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author | Daniel Baumann <daniel.baumann@progress-linux.org> | 2024-04-13 14:07:11 +0000 |
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committer | Daniel Baumann <daniel.baumann@progress-linux.org> | 2024-04-13 14:07:11 +0000 |
commit | 63847496f14c813a5d80efd5b7de0f1294ffe1e3 (patch) | |
tree | 01c7571c7c762ceee70638549a99834fdd7c411b /www/fts3.html | |
parent | Initial commit. (diff) | |
download | sqlite3-63847496f14c813a5d80efd5b7de0f1294ffe1e3.tar.xz sqlite3-63847496f14c813a5d80efd5b7de0f1294ffe1e3.zip |
Adding upstream version 3.45.1.upstream/3.45.1
Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>
Diffstat (limited to 'www/fts3.html')
-rw-r--r-- | www/fts3.html | 3287 |
1 files changed, 3287 insertions, 0 deletions
diff --git a/www/fts3.html b/www/fts3.html new file mode 100644 index 0000000..ac3a881 --- /dev/null +++ b/www/fts3.html @@ -0,0 +1,3287 @@ +<!DOCTYPE html> +<html><head> +<meta name="viewport" content="width=device-width, initial-scale=1.0"> +<meta http-equiv="content-type" content="text/html; charset=UTF-8"> +<link href="sqlite.css" rel="stylesheet"> +<title>SQLite FTS3 and FTS4 Extensions</title> +<!-- path= --> +</head> +<body> +<div class=nosearch> +<a href="index.html"> +<img class="logo" src="images/sqlite370_banner.gif" alt="SQLite" border="0"> +</a> +<div><!-- IE hack to prevent disappearing logo --></div> +<div class="tagline desktoponly"> +Small. Fast. Reliable.<br>Choose any three. +</div> +<div class="menu mainmenu"> +<ul> +<li><a href="index.html">Home</a> +<li class='mobileonly'><a href="javascript:void(0)" onclick='toggle_div("submenu")'>Menu</a> +<li class='wideonly'><a href='about.html'>About</a> +<li class='desktoponly'><a href="docs.html">Documentation</a> +<li class='desktoponly'><a href="download.html">Download</a> +<li class='wideonly'><a href='copyright.html'>License</a> +<li class='desktoponly'><a href="support.html">Support</a> +<li class='desktoponly'><a href="prosupport.html">Purchase</a> +<li class='search' id='search_menubutton'> +<a href="javascript:void(0)" onclick='toggle_search()'>Search</a> +</ul> +</div> +<div class="menu submenu" id="submenu"> +<ul> +<li><a href='about.html'>About</a> +<li><a href='docs.html'>Documentation</a> +<li><a href='download.html'>Download</a> +<li><a href='support.html'>Support</a> +<li><a href='prosupport.html'>Purchase</a> +</ul> +</div> +<div class="searchmenu" id="searchmenu"> +<form method="GET" action="search"> +<select name="s" id="searchtype"> +<option value="d">Search Documentation</option> +<option value="c">Search Changelog</option> +</select> +<input type="text" name="q" id="searchbox" value=""> +<input type="submit" value="Go"> +</form> +</div> +</div> +<script> +function toggle_div(nm) { +var w = document.getElementById(nm); +if( w.style.display=="block" ){ +w.style.display = "none"; +}else{ +w.style.display = "block"; +} +} +function toggle_search() { +var w = document.getElementById("searchmenu"); +if( w.style.display=="block" ){ +w.style.display = "none"; +} else { +w.style.display = "block"; +setTimeout(function(){ +document.getElementById("searchbox").focus() +}, 30); +} +} +function div_off(nm){document.getElementById(nm).style.display="none";} +window.onbeforeunload = function(e){div_off("submenu");} +/* Disable the Search feature if we are not operating from CGI, since */ +/* Search is accomplished using CGI and will not work without it. */ +if( !location.origin || !location.origin.match || !location.origin.match(/http/) ){ +document.getElementById("search_menubutton").style.display = "none"; +} +/* Used by the Hide/Show button beside syntax diagrams, to toggle the */ +function hideorshow(btn,obj){ +var x = document.getElementById(obj); +var b = document.getElementById(btn); +if( x.style.display!='none' ){ +x.style.display = 'none'; +b.innerHTML='show'; +}else{ +x.style.display = ''; +b.innerHTML='hide'; +} +return false; +} +var antiRobot = 0; +function antiRobotGo(){ +if( antiRobot!=3 ) return; +antiRobot = 7; +var j = document.getElementById("mtimelink"); +if(j && j.hasAttribute("data-href")) j.href=j.getAttribute("data-href"); +} +function antiRobotDefense(){ +document.body.onmousedown=function(){ +antiRobot |= 2; +antiRobotGo(); +document.body.onmousedown=null; +} +document.body.onmousemove=function(){ +antiRobot |= 2; +antiRobotGo(); +document.body.onmousemove=null; +} +setTimeout(function(){ +antiRobot |= 1; +antiRobotGo(); +}, 100) +antiRobotGo(); +} +antiRobotDefense(); +</script> +<div class=fancy> +<div class=nosearch> +<div class="fancy_title"> +SQLite FTS3 and FTS4 Extensions +</div> +<div class="fancy_toc"> +<a onclick="toggle_toc()"> +<span class="fancy_toc_mark" id="toc_mk">►</span> +Table Of Contents +</a> +<div id="toc_sub"><div class="fancy-toc1"><a href="#introduction_to_fts3_and_fts4">1. Introduction to FTS3 and FTS4</a></div> +<div class="fancy-toc2"><a href="#differences_between_fts3_and_fts4">1.1. Differences between FTS3 and FTS4</a></div> +<div class="fancy-toc2"><a href="#creating_and_destroying_fts_tables">1.2. Creating and Destroying FTS Tables</a></div> +<div class="fancy-toc2"><a href="#populating_fts_tables">1.3. Populating FTS Tables</a></div> +<div class="fancy-toc2"><a href="#simple_fts_queries">1.4. Simple FTS