangeGlobalStep(0,11),\nCountGlobalStep,\nIsStep(gt(10))])]\n\"What is the execution plan for the traversal after compiler optimizations have been applied?\"\n* TinkerGraphStragegy: Access vendor-speciﬁc vertex partition by label.\n* RangeByIsCountStrategy: Only iterate 1 more than required count.\nwhere : V ∗\n→\ninErated : V ∗\n→ E∗\ncount : E∗\n→ N\nisgt(10) : N → (N ∪ ∅)\nlimit11 : E∗\n→ E∗\nVlabel=movie : G → V ∗\n→ V ∗\n\"true\norfalse\"\n ","gremlin\u003e g.getStrategies()\n==\u003eConjunctionStrategy\na.and().b =\u003e and(a,b)\na.or().b =\u003e or(a,b)\na.or().b.and().c =\u003e or(a,and(b,c))\na.and().b.or().c =\u003e or(and(a,b),c)\n==\u003eIncidentToAdjacentStrategy\na.outE().inV().b =\u003e a.out().b\n==\u003eAdjacentToIncidentStrategy\na.in().count().b =\u003e a.inE().count().b\na.where(out()).b =\u003e a.where(outE()).b\na.and(in(),out()).b =\u003e a.and(inE(),outE()).b\n==\u003eIdentityRemovalStrategy\na.identity().b =\u003e a.b\n==\u003eFilterRankingStrategy\na.order().dedup().b =\u003e a.dedup().order().b\na.and(c,d).has().b =\u003e a.has().and(c,d).b\na.simplePath().where().b =\u003e b.where().simplePath().a\n==\u003eMatchPredicateStrategy\na.match(c,d).where(e).b =\u003e a.match(c,d,e)\na.match(has(),c,d).b =\u003e a.has().match(c,d).b\n==\u003eRangeByIsCountStrategy\na.count().is(0) =\u003e a.limit(1).count().is(0)\n==\u003eTinkerGraphStepStrategy\nV.has().has().b =\u003e V[has,has].b\n==\u003eProfileStrategy\na.b.c.profile() =\u003e a.profile().b.profile().c.profile()\n==\u003eComputerVerificationStrategy\na.order.b =\u003e IllegalStateException\na.local(out().out()).b =\u003e IllegalStateException\n\"What compilation strategies are associated with the graph traversal source?\"\n ","gremlin\u003e g.V().has('movie','name','Die Hard').\ninE('rated').values('stars').mean()\n==\u003e4.121848739495798\n\"What is Die Hard's average rating?\"\n ","gremlin\u003e g.V().has('movie','name','Die Hard').\ninE('rated').values('stars').mean()\n==\u003e4.121848739495798\n\"What is Die Hard's average rating?\"\nmovie\nmovie\nmovie\nVertex\nmovie\nVertex\nﬁlter\nname:Die Hard\nﬂatMap\nrated\nrated\nrated\n...\nrated\nEdge\nmap\n3\n5\n5\n…\n4\nInteger\nmap\nDouble\n4.1218\nreducing\nbarrier\nV : G → V ∗\nhasLabelmovie : V ∗\n→ V ∗\nhasname=Die Hard : V ∗\n→ V ∗\ninErated : V ∗\n→ E∗ mean : N∗\n→ R\nvaluesstars : E∗\n→ N∗\nuser\nuser\nmovie\nuser\nVertex\nﬁlter\n{\n\"one-to-[one-or-none]\"\n\"one-to-[one-or-none]\"\n\"one-to-many\"\n\"one-to-one\"\n\"many-to-one\"\n ","gremlin\u003e g.V().has('movie','name','Die Hard').as('a').\ninE('rated').has('stars',5).outV().\nwhere(out('occupation').has('name','programmer')).\noutE('rated').has('stars',5).inV().\nwhere(neq('a')).\ngroupCount().by('name').\norder(local).by(valueDecr).\nlimit(local,10).\nunfold() // so its not printed on a single line\n\"Which programmers like Die Hard and what other movies do they like?\nGroup and count the movies by their name. Sort the group count map in decreasing order by the count.\nClip the map to the top 10 entries and stream out the map's entries (for display purposes).\"\n ","gremlin\u003e g.V().has('movie','name','Die Hard').as('a').\ninE('rated').has('stars',5).outV().\nwhere(out('occupation').has('name','programmer')).\noutE('rated').has('stars',5).inV().\nwhere(neq('a')).\ngroupCount().by('name').\norder(local).by(valueDecr).\nlimit(local,10).\nunfold() // so its not printed on a single line\n\"Which programmers like Die Hard and what other movies do they like?\nGroup and count the movies by their name. Sort the group count map in decreasing order by the count.\nClip the map to the top 10 entries and stream out the map's entries (for display purposes).\"\nuser\nuser\nmovie\nuser\nVertex\nmovie\nVertex\nﬁlter ﬁlter\nname:Die Hard\nﬂatMap\nrated\nrated\nrated\n...\nrated\nEdge\nﬁlter\nrated\n...\nrated\nEdge\nmap\nVertex\nuser\nuser\nuser\nuseruser\nuser\nVertex Vertex\noccupationﬂatMap\nVertex\nﬁlter\nrated\nrated\nrated\n...\nrated\nEdge\nﬁlter\nrated\n...\nrated\nEdge\nmap\nVertex\nmovie\nmovie\nmoviemovie\nmovie\nVertex\nVertex\nuser\nuser\nuser\nﬂatMap ﬁlter movie\nVertex\nﬁlter\nVertex\nmovie\nmovie\nmovie\nmap\nreducing\nbarrier\n[\nAliens=105,\nBraveheart=24,\n…\nPulp Fiction=19\n]\nMap\u003cString,Long\u003e\nmap\ncollecting\nbarrier\n[\nRaider of the Lost Ark=36,\nStar Wars: Episode V=24,\nStar Wars: Episode IV=34\n…\nAirplane II: The Sequel=1\n]\nMap\u003cString,Long\u003e\n[\nRaider of the Lost Ark=36,\nStar Wars: Episode V=24,\nStar Wars: Episode IV=34\n…\nAlien=22\n]\nMap\u003cString,Long\u003e\nmap\noccupation\nprogrammer\nnot Die Hard\n ","gremlin\u003e g.V().has('movie','name','Die Hard').as('a').\ninE('rated').has('stars',5).outV().\nwhere(out('occupation').has('name','programmer')).\noutE('rated').has('stars',5).inV().\nwhere(neq('a')).\ngroupCount().by('name').\norder(local).by(valueDecr).\nlimit(local,10).\nunfold() // so its not printed on a single line\n==\u003eRaiders of the Lost Ark=36\n==\u003eStar Wars: Episode V - The Empire Strikes Back=36\n==\u003eStar Wars: Episode IV - A New Hope=34\n==\u003eMatrix, The=32\n==\u003eTerminator, The=29\n==\u003eStar Wars: Episode VI - Return of the Jedi=26\n==\u003eSixth Sense, The=26\n==\u003eBraveheart=24\n==\u003eAliens=23\n==\u003eAlien=22\ngremlin\u003e\n\"Which programmers like Die Hard and what other movies do they like?\nGroup and count the movies by their name. Sort the group count map in decreasing order by the count.