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diff --git a/doc/src/sgml/html/textsearch-indexes.html b/doc/src/sgml/html/textsearch-indexes.html new file mode 100644 index 0000000..6667094 --- /dev/null +++ b/doc/src/sgml/html/textsearch-indexes.html @@ -0,0 +1,80 @@ +<?xml version="1.0" encoding="UTF-8" standalone="no"?> +<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"><html xmlns="http://www.w3.org/1999/xhtml"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8" /><title>12.9. Preferred Index Types for Text Search</title><link rel="stylesheet" type="text/css" href="stylesheet.css" /><link rev="made" href="pgsql-docs@lists.postgresql.org" /><meta name="generator" content="DocBook XSL Stylesheets Vsnapshot" /><link rel="prev" href="textsearch-debugging.html" title="12.8. Testing and Debugging Text Search" /><link rel="next" href="textsearch-psql.html" title="12.10. psql Support" /></head><body id="docContent" class="container-fluid col-10"><div class="navheader"><table width="100%" summary="Navigation header"><tr><th colspan="5" align="center">12.9. Preferred Index Types for Text Search</th></tr><tr><td width="10%" align="left"><a accesskey="p" href="textsearch-debugging.html" title="12.8. Testing and Debugging Text Search">Prev</a> </td><td width="10%" align="left"><a accesskey="u" href="textsearch.html" title="Chapter 12. Full Text Search">Up</a></td><th width="60%" align="center">Chapter 12. Full Text Search</th><td width="10%" align="right"><a accesskey="h" href="index.html" title="PostgreSQL 15.4 Documentation">Home</a></td><td width="10%" align="right"> <a accesskey="n" href="textsearch-psql.html" title="12.10. psql Support">Next</a></td></tr></table><hr /></div><div class="sect1" id="TEXTSEARCH-INDEXES"><div class="titlepage"><div><div><h2 class="title" style="clear: both">12.9. Preferred Index Types for Text Search</h2></div></div></div><a id="id-1.5.11.12.2" class="indexterm"></a><p> + There are two kinds of indexes that can be used to speed up full text + searches: + <a class="link" href="gin.html" title="Chapter 70. GIN Indexes"><acronym class="acronym">GIN</acronym></a> and + <a class="link" href="gist.html" title="Chapter 68. GiST Indexes"><acronym class="acronym">GiST</acronym></a>. + Note that indexes are not mandatory for full text searching, but in + cases where a column is searched on a regular basis, an index is + usually desirable. + </p><p> + To create such an index, do one of: + + </p><div class="variablelist"><dl class="variablelist"><dt><span class="term"> + <a id="id-1.5.11.12.4.1.1.1.1" class="indexterm"></a> + + <code class="literal">CREATE INDEX <em class="replaceable"><code>name</code></em> ON <em class="replaceable"><code>table</code></em> USING GIN (<em class="replaceable"><code>column</code></em>);</code> + </span></dt><dd><p> + Creates a GIN (Generalized Inverted Index)-based index. + The <em class="replaceable"><code>column</code></em> must be of <code class="type">tsvector</code> type. + </p></dd><dt><span class="term"> + <a id="id-1.5.11.12.4.1.2.1.1" class="indexterm"></a> + + <code class="literal">CREATE INDEX <em class="replaceable"><code>name</code></em> ON <em class="replaceable"><code>table</code></em> USING GIST (<em class="replaceable"><code>column</code></em> [ { DEFAULT | tsvector_ops } (siglen = <em class="replaceable"><code>number</code></em>) ] );</code> + </span></dt><dd><p> + Creates a GiST (Generalized Search Tree)-based index. + The <em class="replaceable"><code>column</code></em> can be of <code class="type">tsvector</code> or + <code class="type">tsquery</code> type. + Optional integer parameter <code class="literal">siglen</code> determines + signature length in bytes (see below for details). + </p></dd></dl></div><p> + </p><p> + GIN indexes are the preferred text search index type. As inverted + indexes, they contain an index entry for each word (lexeme), with a + compressed list of matching locations. Multi-word searches can find + the first match, then use the index to remove rows that are lacking + additional words. GIN indexes store only the words (lexemes) of + <code class="type">tsvector</code> values, and not their weight labels. Thus a table + row recheck is needed when using a query that involves weights. + </p><p> + A GiST index is <em class="firstterm">lossy</em>, meaning that the index + might produce false matches, and it is necessary + to check the actual table row to eliminate such false matches. + (<span class="productname">PostgreSQL</span> does this automatically when needed.) + GiST indexes are lossy because each document is represented in the + index by a fixed-length signature. The signature length in bytes is determined + by the value of the optional integer parameter <code class="literal">siglen</code>. + The default signature length (when <code class="literal">siglen</code> is not specified) is + 124 bytes, the maximum signature length is 2024 bytes. The signature is generated by hashing + each word into a single bit in an n-bit string, with all these bits OR-ed + together to produce an n-bit document signature. When two words hash to + the same bit position there will be a false match. If all words in + the query have matches (real or false) then the table row must be + retrieved to see if the match is correct. Longer signatures lead to a more + precise search (scanning a smaller fraction of the index and fewer heap + pages), at the cost of a larger index. + </p><p> + A GiST index can be covering, i.e., use the <code class="literal">INCLUDE</code> + clause. Included columns can have data types without any GiST operator + class. Included attributes will be stored uncompressed. + </p><p> + Lossiness causes performance degradation due to unnecessary fetches of table + records that turn out to be false matches. Since random access to table + records is slow, this limits the usefulness of GiST indexes. The + likelihood of false matches depends on several factors, in particular the + number of unique words, so using dictionaries to reduce this number is + recommended. + </p><p> + Note that <acronym class="acronym">GIN</acronym> index build time can often be improved + by increasing <a class="xref" href="runtime-config-resource.html#GUC-MAINTENANCE-WORK-MEM">maintenance_work_mem</a>, while + <acronym class="acronym">GiST</acronym> index build time is not sensitive to that + parameter. + </p><p> + Partitioning of big collections and the proper use of GIN and GiST indexes + allows the implementation of very fast searches with online update. + Partitioning can be done at the database level using table inheritance, + or by distributing documents over + servers and collecting external search results, e.g., via <a class="link" href="ddl-foreign-data.html" title="5.12. Foreign Data">Foreign Data</a> access. + The latter is possible because ranking functions use + only local information. + </p></div><div class="navfooter"><hr /><table width="100%" summary="Navigation footer"><tr><td width="40%" align="left"><a accesskey="p" href="textsearch-debugging.html" title="12.8. Testing and Debugging Text Search">Prev</a> </td><td width="20%" align="center"><a accesskey="u" href="textsearch.html" title="Chapter 12. Full Text Search">Up</a></td><td width="40%" align="right"> <a accesskey="n" href="textsearch-psql.html" title="12.10. psql Support">Next</a></td></tr><tr><td width="40%" align="left" valign="top">12.8. Testing and Debugging Text Search </td><td width="20%" align="center"><a accesskey="h" href="index.html" title="PostgreSQL 15.4 Documentation">Home</a></td><td width="40%" align="right" valign="top"> 12.10. <span class="application">psql</span> Support</td></tr></table></div></body></html>
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