Queries</a></div> +<div class="fancy-toc2"><a href="#summary">1.5. Summary</a></div> +<div class="fancy-toc1"><a href="#compiling_and_enabling_fts3_and_fts4">2. Compiling and Enabling FTS3 and FTS4</a></div> +<div class="fancy-toc1"><a href="#full_text_index_queries">3. Full-text Index Queries</a></div> +<div class="fancy-toc2"><a href="#_set_operations_using_the_enhanced_query_syntax">3.1. +Set Operations Using The Enhanced Query Syntax</a></div> +<div class="fancy-toc2"><a href="#set_operations_using_the_standard_query_syntax">3.2. Set Operations Using The Standard Query Syntax</a></div> +<div class="fancy-toc1"><a href="#auxiliary_functions_snippet_offsets_and_matchinfo">4. Auxiliary Functions - Snippet, Offsets and Matchinfo</a></div> +<div class="fancy-toc2"><a href="#the_offsets_function">4.1. The Offsets Function</a></div> +<div class="fancy-toc2"><a href="#the_snippet_function">4.2. The Snippet Function</a></div> +<div class="fancy-toc2"><a href="#matchinfo">4.3. The Matchinfo Function</a></div> +<div class="fancy-toc1"><a href="#fts4aux">5. Fts4aux - Direct Access to the Full-Text Index</a></div> +<div class="fancy-toc1"><a href="#fts4_options">6. FTS4 Options</a></div> +<div class="fancy-toc2"><a href="#the_compress_and_uncompress_options">6.1. The compress= and uncompress= options</a></div> +<div class="fancy-toc2"><a href="#the_content_option_">6.2. The content= option </a></div> +<div class="fancy-toc3"><a href="#_contentless_fts4_tables_">6.2.1. Contentless FTS4 Tables </a></div> +<div class="fancy-toc3"><a href="#_external_content_fts4_tables_">6.2.2. External Content FTS4 Tables </a></div> +<div class="fancy-toc2"><a href="#the_languageid_option">6.3. The languageid= option</a></div> +<div class="fancy-toc2"><a href="#the_matchinfo_option">6.4. The matchinfo= option</a></div> +<div class="fancy-toc2"><a href="#the_notindexed_option">6.5. The notindexed= option</a></div> +<div class="fancy-toc2"><a href="#the_prefix_option">6.6. The prefix= option</a></div> +<div class="fancy-toc1"><a href="#commands">7. Special Commands For FTS3 and FTS4</a></div> +<div class="fancy-toc2"><a href="#optimize">7.1. The "optimize" command</a></div> +<div class="fancy-toc2"><a href="#rebuild">7.2. The "rebuild" command</a></div> +<div class="fancy-toc2"><a href="#integcheck">7.3. The "integrity-check" command</a></div> +<div class="fancy-toc2"><a href="#mergecmd">7.4. The "merge=X,Y" command</a></div> +<div class="fancy-toc2"><a href="#automerge"">7.5. The "automerge=N" command</a></div> +<div class="fancy-toc1"><a href="#tokenizer">8. Tokenizers</a></div> +<div class="fancy-toc2"><a href="#custom_application_defined_tokenizers">8.1. Custom (Application Defined) Tokenizers</a></div> +<div class="fancy-toc2"><a href="#querying_tokenizers">8.2. Querying Tokenizers</a></div> +<div class="fancy-toc1"><a href="#data_structures">9. Data Structures</a></div> +<div class="fancy-toc2"><a href="#shadow_tables">9.1. Shadow Tables</a></div> +<div class="fancy-toc2"><a href="#variable_length_integer_varint_format">9.2. Variable Length Integer (varint) Format</a></div> +<div class="fancy-toc2"><a href="#segment_b_tree_format">9.3. Segment B-Tree Format</a></div> +<div class="fancy-toc3"><a href="#segment_b_tree_leaf_nodes">9.3.1. Segment B-Tree Leaf Nodes</a></div> +<div class="fancy-toc3"><a href="#segment_b_tree_interior_nodes">9.3.2. Segment B-Tree Interior Nodes</a></div> +<div class="fancy-toc2"><a href="#doclist_format">9.4. Doclist Format</a></div> +<div class="fancy-toc1"><a href="#limitations">10. Limitations</a></div> +<div class="fancy-toc2"><a href="#_utf_16_byte_order_mark_problem_">10.1. UTF-16 byte-order-mark problem </a></div> +<div class="fancy-toc1"><a href="#appendix_a"> +Appendix A: Search Application Tips +</a></div> +</div> +</div> +<script> +function toggle_toc(){ +var sub = document.getElementById("toc_sub") +var mk = document.getElementById("toc_mk") +if( sub.style.display!="block" ){ +sub.style.display = "block"; +mk.innerHTML = "▼"; +} else { +sub.style.display = "none"; +mk.innerHTML = "►"; +} +} +</script> +</div> + + + + + + +<h2 id="overview" style="margin-left:1.0em" notoc="1"> Overview</h2> + +<p> + FTS3 and FTS4 are SQLite virtual table modules that allows users to perform + full-text searches on a set of documents. The most common (and effective) + way to describe full-text searches is "what Google, Yahoo, and Bing do + with documents placed on the World Wide Web". Users input a term, or series + of terms, perhaps connected by a binary operator or grouped together into a + phrase, and the full-text query system finds the set of documents that best + matches those terms considering the operators and groupings the user has + specified. This article describes the deployment and usage of FTS3 and FTS4. + +</p><p> + FTS1 and FTS2 are obsolete full-text search modules for SQLite. There are known + issues with these older modules and their use should be avoided. + Portions of the original FTS3 code were contributed to the SQLite project + by Scott Hess of <a href="http://www.google.com">Google</a>. It is now + developed and maintained as part of SQLite. + +</p><h1 id="introduction_to_fts3_and_fts4"><span>1. </span>Introduction to FTS3 and FTS4</h1> + +<p> + The FTS3 and FTS4 extension modules allows users to