\nClip the map to the top 10 entries and stream out the map's entries (for display purposes).\"\n ","gremlin\u003e g.V().\nmatch(\n__.as('a').hasLabel('movie'),\n__.as('a').out('category').has('name','Action'),\n__.as('a').has('year',between(1980,1990)),\n__.as('a').inE('rated').as('b'),\n__.as('b').has('stars',5),\n__.as('b').outV().as('c'),\n__.as('c').out('occupation').has('name','programmer'),\n__.as('c').has('age',between(30,40))).\nselect('a').groupCount().by('name').\norder(local).by(valueDecr).\nlimit(local,10).\nunfold() // so its not printed on a single line\n\"What 80's action movies do 30-something programmers like?\nGroup count the movies by their name and sort the group count map in decreasing order by value.\nClip the map to the top 10 and emit the map entries.\"\n ","\"What 80's action movies do 30-something programmers like?\nGroup count the movies by their name and sort the group count map in decreasing order by value.\nClip the map to the top 10 and emit the map entries.\"\ngremlin\u003e g.V().\nmatch(\n__.as('a').hasLabel('movie'),\n__.as('a').out('category').has('name','Action'),\n__.as('a').has('year',between(1980,1990)),\n__.as('a').inE('rated').as('b'),\n__.as('b').has('stars',5),\n__.as('b').outV().as('c'),\n__.as('c').out('occupation').has('name','programmer'),\n__.as('c').has('age',between(30,40))).\nselect('a').groupCount().by('name').\norder(local).by(valueDecr).\nlimit(local,10).\nunfold() // so its not printed on a single line\n==\u003eRaiders of the Lost Ark=26\n==\u003eStar Wars: Episode V - The Empire Strikes Back=26\n==\u003eTerminator, The=23\n==\u003eStar Wars: Episode VI - Return of the Jedi=22\n==\u003ePrincess Bride, The=19\n==\u003eAliens=18\n==\u003eBoat, The (Das Boot)=11\n==\u003eIndiana Jones and the Last Crusade=11\n==\u003eStar Trek: The Wrath of Khan=10\n==\u003eAbyss, The=9\ngremlin\u003e\n ","MatchStep\nGraphTraversal.match(Traversal... traversalPatterns)\nx.match(\na...b\na...c\nc...\nor(\na...c\na...b\n)\nc.repeat(...).b\nnot(c...a)\nb...count().e\nc...count().e\n).dedup(a,b).y\na,b,c,e : once a variable is set, it must hold equal for all patterns\nc... : \"predicate patterns\" simply check for the existence of a result\nor()/and() : nested conjunctive patterns supported\nrepeat(...) : recursive patterns supported\nnot(...) : not'ing of patterns supported\ncount() : barrier patterns supported\ndedup(a,b) : internal de-duplication of variable values supported\nx.match().y : possible to go from imperative to declarative, etc.\nPlug and Play MatchAlgorithms\nGreedyMatchAlgorithm :\ntry each pattern in the order provided by the user\nCountMatchAlgorithm :\ncontinually re-sort patterns by the cardinality of their set reductions\n ","// CountMatchAlgorithm (default)\ngremlin\u003e clockWithResult(50){\ng.V().match(\n__.as('a').out('rated').as('b'),\n__.as('a').out('occupation').has('name','farmer')).\nselect('a','b').count().next()}\n==\u003e66.31955294 // time in milliseconds\n==\u003e2706 // number of results\n// GreedyMatchAlgorithm\ngremlin\u003e g = graph.traversal(GraphTraversalSource.build().\nwith(MatchAlgorithmStrategy.build().\nalgorithm(MatchStep.GreedyMatchAlgorithm).create()))\n==\u003egraphtraversalsource[tinkergraph[vertices:9962 edges:1012657], standard]\ngremlin\u003e clockWithResult(50){\ng.V().match(\n__.as('a').out('rated').as('b'),\n__.as('a').out('occupation').has('name','farmer')).\nselect('a','b').count().next()}\n==\u003e1902.6290871599997 // time in milliseconds\n==\u003e2706 // number of results\n\"Which movies did each farmer rate? -- benchmark CountMatchAlgorithm vs. GreedyMatchAlgorithm.\"\nfarmermoviesusers\n1000209 2706\nfarmer moviesusers\n17 2706\n ","gremlin\u003e g.V().hasLabel('movie').\nwhere(inE('rated').count().is(gt(10))).\ngroup().\nby{((int)(it.value('year') / 10)) * 10}.\nby().\nby(unfold().order().\nby(inE('rated').values('stars').mean(),decr).\nvalues('name').\nlimit(1)).\norder(local).by(keyIncr).\nunfold() // so its not printed on a single line\n\"What is the most liked movie in each decade?\"\n ","gremlin\u003e g.V().hasLabel('movie').\nwhere(inE('rated').count().is(gt(10))).\ngroup().\nby{((int)(it.value('year') / 10)) * 10}.\nby().\nby(unfold().order().\nby(inE('rated').values('stars').mean(),decr).\nvalues('name').\nlimit(1)).\norder(local).by(keyIncr).\nunfold() // so its not printed on a single line\n\"What is the most liked movie in each decade?\"\nλ\nλ\nNearly every step that takes a traversal argument can also take a lambda.\nIt is recommended that users do not use lambdas as they are not subject to traversal strategy (i.e. compiler) optimization.\nHowever, they are useful when no provided step yields the desired computation.\n ","gremlin\u003e g.V().hasLabel('movie').\nwhere(inE('rated').count().is(gt(10))).\ngroup().\nby{((int)(it.value('year') / 10)) * 10}.\nby().\nby(unfold().order().\nby(inE('rated').values('stars').mean(),decr).\nvalues('name').\nlimit(1)).\norder(local).by(keyIncr).\nunfold() // so its not printed on a single line\n==\u003e1910=Daddy Long Legs\n==\u003e1920=General, The\n==\u003e1930=City Lights\n==\u003e1940=Third Man, The\n==\u003e1950=Seven Samurai (The Magnificent Seven)\n==\u003e1960=Sanjuro\n==\u003e1970=Godfather, The\n==\u003e1980=Raiders of the Lost Ark\n==\u003e1990=Shawshank Redemption, The\n==\u003e2000=Almost Famous\ngremlin\u003e\n\"What is the most liked movie in each decade?