Full Text Search Improve Query Performance - Full Text Search

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I configured the FTS index as below. "name": "full_text_index", "type": "fulltext-index", "params": { "mapping": { "types": { "_default.native": { "enabled": true, "dynamic": true, "default_analyzer": "standard", "properties": { "text": { "enabled": true, "dynamic": false, "fie..." /> <meta name="twitter:description" content="Hi Community, Description: I have a data set around 4 - 5 Million documents, where I need to configure Full Text Search Capability with minimum response time. I configured the FTS index as below. "name": "full_text_index", "type": "fulltext-index", "params": { "mapping": { "types": { "_default.native": { "enabled": true, "dynamic": true, "default_analyzer": "standard", "properties": { "text": { "enabled": true, "dynamic": false, "fie..." /> <meta property="og:article:section" content="Full Text Search" /> <meta property="og:article:section:color" content="81D742" /> <meta property="og:article:tag" content="fts" /> <meta property="article:published_time" content="2024-11-12T13:52:35+00:00" /> <meta property="og:ignore_canonical" content="true" /> <script type="application/ld+json">{"@context":"http://schema.org","@type":"QAPage","name":"Full Text Search Improve Query Performance","mainEntity":{"@type":"Question","name":"Full Text Search Improve Query Performance","text":"Hi Community,\n\nDescription:\n\nI have a data set around 4 - 5 Million documents, where I need to configure Full Text Search Capability with minimum response time.\n\nI configured the FTS index as below.\n\n"name": "full_text_index",\n\n"type": "fulltext-index",\n\n"params": {\n\n"mapping": {\n\n"types": {\n\n…","upvoteCount":0,"answerCount":0,"datePublished":"2024-11-12T13:52:34.999Z","author":{"@type":"Person","name":"mohithraj_kulal","url":"https://www.couchbase.com/forums/u/mohithraj_kulal"}}}</script> </head> <body class="crawler browser-update"> <header> <a href="/forums/"> Couchbase Forums </a> </header> <div id="main-outlet" class="wrap" role="main"> <div id="topic-title"> <h1> <a href="/forums/t/full-text-search-improve-query-performance/39705">Full Text Search Improve Query Performance</a> </h1> <div class="topic-category" itemscope itemtype="http://schema.org/BreadcrumbList"> <span itemprop="itemListElement" itemscope itemtype="http://schema.org/ListItem"> <a href="/forums/c/couchbase-full-text-search/25" class="badge-wrapper bullet" itemprop="item"> <span class='badge-category-bg' style='background-color: #81D742'></span> <span class='badge-category clear-badge'> <span class='category-name' itemprop='name'>Full Text Search</span> </span> </a> <meta itemprop="position" content="1" /> </span> </div> <div class="topic-category"> <div class='discourse-tags list-tags'> <a href='https://www.couchbase.com/forums/tag/fts' class='discourse-tag' rel="tag">fts</a> </div> </div> </div> <div itemscope itemtype='http://schema.org/DiscussionForumPosting'> <meta itemprop='headline' content='Full Text Search Improve Query Performance'> <link itemprop='url' href='https://www.couchbase.com/forums/t/full-text-search-improve-query-performance/39705'> <meta itemprop='datePublished' content='2024-11-12T13:52:34Z'> <meta itemprop='articleSection' content='Full Text Search'> <meta itemprop='keywords' content='fts'> <div itemprop='publisher' itemscope itemtype="http://schema.org/Organization"> <meta itemprop='name' content='Couchbase Forums'> <div itemprop='logo' itemscope itemtype="http://schema.org/ImageObject"> <meta itemprop='url' content='https://global.discourse-cdn.com/couchbase/original/2X/0/01f9ae109c030e7bf64d0812eaa8a3b08cf5ce60.png'> </div> </div> <div id='post_1' class='topic-body crawler-post'> <div class='crawler-post-meta'> <span class="creator" itemprop="author" itemscope itemtype="http://schema.org/Person"> <a itemprop="url" rel='nofollow' href='https://www.couchbase.com/forums/u/mohithraj_kulal'><span itemprop='name'>mohithraj_kulal</span></a> </span> <link itemprop="mainEntityOfPage" href="https://www.couchbase.com/forums/t/full-text-search-improve-query-performance/39705"> <span class="crawler-post-infos"> <time datetime='2024-11-12T13:52:35Z' class='post-time'> November 12, 2024, 1:52pm </time> <meta itemprop='dateModified' content='2024-11-12T14:00:04Z'> <span itemprop='position'>1</span> </span> </div> <div class='post' itemprop='text'> <p>Hi Community,</p> <p>Description:</p> <p>I have a data set around 4 - 5 Million documents, where I need to configure Full Text Search Capability with minimum response time.<br> I configured the FTS index as below.