create special tables with a + built-in full-text index (hereafter "FTS tables"). The full-text index + allows the user to efficiently query the database for all rows that contain + one or more words (hereafter "tokens"), even if the table + contains many large documents. + +</p><p> + For example, if each of the 517430 documents in the + "<a href="http://www.cs.cmu.edu/~enron/">Enron E-Mail Dataset</a>" + is inserted into both an FTS table and an ordinary SQLite table + created using the following SQL script: + +</p><div class="codeblock"><pre>CREATE VIRTUAL TABLE enrondata1 USING fts3(content TEXT); /* FTS3 table */ +CREATE TABLE enrondata2(content TEXT); /* Ordinary table */ +</pre></div> + +<p> + Then either of the two queries below may be executed to find the number of + documents in the database that contain the word "linux" (351). Using one + desktop PC hardware configuration, the query on the FTS3 table returns in + approximately 0.03 seconds, versus 22.5 for querying the ordinary table. + +</p><div class="codeblock"><pre>SELECT count(*) FROM enrondata1 WHERE content MATCH 'linux'; /* 0.03 seconds */ +SELECT count(*) FROM enrondata2 WHERE content LIKE '%linux%'; /* 22.5 seconds */ +</pre></div> + +<p> + Of course, the two queries above are not entirely equivalent. For example + the LIKE query matches rows that contain terms such as "linuxophobe" + or "EnterpriseLinux" (as it happens, the Enron E-Mail Dataset does not + actually contain any such terms), whereas the MATCH query on the FTS3 table + selects only those rows that contain "linux" as a discrete token. Both + searches are case-insensitive. The FTS3 table consumes around 2006 MB on + disk compared to just 1453 MB for the ordinary table. Using the same + hardware configuration used to perform the SELECT queries above, the FTS3 + table took just under 31 minutes to populate, versus 25 for the ordinary + table. + +</p><h2 id="differences_between_fts3_and_fts4"><span>1.1. </span>Differences between FTS3 and FTS4</h2> +<a name="fts4"></a> + + +<p> + FTS3 and FTS4 are nearly identical. They share most of their code in common, + and their interfaces are the same. The differences are: + +</p><ul> + <li> <p>FTS4 contains query performance optimizations that may significantly + improve the performance of full-text queries that contain terms that are + very common (present in a large percentage of table rows). + + </p></li><li> <p>FTS4 supports some additional options that may used with the <a href="fts3.html#matchinfo">matchinfo()</a> + function. + + </p></li><li> <p>Because it stores extra information on disk in two new + <a href="fts3.html#*shadowtab">shadow tables</a> in order to support the performance + optimizations and extra matchinfo() options, FTS4 tables may consume more + disk space than the equivalent table created using FTS3. Usually the overhead + is 1-2% or less, but may be as high as 10% if the documents stored in the + FTS table are very small. The overhead may be reduced by specifying the + directive <a href="fts3.html#fts4matchinfo">"matchinfo=fts3"</a> as part of the FTS4 table + declaration, but this comes at the expense of sacrificing some of the + extra supported matchinfo() options. + + </p></li><li> <p>FTS4 provides hooks (the compress and uncompress + <a href="fts3.html#fts4_options">options</a>) allowing data to be stored in a compressed + form, reducing disk usage and IO. +</p></li></ul> + +<p> + FTS4 is an enhancement to FTS3. + FTS3 has been available since SQLite <a href="releaselog/3_5_0.html">version 3.5.0</a> (2007-09-04) + The enhancements for FTS4 were added with SQLite <a href="releaselog/3_7_4.html">version 3.7.4</a> + (2010-12-07). + +</p><p> + Which module, FTS3 or FTS4, should you use in your application? FTS4 is + sometimes significantly faster than FTS3, even orders of magnitude faster + depending on the query, though in the common case the performance of the two + modules is similar. FTS4 also offers the enhanced <a href="fts3.html#matchinfo">matchinfo()</a> outputs which + can be useful in ranking the results of a <a href="fts3.html#full_text_index_queries">MATCH</a> operation. On the + other hand, in the absence of a <a href="fts3.html#fts4matchinfo">matchinfo=fts3</a> directive FTS4 requires a little + more disk space than FTS3, though only a percent of two in most cases. + +</p><p> + For newer applications, FTS4 is recommended; though if compatibility with older + versions of SQLite is important, then FTS3 will usually serve just as well. + +</p><h2 id="creating_and_destroying_fts_tables"><span>1.2. </span>Creating and Destroying FTS Tables</h2> + +<p> + Like other virtual table types, new FTS tables are created using a + <a href="lang_createvtab.html">CREATE VIRTUAL TABLE</a> statement. The module name, which follows + the USING keyword, is either "fts3" or "fts4". The virtual table module arguments may + be left empty, in which case an FTS table with a single user-defined + column named "content" is created. Alternatively, the module arguments + may be passed a list of comma separated column names. + +</p><p> + If column names are explicitly provided for the FTS table as part of + the CREATE VIRTUAL TABLE statement, then a datatype name may be optionally + specified for each column. This is pure syntactic sugar, the + supplied typenames are not used by FTS or the SQLite core for any + purpose. The same applies to any constraints specified along with an + FTS column name - they are parsed but not used or recorded by the system + in any way. + +</p><div class="codeblock"><pre><i>-- Create an FTS table named "data" with one column - "content":</i> +CREATE VIRTUAL TABLE data USING fts3(); + +<i>-- Create an FTS table named "pages" with three columns:</i> +CREATE VIRTUAL TABLE pages USING fts4(title, keywords, body); + +<i>-- Create an FTS table named "mail" with two columns. Datatypes +-- and column constraints are specified along with each column. These +-- are completely ignored by FTS and SQLite. </i> +CREATE VIRTUAL TABLE mail USING fts3( + subject VARCHAR(256) NOT NULL, + body TEXT CHECK(length(body)<10240) +); +</pre></div> + +<p> + As well as a list of columns, the module arguments passed to a CREATE + VIRTUAL TABLE statement used to create an FTS table may be used to specify + a <a href="fts3.html#tokenizer">tokenizer</a>. This is done by specifying a string of the form + "tokenize=<tokenizer name> <tokenizer args>" in place of a column + name, where <tokenizer name> is the name of the tokenizer to use and + <tokenizer args> is an optional list of whitespace separated qualifiers + to pass to the tokenizer implementation. A tokenizer specification may be + placed anywhere in the column list, but at most one tokenizer declaration is + allowed for each CREATE VIRTUAL TABLE statement. <a href="fts3.html#tokenizer">See below</a> for a + detailed description of using (and, if necessary, implementing) a tokenizer. + +</p><div class="codeblock"><pre><i>-- Create an FTS table named "papers" with two columns that uses</i> +<i>-- the tokenizer "porter".</i> +CREATE VIRTUAL TABLE papers USING fts3(author, document, tokenize=porter); + +<i>-- Create an FTS table with a single column - "content" - that uses</i> +<i>-- the "simple" tokenizer.</i> +CREATE VIRTUAL TABLE data USING fts4(tokenize=simple); + +<i>-- Create an FTS table with two columns that uses the "icu" tokenizer.</i> +<i>-- The qualifier "en_AU" is passed to the tokenizer implementation</i> +CREATE VIRTUAL TABLE names USING fts3(a, b, tokenize=icu en_AU); +</pre></div> + +<p> + FTS tables may be dropped from the database using an ordinary <a href="lang_droptable.html">DROP TABLE</a> + statement. For example: + +</p><div class="codeblock"><pre><i>-- Create, then immediately drop, an FTS4 table.</i> +CREATE VIRTUAL TABLE data USING fts4(); +DROP TABLE data; +</pre></div> + +<h2 id="populating_fts_tables"><span>1.3. </span>Populating FTS Tables</h2> + + <p> + FTS tables are populated using <a href="lang_insert.html">INSERT</a>, <a href="lang_update.html">UPDATE</a> and <a href="lang_delete.html">DELETE</a> + statements in the same way as ordinary SQLite tables are. + + </p><p> + As well as the columns named by the user (or the "content" column if no + module arguments were specified as part of the <a href="lang_createvtab.html">CREATE VIRTUAL TABLE</a> + statement), each FTS table has a "rowid" column. The rowid of an FTS + table behaves in the same way as the rowid column of an ordinary SQLite + table, except that the values stored in the rowid column of an FTS table + remain unchanged if the database is rebuilt using the <a href="lang_vacuum.html">VACUUM</a> command. + For FTS tables, "docid" is allowed as an alias along with the usual "rowid", + "oid" and "_oid_" identifiers. Attempting to insert or update a row with a + docid value that already exists in the table is an error, just as it would + be with an ordinary SQLite table. + + </p><p> + There is one other subtle difference between "docid" and the normal SQLite + aliases for the rowid column. Normally, if an INSERT or UPDATE statement + assigns discrete values to two or more aliases of the rowid column, SQLite + writes the rightmost of such values specified in the INSERT or UPDATE + statement to the database. However, assigning a non-NULL value to both + the "docid" and one or more of the SQLite rowid aliases when inserting or + updating an FTS table is considered an error. See below for an example. + +</p><div class="codeblock"><pre><i>-- Create an FTS table</i> +CREATE VIRTUAL TABLE pages USING fts4(title, body); + +<i>-- Insert a row with a specific docid value.</i> +INSERT INTO pages(docid, title, body) VALUES(53, 'Home Page', 'SQLite is a software...'); + +<i>-- Insert a row and allow FTS to assign a docid value using the same algorithm as</i> +<i>-- SQLite uses for ordinary tables. In this case the new docid will be 54,</i> +<i>-- one greater than the largest docid currently present in the table.</i> +INSERT INTO pages(title, body) VALUES('Download', 'All SQLite source code...'); + +<i>-- Change the title of the row just inserted.</i> +UPDATE pages SET title = 'Download SQLite' WHERE rowid = 54; + +<i>-- Delete the entire table contents.</i> +DELETE FROM pages; + +<i>-- The following is an error. It is not possible to assign non-NULL values to both</i> +<i>-- the rowid and docid columns of an FTS table.