\"\n ","gremlin\u003e graph = HadoopGraph.open('conf/hadoop/movie-lens.properties')\n==\u003ehadoopgraph[gryoinputformat-\u003egryooutputformat]\ngremlin\u003e g = graph.traversal(computer(SparkGraphComputer))\n==\u003egraphtraversalsource\n[hadoopgraph[gryoinputformat-\u003egryooutputformat], sparkgraphcomputer]\ngremlin\u003e\n\"Which movies are most central in the implicit 5-stars graph?\"\n ","gremlin\u003e graph = HadoopGraph.open('conf/hadoop/movie-lens.properties')\n==\u003ehadoopgraph[gryoinputformat-\u003egryooutputformat]\ngremlin\u003e g = graph.traversal(computer(SparkGraphComputer))\n==\u003egraphtraversalsource\n[hadoopgraph[gryoinputformat-\u003egryooutputformat], sparkgraphcomputer]\ngremlin\u003e g.V().repeat(outE('rated').has('stars', 5).inV().\ngroupCount('m').by('name').\ninE('rated').has('stars', 5).outV()).\ntimes(4).cap('m')\n\"Which movies are most central in the implicit 5-stars graph?\"\nuser movie user\nratedrated\nm\n4x\ncap('m')\nrepeat(…).times(4)\ng.V()\nstars=5 stars=5\n ","gremlin\u003e graph = HadoopGraph.open('conf/hadoop/movie-lens.properties')\n==\u003ehadoopgraph[gryoinputformat-\u003egryooutputformat]\ngremlin\u003e g = graph.traversal(computer(SparkGraphComputer))\n==\u003egraphtraversalsource\n[hadoopgraph[gryoinputformat-\u003egryooutputformat], sparkgraphcomputer]\ngremlin\u003e g.V().repeat(outE('rated').has('stars', 5).inV().\ngroupCount('m').by('name').\ninE('rated').has('stars', 5).outV()).\ntimes(4).cap('m')\n==\u003eFantasia 2000=2676505178171564\n==\u003ePale Rider=1369969000295362\n==\u003eCrucible, The=401712993698149\n==\u003eAbout Adam=37981148456999\n==\u003eAkira=3659939409345918\n...\ngremlin\u003e\n\"Which movies are most central in the implicit 5-stars graph?\"\n ","gremlin\u003e graph = HadoopGraph.open('conf/hadoop/movie-lens.properties')\n==\u003ehadoopgraph[gryoinputformat-\u003egryooutputformat]\ngremlin\u003e g = graph.traversal(computer(SparkGraphComputer))\n==\u003egraphtraversalsource\n[hadoopgraph[gryoinputformat-\u003egryooutputformat], sparkgraphcomputer]\ngremlin\u003e g.V().repeat(outE('rated').has('stars', 5).inV().\ngroupCount('m').by('name').\ninE('rated').has('stars', 5).outV()).\ntimes(4).cap('m')\n==\u003eFantasia 2000=2676505178171564\n==\u003ePale Rider=1369969000295362\n==\u003eCrucible, The=401712993698149\n==\u003eAbout Adam=37981148456999\n==\u003eAkira=3659939409345918\n...\ngremlin\u003e hdfs.ls('output/m')\n==\u003erw-r--r-- daniel supergroup 0 _SUCCESS\n==\u003erw-r--r-- daniel supergroup 245314 part-r-00000\ngremlin\u003e hdfs.head('output/m', ObjectWritable).sort {-it.value}.take(10)\n==\u003eStar Wars: Episode IV - A New Hope 35405394353105332\n==\u003eAmerican Beauty 31943228282020585\n==\u003eRaiders of the Lost Ark 31224779793238499\n==\u003eStar Wars: Episode V - The Empire Strikes Back 30434677119726223\n==\u003eGodfather, The 30258518523013057\n==\u003eShawshank Redemption, The 28297717387901031\n==\u003eSchindler's List 27539336654199309\n==\u003eSilence of the Lambs, The 26736276376806173\n==\u003eFargo 26531050311325270\n==\u003eMatrix, The 26395118239203191\n\"Which movies are most central in the implicit 5-stars graph?\"\n ","gremlin\u003e :plugin use tinkerpop.gephi\n==\u003etinkerpop.gephi activated\ngremlin\u003e :remote connect tinkerpop.gephi\n==\u003eConnection to Gephi - http://localhost:8080/workspace0 with stepDelay:1000,\nstartRGBColor:[0.0, 1.0, 0.5], colorToFade:g, colorFadeRate:0.7, startSize:\n20.0,sizeDecrementRate:0.33\ngremlin\u003e\n ","gremlin\u003e :plugin use tinkerpop.gephi\n==\u003etinkerpop.gephi activated\ngremlin\u003e :remote connect tinkerpop.gephi\n==\u003eConnection to Gephi - http://localhost:8080/workspace0 with stepDelay:1000,\nstartRGBColor:[0.0, 1.0, 0.5], colorToFade:g, colorFadeRate:0.7, startSize:\n20.0,sizeDecrementRate:0.33\ngremlin\u003e :\u003e g.V().hasLabel('user').\norder().\nby(outE('rated').count(), decr).limit(10).as('a').\nlocal(outE('rated').order().\nby('stars', decr). // first by stars\nby(inV().inE('rated').count(), decr). // then by ratings\nlimit(10)).\nsubgraph('sg').inV().outE('category').\nsubgraph('sg').select('a').outE('occupation').\nsubgraph('sg').cap('sg').next()\n==\u003etinkergraph[vertices:82 edges:233]\ngremlin\u003e\n\"Which users rated the most movies?\nFor each user, display their 10 favorite movies, the categories of those movies, and their occupation.\n\"moviebuffs\"\n ","","Thanks for listening…\n "],"twitterShareUrl":"https://twitter.com/intent/tweet?via=SlideShare\u0026text=The+Gremlin+Graph+Traversal+Language+by+%40twarko+%23graphdatabases+%23graphdb+https%3A%2F%2Fwww.slideshare.net%2Fslideshow%2Fthe-gremlin-traversal-language%2F51792873","type":"presentation","viewStats":{"views":20197,"viewsFromEmbeds":1361,"topEmbeds":[]},"recommendationsByLocation":{"rightRail":[{"algorithmId":"5","displayTitle":"Gremlin's Graph Traversal 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The graph representation is a distributed adjacency list, whereby a vertex and its incident edges are co-located on the same machine. Querying a Faunus graph is possible with a MapReduce-variant of the Gremlin graph traversal language. A Gremlin expression compiles down to a series of MapReduce-steps that are sequence optimized and then executed by Hadoop. Results are stored as transformations to the input graph (graph derivations) or computational side-effects such as aggregates (graph statistics). Beyond querying, a collection of input/output formats are supported which enable Faunus to load/store graphs in the distributed graph database Titan, various graph formats stored in HDFS, and via arbitrary user-defined functions. 