</p> <pre><code class="lang-auto"> "name": "full_text_index", "type": "fulltext-index", "params": { "mapping": { "types": { "_default.native": { "enabled": true, "dynamic": true, "default_analyzer": "standard", "properties": { "text": { "enabled": true, "dynamic": false, "fields": [ { "name": "text", "type": "text", "analyzer": "simple", "store": false, "index": true, "include_term_vectors": true, "include_in_all": false, "docvalues": false } ] }, "tenant": { "enabled": true, "dynamic": false, "fields": [ { "name": "tenant", "type": "text", "analyzer": "keyword", "store": false, "index": true, "include_term_vectors": false, "include_in_all": false, "docvalues": false } ] }, "status": { "enabled": true, "dynamic": false, "fields": [ { "name": "status", "type": "text", "analyzer": "keyword", "store": false, "index": true, "include_term_vectors": false, "include_in_all": false, "docvalues": false } ] }, "locale": { "enabled": true, "dynamic": false, "fields": [ { "name": "locale", "type": "text", "analyzer": "keyword", "store": false, "index": true, "include_term_vectors": false, "include_in_all": false, "docvalues": false } ] }, "lastUpdateTime": { "enabled": true, "dynamic": false, "fields": [ { "name": "lastUpdateTime", "type": "number", "store": false, "index": true, "include_term_vectors": false, "include_in_all": false, "docvalues": true } ] }, "productIds": { "enabled": true, "dynamic": false, "fields": [ { "name": "productIds", "type": "text", "analyzer": "keyword", "store": false, "index": true, "include_term_vectors": false, "include_in_all": false, "docvalues": false } ] }, "id": { "enabled": true, "dynamic": false, "fields": [ { "name": "id", "type": "text", "analyzer": "keyword", "store": false, "index": true, "include_term_vectors": false, "include_in_all": false, "docvalues": false } ] }, "summary": { "enabled": true, "dynamic": false, "fields": [ { "name": "summary", "type": "text", "analyzer": "simple", "store": false, "index": true, "include_term_vectors": true, "include_in_all": false, "docvalues": false } ] } } } }, "default_mapping": { "enabled": false, "dynamic": true }, "default_type": "_default", "default_analyzer": "standard", "default_datetime_parser": "dateTimeOptional", "default_field": "", "store_dynamic": false, "index_dynamic": false, "docvalues_dynamic": false }, "store": { "indexType": "scorch", "kvStoreName": "" }, "doc_config": { "docid_prefix_delim": "", "docid_regexp": "", "mode": "scope.collection.type_field", "type_field": "type" } }, "sourceType": "couchbase", "sourceName": "Sample", "sourceUUID": "be04daad7edfa09f20ecf781c0817483", "sourceParams": {}, "planParams": { "maxPartitionsPerPIndex": 1024, "numReplicas": 0, "indexPartitions": 12 }, "uuid": "" } </code></pre> <p>Document Description:<br> tenant, status, locale are string attributes where I need a full match, hence used keyword analyser<br> productIds is list of IDs where I need a full match, hence used keyword analyser<br> lastUpdateTime is long value where I need to query by range and sort in descending order<br> Id is a string, where I need to query for full match or a partial match as a wildcard like suffix match (Ex: *documentId)<br> text and summary are text attributes where I need to match phrases or normal word match.</p> <p>I have created index as above screenshot with index partition as 12 without using any custom analyser of filter.</p> <p>Search Query:</p> <pre><code class="lang-auto">{ "query": { "conjuncts": [ { "disjuncts": [ { "wildcard": "*{{searchText}}", "field": "id" }, { "match_phrase": "{{searchText}}", "field": "text" }, { "match_phrase": "{{searchText}}", "field": "summary" }, { "match": "{{searchText}}", "field": "prod" } ] }, { "term": "abc-123", "field": "tenant" }, { "disjuncts": [ { "term": "en", "field": "locale" } ] }, { "disjuncts": [ { "term": "Approved", "field": "status" }, { "term": "Rejected", "field": "status" } ] }, { "field": "lastUpdateTime", "min": 1603799414000, "max": 1730029814000, "inclusive_min": true, "inclusive_max": true } ] }, "sort": [ "-lastUpdateTime" ], "size": 10, "from": 0 } </code></pre> <p>My query looks above, the {{searchText}} place holder will be replaced with my dynamic input from UI and other query attributes are filled based on user type and filter params.</p> <p>Problem:<br> Currently with above index configuration and querying for 4-5 million documents I am able to get the data in 400ms - 500ms. Even though I do not store any data in index for retrieval as it increases my index size in disk.<br> I need to get response within 50ms. Is is possible to achieve such low latency. If yes, Can anyone help me here to get query data with faster retrieval.