</i> +INSERT INTO pages(rowid, docid, title, body) VALUES(1, 2, 'A title', 'A document body'); +</pre></div> + + <p> + To support full-text queries, FTS maintains an inverted index that maps + from each unique term or word that appears in the dataset to the locations + in which it appears within the table contents. For the curious, a + complete description of the <a href="fts3.html#data_structures">data structure</a> used to store + this index within the database file appears below. A feature of + this data structure is that at any time the database may contain not + one index b-tree, but several different b-trees that are incrementally + merged as rows are inserted, updated and deleted. This technique improves + performance when writing to an FTS table, but causes some overhead for + full-text queries that use the index. Evaluating the special <a href="fts3.html#*fts4optcmd">"optimize" command</a>, + an SQL statement of the + form "INSERT INTO <fts-table>(<fts-table>) VALUES('optimize')", + causes FTS to merge all existing index b-trees into a single large + b-tree containing the entire index. This can be an expensive operation, + but may speed up future queries. + + </p><p> + For example, to optimize the full-text index for an FTS table named + "docs": + +</p><div class="codeblock"><pre><i>-- Optimize the internal structure of FTS table "docs".</i> +INSERT INTO docs(docs) VALUES('optimize'); +</pre></div> + + <p> + The statement above may appear syntactically incorrect to some. Refer to + the section describing the <a href="fts3.html#simple_fts_queries">simple fts queries</a> for an explanation. + + </p><p> + There is another, deprecated, method for invoking the optimize + operation using a SELECT statement. New code should use statements + similar to the INSERT above to optimize FTS structures. + +</p><a name="simple_fts_queries"></a> +<h2 tags="simple fts queries" id="simple_fts_queries"><span>1.4. </span>Simple FTS Queries</h2> + +<p> + As for all other SQLite tables, virtual or otherwise, data is retrieved + from FTS tables using a <a href="lang_select.html">SELECT</a> statement. + +</p><p> + FTS tables can be queried efficiently using SELECT statements of two + different forms: + +</p><ul> + <li><p> + <b>Query by rowid</b>. If the WHERE clause of the SELECT statement + contains a sub-clause of the form "rowid = ?", where ? is an SQL expression, + FTS is able to retrieve the requested row directly using the equivalent + of an SQLite <a href="lang_createtable.html#rowid">INTEGER PRIMARY KEY</a> index. + + </p></li><li><p> + <b>Full-text query</b>. If the WHERE clause of the SELECT statement contains + a sub-clause of the form "<column> MATCH ?", FTS is able to use + the built-in full-text index to restrict the search to those documents + that match the full-text query string specified as the right-hand operand + of the MATCH clause. +</p></li></ul> + +<p> + If neither of these two query strategies can be used, all + queries on FTS tables are implemented using a linear scan of the entire + table. If the table contains large amounts of data, this may be an + impractical approach (the first example on this page shows that a linear + scan of 1.5 GB of data takes around 30 seconds using a modern PC). + +</p><div class="codeblock"><pre><i>-- The examples in this block assume the following FTS table:</i> +CREATE VIRTUAL TABLE mail USING fts3(subject, body); + +SELECT * FROM mail WHERE rowid = 15; <i>-- Fast. Rowid lookup.</i> +SELECT * FROM mail WHERE body MATCH 'sqlite'; <i>-- Fast. Full-text query.</i> +SELECT * FROM mail WHERE mail MATCH 'search'; <i>-- Fast. Full-text query.</i> +SELECT * FROM mail WHERE rowid BETWEEN 15 AND 20; <i>-- Fast. Rowid lookup.</i> +SELECT * FROM mail WHERE subject = 'database'; <i>-- Slow. Linear scan.</i> +SELECT * FROM mail WHERE subject MATCH 'database'; <i>-- Fast. Full-text query.</i> +</pre></div> + +<p> + In all of the full-text queries above, the right-hand operand of the MATCH + operator is a string consisting of a single term. In this case, the MATCH + expression evaluates to true for all documents that contain one or more + instances of the specified word ("sqlite", "search" or "database", depending + on which example you look at). Specifying a single term as the right-hand + operand of the MATCH operator results in the simplest and most common type + of full-text query possible. However more complicated queries are possible, + including phrase searches, term-prefix searches and searches for documents + containing combinations of terms occurring within a defined proximity of each + other. The various ways in which the full-text index may be queried are + <a href="fts3.html#full_text_index_queries">described below</a>. + +</p><p> + Normally, full-text queries are case-insensitive. However, this + is dependent on the specific <a href="fts3.html#tokenizer">tokenizer</a> used by the FTS table + being queried. Refer to the section on <a href="fts3.html#tokenizer">tokenizers</a> for details. + +</p><p> + The paragraph above notes that a MATCH operator with a simple term as the + right-hand operand evaluates to true for all documents that contain the + specified term. In this context, the "document" may refer to either the + data stored in a single column of a row of an FTS table, or to the contents + of all columns in a single row, depending on the identifier used as the + left-hand operand to the MATCH operator. If the identifier specified as + the left-hand operand of the MATCH