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Those who succumb to this data processing pattern euphorically suffer from graph pathology.\n\nThis is a case study of the Graph Addict.","tags":["gremlin","graphdb","graph"],"url":"https://www.slideshare.net/slideshow/the-pathology-of-graph-databases/8422170","userLogin":"slidarko","userName":"Marko Rodriguez","viewCount":6356},{"algorithmId":"","displayTitle":"The Path-o-Logical Gremlin","isSavedByCurrentUser":false,"pageCount":47,"score":0,"slideshowId":"7640601","sourceName":"MORE_FROM_USER","strippedTitle":"the-pathological-gremlin","thumbnail":"https://cdn.slidesharecdn.com/ss_thumbnails/gremlin-gdm2011-110415101933-phpapp02-thumbnail.jpg?width=600\u0026height=600\u0026fit=bounds","description":"Gremlin is a graph traversal language that connects to various graph databases/frameworks.\r\n\r\n * Neo4j [http://neo4j.org]\r\n * OrientDB [http://orientechnologies.com]\r\n * DEX [http://www.sparsity-technologies.com/dex]\r\n * OpenRDF Sail [http://openrdf.org]\r\n * JUNG [http://jung.sourceforge.net]\r\n\r\nThis lecture addresses the state of Gremlin as of the 0.9 (April 16, 2011).","tags":["gremlin","graphdb","nosql"],"url":"https://www.slideshare.net/slideshow/the-pathological-gremlin/7640601","userLogin":"slidarko","userName":"Marko Rodriguez","viewCount":3283},{"algorithmId":"","displayTitle":"Memoirs of a Graph Addict: Despair to Redemption","isSavedByCurrentUser":false,"pageCount":129,"score":0,"slideshowId":"6490042","sourceName":"MORE_FROM_USER","strippedTitle":"memoirs-of-a-graph-addict-despair-to-redemption","thumbnail":"https://cdn.slidesharecdn.com/ss_thumbnails/whirlwind-tour-2011-110108171503-phpapp02-thumbnail.jpg?width=600\u0026height=600\u0026fit=bounds","description":"This document summarizes a lecture about graph databases and graph structures. It discusses graph databases as an alternative to relational databases that allows for direct linking of objects without joins. It then describes the speaker's 10 years of experience working with graph structures and applications. Finally, it outlines the TinkerPop product suite for working with graph databases.","tags":["graphs","rdf"],"url":"https://www.slideshare.net/slideshow/memoirs-of-a-graph-addict-despair-to-redemption/6490042","userLogin":"slidarko","userName":"Marko Rodriguez","viewCount":7978},{"algorithmId":"","displayTitle":"Graph Databases: Trends in the Web of Data","isSavedByCurrentUser":false,"pageCount":129,"score":0,"slideshowId":"5228110","sourceName":"MORE_FROM_USER","strippedTitle":"graph-databases-trends-in-the-web-of-data","thumbnail":"https://cdn.slidesharecdn.com/ss_thumbnails/krdb-graphdb-2010-100918034109-phpapp01-thumbnail.jpg?width=600\u0026height=600\u0026fit=bounds","description":" Aanswers · Aanswers ◦ n(I) π\n\netc...15\n 15\n I is the identity matrix.\n\fThe Multi-Relational Path Algebra:\n\n- Allows single-relational algorithms to be applied to multi-relational graphs\n\n- Provides a universal framework for defining paths through a multi-relational\n graph\n\n- Enables the computation of multiple primary eigenvectors, each\n corresponding to a different path definition\n\n- In effect, provides multiple definitions of centrality for a multi-relational\n network\n\n- Is Turing complete—any computable path can be expressed\n\n- Is a general framework—applies to any multi-relational data model","tags":["graphs","graph databases","rdf"],"url":"https://www.slideshare.net/slideshow/graph-databases-trends-in-the-web-of-data/5228110","userLogin":"slidarko","userName":"Marko Rodriguez","viewCount":58218},{"algorithmId":"","displayTitle":"Problem-Solving using Graph Traversals: Searching, Scoring, Ranking, and Reco...","isSavedByCurrentUser":false,"pageCount":127,"score":0,"slideshowId":"4833581","sourceName":"MORE_FROM_USER","strippedTitle":"problemsolving-using-graph-traversals-searching-scoring-ranking-and-recommendation","thumbnail":"https://cdn.slidesharecdn.com/ss_thumbnails/atti-ps-graphs-100725105805-phpapp01-thumbnail.jpg?width=600\u0026height=600\u0026fit=bounds","description":"A graph is a data structure that links a set of vertices by a set of edges. Modern graph databases support multi-relational graph structures, where there exist different types of vertices (e.g. people, places, items) and different types of edges (e.g. friend, lives at, purchased). By means of index-free adjacency, graph databases are optimized for graph traversals and are interacted with through a graph traversal engine. A graph traversal is defined as an abstract path whose instance is realized on a graph dataset. Graph databases and traversals can be used for searching, scoring, ranking, and in concert, recommendation. This presentation will explore graph structures, algorithms, traversal algebras, graph-related software suites, and a host of examples demonstrating how to solve real-world problems, in real-time, with graphs. This is a whirlwind tour of the theory and application of graphs.","tags":["ethics","graphs","multi-relational"],"url":"https://www.slideshare.net/slideshow/problemsolving-using-graph-traversals-searching-scoring-ranking-and-recommendation/4833581","userLogin":"slidarko","userName":"Marko Rodriguez","viewCount":67026},{"algorithmId":"","displayTitle":"A Perspective