</p> </div> <div itemprop="interactionStatistic" itemscope itemtype="http://schema.org/InteractionCounter"> <meta itemprop="interactionType" content="http://schema.org/LikeAction"/> <meta itemprop="userInteractionCount" content="0" /> <span class='post-likes'></span> </div> </div> <div id='post_2' itemprop='comment' itemscope itemtype='http://schema.org/Comment' class='topic-body crawler-post'> <div class='crawler-post-meta'> <span class="creator" itemprop="author" itemscope itemtype="http://schema.org/Person"> <a itemprop="url" rel='nofollow' href='https://www.couchbase.com/forums/u/abhinav'><span itemprop='name'>abhinav</span></a> </span> <span class="crawler-post-infos"> <time itemprop='datePublished' datetime='2024-11-20T22:51:18Z' class='post-time'> November 20, 2024, 10:51pm </time> <meta itemprop='dateModified' content='2024-11-20T22:51:18Z'> <span itemprop='position'>2</span> </span> </div> <div class='post' itemprop='text'> <p>Hello <a class="mention" href="/forums/u/mohithraj_kulal">@mohithraj_kulal</a> ,</p> <p>Your query generally looks good for the index.</p> <p>A wildcard query could be the slower one here because it runs in two phases where first the candidate terms for the list will be determined and then a disjunction will run over all those candidate terms - you can look into moving this query-time-compute to the index time, by devising a custom analyzer that uses maybe a <code>whitespace</code> or <code>unicode</code> tokenizer but importantly an <code>ngram</code> token filter with a low enough <code>min</code> (smallest word size) and reasonable max (maybe max word length).</p> <aside class="onebox allowlistedgeneric" data-onebox-src="https://docs.couchbase.com/server/current/search/create-custom-token-filter.html#edge-ngram"> <header class="source"> <img src="https://docs.couchbase.com/_/img/favicon.svg" class="site-icon" width="16" height="16"> <a href="https://docs.couchbase.com/server/current/search/create-custom-token-filter.html#edge-ngram" target="_blank" rel="noopener nofollow ugc">docs.couchbase.com</a> </header> <article class="onebox-body"> <h3><a href="https://docs.couchbase.com/server/current/search/create-custom-token-filter.html#edge-ngram" target="_blank" rel="noopener nofollow ugc">Create a Custom Token Filter | Couchbase Docs</a></h3> <p>Create a custom token filter with the Couchbase Server Web Console to change how the Search Service creates tokens from Search index content and Search queries.</p> </article> <div class="onebox-metadata"> </div> <div style="clear: both"></div> </aside> <p>With this your index size would slightly increase (to hold more tokens for the data), but you get to replace your wildcard query with a term query instead …</p> <pre><code class="lang-auto">{ "query": { "conjuncts": [ { "disjuncts": [ {"field": "id", "term": "{{searchText}}"}, {"match_phrase": "{{searchText}}", "field": "text"}, {"match_phrase": "{{searchText}}", "field": "summary"}, {"match": "{{searchText}}", "field": "prod"} ] }, {"term": "abc-123", "field": "tenant"}, {"term": "en", "field": "locale"}, { "disjuncts": [ {"term": "Approved", "field": "status"}, {"term": "Rejected", "field": "status"} ] }, { "field": "lastUpdateTime", "min": 1603799414000, "max": 1730029814000, "inclusive_min": true, "inclusive_max": true } ] }, "sort": [ "-lastUpdateTime" ], "size": 10, "from": 0 } </code></pre> <p>Another optimization also comes to mind here …</p> <ul> <li>find a common analyzer for fields - <code>id</code>, <code>text</code>, <code>summary</code> and <code>prod</code></li> <li>set <code>include in _all</code> to true for all these fields</li> <li>set the <code>default_analyzer</code> at the top level of your index definition to this common analyzer, or maybe something better</li> <li>now you can replace the top 4 disjuncts with a single match query (uses the <code>default_analyzer</code>) that would search within the <code>_all</code> field which will be a composite of the 4 fields above …</li> </ul> <pre><code class="lang-auto">{ "query": { "conjuncts": [ {"match": "{{searchText}}"}, {"term": "abc-123", "field": "tenant"}, {"term": "en", "field": "locale"}, { "disjuncts": [ {"term": "Approved", "field": "status"}, {"term": "Rejected", "field": "status"} ] }, { "field": "lastUpdateTime", "min": 1603799414000, "max": 1730029814000, "inclusive_min": true, "inclusive_max": true } ] }, "sort": [ "-lastUpdateTime" ], "size": 10, "from": 0 } </code></pre> </div> <div itemprop="interactionStatistic" itemscope itemtype="http://schema.org/InteractionCounter"> <meta itemprop="interactionType" content="http://schema.org/LikeAction"/> <meta itemprop="userInteractionCount" content="0" /> <span class='post-likes'></span> </div> </div> </div> <div id="related-topics" class="more-topics__list " role="complementary" aria-labelledby="related-topics-title"> <h3 id="related-topics-title" 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