operator is an FTS table column name, + then the document that the search term must be contained in is the value + stored in the specified column. However, if the identifier is the name + of the FTS <i>table</i> itself, then the MATCH operator evaluates to true + for each row of the FTS table for which any column contains the search + term. The following example demonstrates this: + +</p><div class="codeblock"><pre><i>-- Example schema</i> +CREATE VIRTUAL TABLE mail USING fts3(subject, body); + +<i>-- Example table population</i> +INSERT INTO mail(docid, subject, body) VALUES(1, 'software feedback', 'found it too slow'); +INSERT INTO mail(docid, subject, body) VALUES(2, 'software feedback', 'no feedback'); +INSERT INTO mail(docid, subject, body) VALUES(3, 'slow lunch order', 'was a software problem'); + +<i>-- Example queries</i> +SELECT * FROM mail WHERE subject MATCH 'software'; <i>-- Selects rows 1 and 2</i> +SELECT * FROM mail WHERE body MATCH 'feedback'; <i>-- Selects row 2</i> +SELECT * FROM mail WHERE mail MATCH 'software'; <i>-- Selects rows 1, 2 and 3</i> +SELECT * FROM mail WHERE mail MATCH 'slow'; <i>-- Selects rows 1 and 3</i> +</pre></div> + +<p> + At first glance, the final two full-text queries in the example above seem + to be syntactically incorrect, as there is a table name ("mail") used as + an SQL expression. The reason this is acceptable is that each FTS table + actually has a <a href="c3ref/declare_vtab.html">HIDDEN</a> column with the same name + as the table itself (in this case, "mail"). The value stored in this + column is not meaningful to the application, but can be used as the + left-hand operand to a MATCH operator. This special column may also be + passed as an argument to the <a href="fts3.html#snippet">FTS auxiliary functions</a>. + +</p><p> + The following example illustrates the above. The expressions "docs", + "docs.docs" and "main.docs.docs" all refer to column "docs". However, the + expression "main.docs" does not refer to any column. It could be used to + refer to a table, but a table name is not allowed in the context in which + it is used below. + +</p><div class="codeblock"><pre><i>-- Example schema</i> +CREATE VIRTUAL TABLE docs USING fts4(content); + +<i>-- Example queries</i> +SELECT * FROM docs WHERE docs MATCH 'sqlite'; <i>-- OK.</i> +SELECT * FROM docs WHERE docs.docs MATCH 'sqlite'; <i>-- OK.</i> +SELECT * FROM docs WHERE main.docs.docs MATCH 'sqlite'; <i>-- OK.</i> +SELECT * FROM docs WHERE main.docs MATCH 'sqlite'; <i>-- Error.</i> +</pre></div> + +<h2 id="summary"><span>1.5. </span>Summary</h2> + +<p> + From the users point of view, FTS tables are similar to ordinary SQLite + tables in many ways. Data may be added to, modified within and removed + from FTS tables using the INSERT, UPDATE and DELETE commands just as + it may be with ordinary tables. Similarly, the SELECT command may be used + to query data. The following list summarizes the differences between FTS + and ordinary tables: + +</p><ol> + <li><p> + As with all virtual table types, it is not possible to create indices or + triggers attached to FTS tables. Nor is it possible to use the ALTER TABLE + command to add extra columns to FTS tables (although it is possible to use + ALTER TABLE to rename an FTS table). + + </p></li><li><p> + Data-types specified as part of the "CREATE VIRTUAL TABLE" statement + used to create an FTS table are ignored completely. Instead of the + normal rules for applying type <a href="datatype3.html#affinity">affinity</a> to inserted values, all + values inserted into FTS table columns (except the special rowid + column) are converted to type TEXT before being stored. + + </p></li><li><p> + FTS tables permit the special alias "docid" to be used to refer to the + rowid column supported by all <a href="vtab.html">virtual tables</a>. + + </p></li><li><p> + The <a href="fts3.html#full_text_index_queries">FTS MATCH</a> operator is supported for queries based on the built-in + full-text index. + + </p></li><li><p> + The <a href="fts3.html#snippet">FTS auxiliary functions</a>, <a href="fts3.html#snippet">snippet()</a>, <a href="fts3.html#offsets">offsets()</a>, and <a href="fts3.html#matchinfo">matchinfo()</a> are + available to support full-text queries. + + </p></li><li><p> + <a name="hiddencol"></a> + + Every FTS table has a <a href="vtab.html#hiddencol">hidden column</a> with the + same name as the table itself. The value contained in each row for the + hidden column is a blob that is only useful as the left operand of a + <a href="fts3.html#full_text_index_queries">MATCH</a> operator, or as the left-most argument to one + of the <a href="fts3.html#snippet">FTS auxiliary functions</a>. + + +</p></li></ol> + + +<a name="compiling_and_enabling_fts3_and_fts4"></a> +<h1 tags="compile fts" id="compiling_and_enabling_fts3_and_fts4"><span>2. </span>Compiling and Enabling FTS3 and FTS4</h1> + +<p> + Although FTS3 and FTS4 are included with the SQLite core source code, they are not + enabled by default. To build SQLite with FTS functionality enabled, define + the preprocessor macro <a href="compile.html#enable_fts3">SQLITE_ENABLE_FTS3</a> when compiling. New applications + should also define the <a href="compile.html#enable_fts3_parenthesis">SQLITE_ENABLE_FTS3_PARENTHESIS</a> macro to enable the + <a href="fts3.html#_set_operations_using_the_enhanced_query_syntax">enhanced query syntax</a> (see below). Usually, this is done by adding the + following two switches to the compiler command line: + +</p><div class="codeblock"><pre>-DSQLITE_ENABLE_FTS3 +-DSQLITE_ENABLE_FTS3_PARENTHESIS +</pre></div> + +<p> + Note that enabling FTS3 also makes FTS4 available. There is not a separate + SQLITE_ENABLE_FTS4 compile-time option. A build of SQLite either supports + both FTS3 and FTS4 or it supports neither. + +</p><p> + If using the amalgamation autoconf based build system, setting the CPPFLAGS + environment variable while running the 'configure' script is an easy + way to set these macros. For example, the following command: + +</p><div class="codeblock"><pre>CPPFLAGS="-DSQLITE_ENABLE_FTS3 -DSQLITE_ENABLE_FTS3_PARENTHESIS" ./configure <configure options> +</pre></div> + +<p> + where <i><configure options></i> are those options normally passed to + the configure script, if any. + +</p><p> + Because FTS3 and FTS4 are virtual tables, The <a href="compile.html#enable_fts3">SQLITE_ENABLE_FTS3</a> compile-time option + is incompatible with the <a href="compile.html#omit_virtualtable">SQLITE_OMIT_VIRTUALTABLE</a> option. + +</p><p> + If a build of SQLite does not include the FTS modules, then any attempt to prepare an + SQL statement to create an FTS3 or FTS4 table or to drop or access an existing + FTS table in any way will fail. The error message returned will be similar + to "no such module: ftsN" (where N is either 3 or 4). + +</p><p> + If the C version of the <a href="https://icu.unicode.org">ICU library</a> + is available, then FTS may also be compiled with the SQLITE_ENABLE_ICU + pre-processor macro defined. Compiling with this macro enables an FTS + <a href="fts3.html#tokenizer">tokenizer</a> that uses the ICU library to split a document into terms + (words) using the conventions for a specified language and locale. + +</p><div class="codeblock"><pre>-DSQLITE_ENABLE_ICU +</pre></div> + + +<a name="full_text_index_queries"></a> +<h1 tags="FTS MATCH" id="full_text_index_queries"><span>3. </span>Full-text Index Queries</h1> + +<p> + The most useful thing about FTS tables is the queries that may be + performed using the built-in full-text index. Full-text queries are + performed by specifying a clause of the form + "<column> MATCH <full-text query expression>" as part of the WHERE + clause of a SELECT statement that reads data from an FTS table. + <a href="fts3.html#simple_fts_queries">Simple FTS queries</a> that return all documents that + contain a given term are described above. In that discussion the right-hand + operand of the MATCH operator was assumed to be a string consisting of a + single term. This section describes the more complex query types supported + by FTS tables, and how they may be utilized by specifying a more + complex query expression as the right-hand operand of a MATCH operator. + +</p><p> + FTS tables support three basic query types: + +</p><ul> + <a name="termprefix"></a> + + <li><p><b>Token or token prefix queries</b>. + An FTS table may be queried for all documents that contain a specified + term (the <a href="fts3.html#simple_fts_queries">simple case</a> described above), or for + all documents that contain a term with a specified prefix. As we have + seen, the query expression for a specific term is simply the term itself. + The query expression used to search for a term prefix is the prefix + itself with a '*' character appended to it. For example: +</p></li></ul> + +<div class="codeblock"><pre><i>-- Virtual table declaration</i> +CREATE VIRTUAL TABLE docs USING fts3(title, body); + +<i>-- Query for all documents containing the term "linux":</i> +SELECT * FROM docs WHERE docs MATCH 'linux'; + +<i>-- Query for all documents containing a term with the prefix "lin". This will match</i> +<i>-- all documents that contain "linux", but also those that contain terms "linear",</i> +<i>--"linker", "linguistic" and so on.</i> +SELECT * FROM docs WHERE docs MATCH 'lin*'; +</pre></div> + +<ul> + <li style="list-style:none"><p> + Normally, a token or token prefix query is matched against the FTS table + column specified as the left-hand side of the MATCH operator. Or, if the + special column with the same name as the FTS table itself is specified, + against all columns. This may be overridden by specifying a column-name + followed by a ":" character before a basic term query. There may be space + between the ":" and the term to query for, but not between the column-name + and the ":" character. For example: +</p></li></ul> + +<div class="codeblock"><pre><i>-- Query the database for documents for which the term "linux" appears in</i> +<i>-- the document title, and the term "problems" appears in either the title</i> +<i>-- or body of the document.</i> +SELECT * FROM docs WHERE docs MATCH 'title:linux problems'; + +<i>-- Query the database for documents for which the term "linux" appears in</i> +<i>-- the document title, and the term "driver" appears in the body of the document</i> +<i>-- ("driver" may also appear in the title, but this alone will not satisfy the</i> +<i>-- query criteria).