on Graph Theory and Network Science","isSavedByCurrentUser":false,"pageCount":33,"score":0,"slideshowId":"4685485","sourceName":"MORE_FROM_USER","strippedTitle":"a-perspective-on-graph-theory-and-network-science","thumbnail":"https://cdn.slidesharecdn.com/ss_thumbnails/network-graph-sf2010-100705130759-phpapp02-thumbnail.jpg?width=600\u0026height=600\u0026fit=bounds","description":"The graph/network domain has been driven by the creativity of numerous individuals from disparate areas of the academic and the commercial sector. Examples of contributing academic disciplines include mathematics, physics, sociology, and computer science. Given the interdisciplinary nature of the domain, it is difficult for any single individual to objectively realize and speak about the space as a whole. Any presentation of the ideas is ultimately biased by the formal training and expertise of the individual. For this reason, I will simply present on the domain from my perspective---from my personal experiences. More specifically, from my perspective biased by cognitive and computer science.\r\n\r\nThis is an autobiographical lecture on my life (so far) with graphs/networks.","tags":["ethics","graphs","digital libraries"],"url":"https://www.slideshare.net/slideshow/a-perspective-on-graph-theory-and-network-science/4685485","userLogin":"slidarko","userName":"Marko Rodriguez","viewCount":4726},{"algorithmId":"","displayTitle":"The Graph Traversal Programming Pattern","isSavedByCurrentUser":false,"pageCount":76,"score":0,"slideshowId":"4618573","sourceName":"MORE_FROM_USER","strippedTitle":"graph-windycitydb2010","thumbnail":"https://cdn.slidesharecdn.com/ss_thumbnails/graph-windycitydb-2010-100625223624-phpapp01-thumbnail.jpg?width=600\u0026height=600\u0026fit=bounds","description":"A graph is a structure composed of a set of vertices (i.e.~nodes, dots) connected to one another by a set of edges (i.e.~links, lines). The concept of a graph has been around since the late 19th century, however, only in recent decades has there been a strong resurgence in the development of both graph theories and applications. In applied computing, since the late 1960s, the interlinked table structure of the relational database has been the predominant information storage and retrieval paradigm. With the growth of graph/network-based data and the need to efficiently process such data, new data management systems have been developed. In contrast to the index-intensive, set-theoretic operations of relational databases, graph databases make use of index-free traversals. This presentation will discuss the graph traversal programming pattern and its application to problem-solving with graph databases.","tags":["databases","graphs"],"url":"https://www.slideshare.net/slideshow/graph-windycitydb2010/4618573","userLogin":"slidarko","userName":"Marko Rodriguez","viewCount":56716},{"algorithmId":"","displayTitle":"The Network Data Structure in Computing","isSavedByCurrentUser":false,"pageCount":44,"score":0,"slideshowId":"3884767","sourceName":"MORE_FROM_USER","strippedTitle":"the-network-data-structure-in-computing","thumbnail":"https://cdn.slidesharecdn.com/ss_thumbnails/super-computer-100428102426-phpapp01-thumbnail.jpg?width=600\u0026height=600\u0026fit=bounds","description":"The document discusses network data structures and semantic networks. It provides examples of undirected, directed, and semantic networks. It describes how PageRank can be applied to semantic networks using grammar-based random walkers that follow the relationships between nodes defined in an ontology. It also lists related publications by the author on modeling systems and computations as semantic networks.","tags":["graphs"],"url":"https://www.slideshare.net/slideshow/the-network-data-structure-in-computing/3884767","userLogin":"slidarko","userName":"Marko Rodriguez","viewCount":8636},{"algorithmId":"","displayTitle":"A Model of the Scholarly Community","isSavedByCurrentUser":false,"pageCount":22,"score":0,"slideshowId":"3884646","sourceName":"MORE_FROM_USER","strippedTitle":"a-model-of-the-scholarly-community","thumbnail":"https://cdn.slidesharecdn.com/ss_thumbnails/sfi-talk-100428101606-phpapp02-thumbnail.jpg?width=600\u0026height=600\u0026fit=bounds","description":"The document summarizes a two-year project to develop an ontology and data model to represent scholarly works and their usage. It will analyze bibliographic data and usage data from sources like journals, papers, and online usage logs to develop metrics to quantify the scholarly community. The first year will focus on developing the ontology and algorithms while the second year will analyze the results and report findings.","tags":["graphs","digital libraries"],"url":"https://www.slideshare.net/slideshow/a-model-of-the-scholarly-community/3884646","userLogin":"slidarko","userName":"Marko Rodriguez","viewCount":1285},{"algorithmId":"","displayTitle":"General-Purpose, Internet-Scale Distributed Computing with Linked Process","isSavedByCurrentUser":false,"pageCount":57,"score":0,"slideshowId":"3880087","sourceName":"MORE_FROM_USER","strippedTitle":"generalpurpose-internetscale-distributed-computing-with-linked-process-3880087","thumbnail":"https://cdn.slidesharecdn.com/ss_thumbnails/cnls-linkedprocess2009-100428013149-phpapp01-thumbnail.jpg?width=600\u0026height=600\u0026fit=bounds","description":"There are many distributed computing protocols in existence today. Some serve as a solution for scientific computing, some as a middleware solution to large- scale systems engineering, and others as an “easy-to-use” service solution on the Web. What most of these protocols have in common is that they require a strong “handshake” between the machines utilizing each other’s resources. This coupling has rendered many distributed protocols to only be useful for a collection of machines owned and operated by a single organization (e.g. MPI/PVM computing) or for use by foreign machines with a very specific use case (e.g. RPC/Web Services computing). The former allows for general-purpose distributed computing and the latter allows for Internet-scale distributed computing. What if both types of functionality were to be merged? What does a general-purpose, Internet-scale distributed computing protocol look like? Linked Process [ http://linkedprocess.org ]","tags":["distributed computing","xmpp"],"url":"https://www.slideshare.net/slideshow/generalpurpose-internetscale-distributed-computing-with-linked-process-3880087/3880087","userLogin":"slidarko","userName":"Marko Rodriguez","viewCount":2058},{"algorithmId":"","displayTitle":"Collective Decision Making Systems: From the Ideal State to Human Eudaimonia","isSavedByCurrentUser":false,"pageCount":17,"score":0,"slideshowId":"3880075","sourceName":"MORE_FROM_USER","strippedTitle":"collective-decision-making-systems-from-the-ideal-state-to-human-eudaimonia-3880075","thumbnail":"https://cdn.slidesharecdn.com/ss_thumbnails/cnls-cdms-review-100428013055-phpapp01-thumbnail.jpg?width=600\u0026height=600\u0026fit=bounds","description":"Few scholastic disciplines have within them an explicit ideal beyond the production of knowledge. With computer science and engineering, the implicit ideal is to ensure better living through circuitry. Personally, my motivation is driven by the sense that social algorithms will lead to a greater human experience.\n","tags":["computational eudaemonics","decision making"],"url":"https://www.slideshare.net/slideshow/collective-decision-making-systems-from-the-ideal-state-to-human-eudaimonia-3880075/3880075","userLogin":"slidarko","userName":"Marko Rodriguez","viewCount":1673},{"algorithmId":"","displayTitle":"Distributed Graph Databases and the Emerging Web of Data","isSavedByCurrentUser":false,"pageCount":79,"score":0,"slideshowId":"3880066","sourceName":"MORE_FROM_USER","strippedTitle":"distributed-graph-databases-and-the-emerging-web-of-data","thumbnail":"https://cdn.slidesharecdn.com/ss_thumbnails/unm-colloquium2009-100428011205-phpapp02-thumbnail.jpg?width=600\u0026height=600\u0026fit=bounds","description":"The World Wide Web is the defacto medium for publicly exposing a corpus of interrelated documents. In its current form, the World Wide Web is the Web of Documents. The next generation of the World Wide Web will support the Web of Data. The Web of Data utilizes the same Uniform Resource Identifier (URI) address space as the Web of Documents, but instead of a exposing a graph of documents, the Web of Data exposes a graph of data. Given that the URI address space of the Web is distributed and infinite, the Web of Data provides a single unified space by which the worlds data can be publicly exposed and interrelated. The Web of Data is supported by both graph databases (which structure the data) and distributed computing mechanism (which process the data). This presentation will discuss the Web of Data, graph databases, and models of computing in this emerging space.","tags":["databases","graphs","rdf"],"url":"https://www.slideshare.net/slideshow/distributed-graph-databases-and-the-emerging-web-of-data/3880066","userLogin":"slidarko","userName":"Marko Rodriguez","viewCount":2598},{"algorithmId":"","displayTitle":"An Overview of Data Management Paradigms: Relational, Document, and Graph","isSavedByCurrentUser":false,"pageCount":37,"score":0,"slideshowId":"3880059","sourceName":"MORE_FROM_USER","strippedTitle":"an-overview-of-data-management-paradigms-relational-document-and-graph-3880059","thumbnail":"https://cdn.slidesharecdn.com/ss_thumbnails/datamanagement-2010-100428010914-phpapp02-thumbnail.jpg?width=600\u0026height=600\u0026fit=bounds","description":" Here are the key steps:\n\n1. Create vertex for each band member with properties like name, etc\n2. Create vertex for each song with properties like title\n3. Create edge between band member and song to indicate they performed it\n4. Add properties to edges like number of performances\n\nThis models the relationships between band members and songs they played in a graph structure optimized for traversal.","tags":["document stores","graphs","relational databases"],"url":"https://www.slideshare.net/slidarko/an-overview-of-data-management-paradigms-relational-document-and-graph-3880059","userLogin":"slidarko","userName":"Marko Rodriguez","viewCount":8090},{"algorithmId":"","displayTitle":"Graph Databases and the Future of Large-Scale Knowledge Management","isSavedByCurrentUser":false,"pageCount":38,"score":0,"slideshowId":"3880049","sourceName":"MORE_FROM_USER","strippedTitle":"graph-databases-and-the-future-of-largescale-knowledge-management","thumbnail":"https://cdn.slidesharecdn.com/ss_thumbnails/risk-symposium2009-100428010546-phpapp02-thumbnail.jpg?width=600\u0026height=600\u0026fit=bounds","description":"The document discusses how modern graph databases can store billions of relationships and are practical for large-scale knowledge management. It also describes how graph databases can be interlinked using Linked Data standards to create a giant global knowledge structure on the web. The talk will cover graph databases, their data model, querying mechanisms, and benefits for modeling and analysis compared to relational databases.","tags":["databases","graphs","rdf"],"url":"https://www.slideshare.net/slidarko/graph-databases-and-the-future-of-largescale-knowledge-management","userLogin":"slidarko","userName":"Marko Rodriguez","viewCount":3725},{"algorithmId":"","displayTitle":"Automatic Metadata Generation using Associative Networks","isSavedByCurrentUser":false,"pageCount":28,"score":0,"slideshowId":"3880025","sourceName":"MORE_FROM_USER","strippedTitle":"automatic-metadata-generation-using-associative-networks","thumbnail":"https://cdn.slidesharecdn.com/ss_thumbnails/metadata-generation-100428010008-phpapp02-thumbnail.jpg?width=600\u0026height=600\u0026fit=bounds","description":"In spite of its tremendous value, metadata is generally sparse and incomplete, thereby hampering the effectiveness of digital information services. Many of the existing mechanisms for the automated creation of metadata rely primarily on content analysis which can be costly and inefficient. The automatic metadata generation system proposed in this article leverages resource relationships generated from existing metadata as a medium for propagation from metadata-rich to metadata-poor resources. Because of its independence from content analysis, it can be applied to a wide variety of resource media types and is shown to be computationally inexpensive. The proposed method operates through two distinct phases. Occurrence and co-occurrence algorithms first generate an associative network of repository resources leveraging existing repository metadata. Second, using the associative network as a substrate, metadata associated with metadata-rich resources is propagated to metadata-poor resources by means of a discrete-form spreading activation algorithm. This article discusses the general framework for building associative networks, an algorithm for disseminating metadata through such networks, and the results of an experiment and validation of the proposed method using a standard bibliographic dataset. ","tags":["graphs","digital libraries"],"url":"https://www.slideshare.net/slideshow/automatic-metadata-generation-using-associative-networks/3880025","userLogin":"slidarko","userName":"Marko Rodriguez","viewCount":1226}],"featured":null,"latest":[{"algorithmId":"4","displayTitle":"How John started to like TDD (instead of hating it) - TED talk","isSavedByCurrentUser":false,"pageCount":44,"score":0,"slideshowId":"276213669","sourceName":"LATEST","strippedTitle":"how-john-started-to-like-tdd-instead-of-hating-it-ted-talk","thumbnail":"https://cdn.slidesharecdn.com/ss_thumbnails/howjohnstartedtoliketdd-talentarena-250303073311-8859d82f-thumbnail.jpg?width=600\u0026height=600\u0026fit=bounds","description":"John, a typical developer, used to dread writing tests, finding them boring and unnecessary. Test Driven Development (TDD)? Even worse—he couldn’t see how it worked outside of basic exercises. But something clicked. Through his journey, John discovered the magic of writing tests before the production code: fewer bugs, quicker feedback, and cleaner code. Now, he’s hooked and won’t code any other way. This is the story of how TDD turned a skeptic into a believer. 😅\r\n\r\nPS: Think of John as a random person, as if he was even the speaker of this talk 😉!\r\n\r\n---\r\nPresentation shared at Talent Arena '25\r\n\r\nFeedback form:\r\nhttp://tiny.cc/how-john-tdd-feedback","tags":["technology","software","software development"],"url":"https://www.slideshare.net/slideshow/how-john-started-to-like-tdd-instead-of-hating-it-ted-talk/276213669","userLogin":"icougil","userName":"Nacho Cougil","viewCount":60},{"algorithmId":"4","displayTitle":"Advance Website Helpdesk Customer Support Ticket Management Odoo","isSavedByCurrentUser":false,"pageCount":29,"score":0,"slideshowId":"276219588","sourceName":"LATEST","strippedTitle":"advance-website-helpdesk-customer-support-ticket-management-odoo","thumbnail":"https://cdn.slidesharecdn.com/ss_thumbnails/adv-250303110550-98dad014-thumbnail.jpg?width=600\u0026height=600\u0026fit=bounds","description":"Effortlessly manage tickets via email, admin, or website forms, and take advantage of features like merging, reopening, and assigning by type. Create orders and invoices directly from tickets, send updates via WhatsApp, and track progress with timesheets—everything you need, all in one place.\n\n✅Get the App here : https://bit.ly/4fJjGm8\n\n👉Key features of advanced website helpdesk odoo module :\n\n⏺Dashboard For Tickets Tracking\n⏺Helpdesk Tickets List\n⏺Helpdesk Tickets Filter\n⏺advanced helpdesk SLA Policy\n⏺Assign Tickets Via Ticket Type, Team\n⏺Helpdesk Multi language support\nAnd more.....\n\n✅Just visit our app link and explore more new interesting features of Advanced website helpdesk odoo module\n\n👉App download now :🔗\n\nOdoo 18 : https://bit.ly/4fJjGm8\nOdoo 17 : https://bit.ly/3tEBcWg\nOdoo 16 : https://bit.ly/3FEH6K6\nOdoo 15 : https://bit.ly/3yTpJ4H\nOdoo 14 : https://bit.ly/3ywuIbj\nOdoo 13 : https://bit.ly/3rIXMZ8\n\n👉Ask us for free Demo ? business@aagaminfotech.com\n👉Want to discuss: http://www.aagaminfotech.com\n👉Explore more odoo Apps: https://bit.ly/3y02ofI","tags":["odoo helpdesk","odoo helpdesk app","helpdeskmodule"],"url":"https://www.slideshare.net/slideshow/advance-website-helpdesk-customer-support-ticket-management-odoo/276219588","userLogin":"aagaminfotech","userName":"Aagam infotech ","viewCount":35},{"algorithmId":"4","displayTitle":"AI Agents and More:Build Your AI Assistans","isSavedByCurrentUser":false,"pageCount":14,"score":0,"slideshowId":"276255832","sourceName":"LATEST","strippedTitle":"ai-agents-and-more-build-your-ai-assistans","thumbnail":"https://cdn.slidesharecdn.com/ss_thumbnails/gdgbakumeetuppresentation-250304082146-be9d28de-thumbnail.jpg?width=600\u0026height=600\u0026fit=bounds","description":"Süni intellekt dövründə AI Agents, avtomatlaşdırma və otonom sistemlərin əsasını təşkil edir. Smolagents framework gücünü öyrənmək və bu texnologiyalarla öz AI Assistant-inizi yaratmaq istəyirsiniz? Bu tədbir tam sizə görədir!","tags":[],"url":"https://www.slideshare.net/slideshow/ai-agents-and-more-build-your-ai-assistans/276255832","userLogin":"HusseinMalikMammadli","userName":"HusseinMalikMammadli","viewCount":38},{"algorithmId":"4","displayTitle":"Adobe After Effects Crack latest version 2025","isSavedByCurrentUser":false,"pageCount":42,"score":0,"slideshowId":"276337844","sourceName":"LATEST","strippedTitle":"adobe-after-effects-crack-latest-version-2025","thumbnail":"https://cdn.slidesharecdn.com/ss_thumbnails/preexamclass11eng-250306084605-6d613160-thumbnail.jpg?width=600\u0026height=600\u0026fit=bounds","description":"➡ 🌍📱👉COPY \u0026 PASTE LINK👉👉👉 https://crack4pro.net/download-latest-windows-softwaresz/ \n\nFree Download Adobe After Effects CC Pre-Activated offline installer for Windows [Torrent + Direct Download Links] to create cinematic movie titles, intros, and transitions.\n\n","tags":[],"url":"https://www.slideshare.net/slideshow/adobe-after-effects-crack-latest-version-2025/276337844","userLogin":"saniasabbba","userName":"saniasabbba","viewCount":18},{"algorithmId":"4","displayTitle":"Instagram Feed Snippet, Instagram posts display in odoo website","isSavedByCurrentUser":false,"pageCount":16,"score":0,"slideshowId":"276338869","sourceName":"LATEST","strippedTitle":"instagram-feed-snippet-instagram-posts-display-in-odoo-website","thumbnail":"https://cdn.slidesharecdn.com/ss_thumbnails/instagramsnippetnaxis-250306091517-54963130-thumbnail.jpg?width=600\u0026height=600\u0026fit=bounds","description":"➡️Instagram snippet Odoo module come with Completely responsive and mobile ready, layout looks great on screen, simple way to set up, display photos and thumbnail, display #instagram posts, increase your number of follwers exciting features\n\nVisit Odoo 18 app link : https://bit.ly/3YMgiA3\n\nLet's Checkout Some interesting key features of Odoo instagram Snippet :\n\n👉🏻Key features of Instagram Odoo Snippet :\n\nEasy to Setup\nAny Instagram Profile\nInstagram UI Post\nFully Responsive instagram snippet in odoo\nFaster Load More\nAnd more....\n\nJust click On below Odoo Instagram Snippet link and explore more exciting new features :\n\nApp download now :\n\nOdoo 18 : https://bit.ly/3YMgiA3\nOdoo 17 : https://bit.ly/4aiiZ0g\nOdoo 16 : https://bit.ly/3WGPzCv\nOdoo 15 : https://bit.ly/3LD8N6m\nOdoo 14 : https://bit.ly/3K9wL8H\nOdoo 13 : https://bit.ly/3DCiW0c\n\n👉🏻Explore more odoo Apps : https://bit.ly/3oFIOCF\n👉🏻Want A Free DEMO ? : business@axistechnolabs.com\n👉🏻Want to discuss ? : https://lnkd.in/gfXHqhU4\n👉🏻Looking Odoo services : https://lnkd.in/gjxHC4dd\nContact Us : 091066 49361","tags":["odooapps","odoo","instagramsnippet"],"url":"https://www.slideshare.net/slideshow/instagram-feed-snippet-instagram-posts-display-in-odoo-website/276338869","userLogin":"axisasptraining","userName":"AxisTechnolabs","viewCount":14},{"algorithmId":"4","displayTitle":"Cybersecurity \u0026 Innovation: The Future of Mobile App Development","isSavedByCurrentUser":false,"pageCount":8,"score":0,"slideshowId":"276265463","sourceName":"LATEST","strippedTitle":"cybersecurity-innovation-the-future-of-mobile-app-development","thumbnail":"https://cdn.slidesharecdn.com/ss_thumbnails/iprogrammerappsecurity-250304133734-0bbd5b9c-thumbnail.jpg?width=600\u0026height=600\u0026fit=bounds","description":"In 2025, AI-powered cyber threats are growing, but so are AI-driven security measures! Here’s how we’re fighting back:\n\n ✅ AI-Powered Fraud Detection – Spot \u0026 stop attacks in real-time\n ✅ Behavioral Biometrics – AI learns user behavior \u0026 detects anomalies\n ✅ Adaptive Security Models – Auto-adjust security levels based on risk\n ✅ AI-Powered Encryption – Data stays safe, even in transit\n At iProgrammer, we build intelligent, AI-driven security solutions to keep your app one step ahead of cyber threats! 🔐\n\n How secure is your app? 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However, to truly drive impact, platform engineers must think like product managers—leveraging productivity metrics to guide decisions, prioritize investments, and measure success. By applying a data-driven approach, platform teams can optimize developer experience, streamline workflows, and demonstrate tangible ROI on platform initiatives.\n\nIn this 15-minute session, Justin Reock, Deputy CTO at DX (getdx.com), will explore how platform engineers can use key developer productivity metrics—such as cycle time, deployment frequency, and developer satisfaction—to manage their platform as an internal product. 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