</i> +SELECT * FROM docs WHERE body MATCH 'title:linux driver'; +</pre></div> + +<ul> + <li style="list-style:none"><p> + If the FTS table is an FTS4 table (not FTS3), a token may also be prefixed + with a "^" character. In this case, in order to match the token must + appear as the very first token in any column of the matching row. Examples: +</p></li></ul> + +<div class="codeblock"><pre><i>-- All documents for which "linux" is the first token of at least one</i> +<i>-- column.</i> +SELECT * FROM docs WHERE docs MATCH '^linux'; + +<i>-- All documents for which the first token in column "title" begins with "lin".</i> +SELECT * FROM docs WHERE body MATCH 'title: ^lin*'; +</pre></div> + +<a name="phrase"></a> + +<ul> + <li><p><b>Phrase queries</b>. + A phrase query is a query that retrieves all documents that contain a + nominated set of terms or term prefixes in a specified order with no + intervening tokens. Phrase queries are specified by enclosing a space + separated sequence of terms or term prefixes in double quotes ("). + For example: +</p></li></ul> + +<div class="codeblock"><pre><i>-- Query for all documents that contain the phrase "linux applications".</i> +SELECT * FROM docs WHERE docs MATCH '"linux applications"'; + +<i>-- Query for all documents that contain a phrase that matches "lin* app*". As well as</i> +<i>-- "linux applications", this will match common phrases such as "linoleum appliances"</i> +<i>-- or "link apprentice".</i> +SELECT * FROM docs WHERE docs MATCH '"lin* app*"'; +</pre></div> + +<a name="near"></a> + +<ul> + <li><p><b>NEAR queries</b>. + A NEAR query is a query that returns documents that contain a two or + more nominated terms or phrases within a specified proximity of each + other (by default with 10 or less intervening terms). A NEAR query is + specified by putting the keyword "NEAR" between two phrase, token or + token prefix queries. To specify a proximity other than the default, + an operator of the form "NEAR/<i><N></i>" may be used, where + <i><N></i> is the maximum number of intervening terms allowed. + For example: +</p></li></ul> + +<div class="codeblock"><pre><i>-- Virtual table declaration.</i> +CREATE VIRTUAL TABLE docs USING fts4(); + +<i>-- Virtual table data.</i> +INSERT INTO docs VALUES('SQLite is an ACID compliant embedded relational database management system'); + +<i>-- Search for a document that contains the terms "sqlite" and "database" with</i> +<i>-- not more than 10 intervening terms. This matches the only document in</i> +<i>-- table docs (since there are only six terms between "SQLite" and "database"</i> +<i>-- in the document)</i>. +SELECT * FROM docs WHERE docs MATCH 'sqlite NEAR database'; + +<i>-- Search for a document that contains the terms "sqlite" and "database" with</i> +<i>-- not more than 6 intervening terms. This also matches the only document in</i> +<i>-- table docs. Note that the order in which the terms appear in the document</i> +<i>-- does not have to be the same as the order in which they appear in the query.</i> +SELECT * FROM docs WHERE docs MATCH 'database NEAR/6 sqlite'; + +<i>-- Search for a document that contains the terms "sqlite" and "database" with</i> +<i>-- not more than 5 intervening terms. This query matches no documents.</i> +SELECT * FROM docs WHERE docs MATCH 'database NEAR/5 sqlite'; + +<i>-- Search for a document that contains the phrase "ACID compliant" and the term</i> +<i>-- "database" with not more than 2 terms separating the two. This matches the</i> +<i>-- document stored in table docs.</i> +SELECT * FROM docs WHERE docs MATCH 'database NEAR/2 "ACID compliant"'; + +<i>-- Search for a document that contains the phrase "ACID compliant" and the term</i> +<i>-- "sqlite" with not more than 2 terms separating the two. This also matches</i> +<i>-- the only document stored in table docs.</i> +SELECT * FROM docs WHERE docs MATCH '"ACID compliant" NEAR/2 sqlite'; +</pre></div> + +<ul> + <li style="list-style: none"><p> + More than one NEAR operator may appear in a single query. In this case each + pair of terms or phrases separated by a NEAR operator must appear within the + specified proximity of each other in the document. Using the same table and + data as in the block of examples above: +</p></li></ul> + +<div class="codeblock"><pre><i>-- The following query selects documents that contains an instance of the term </i> +<i>-- "sqlite" separated by two or fewer terms from an instance of the term "acid",</i> +<i>-- which is in turn separated by two or fewer terms from an instance of the term</i> +<i>-- "relational".</i> +SELECT * FROM docs WHERE docs MATCH 'sqlite NEAR/2 acid NEAR/2 relational'; + +<i>-- This query matches no documents. There is an instance of the term "sqlite" with</i> +<i>-- sufficient proximity to an instance of "acid" but it is not sufficiently close</i> +<i>-- to an instance of the term "relational".</i> +SELECT * FROM docs WHERE docs MATCH 'acid NEAR/2 sqlite NEAR/2 relational'; +</pre></div> + +<p> + Phrase and NEAR queries may not span multiple columns within a row. + +</p><p> + The three basic query types described above may be used to query the full-text + index for the set of documents that match the specified criteria. Using the + FTS query expression language it is possible to perform various set + operations on the results of basic queries. There are currently three + supported operations: + +</p><ul> + <li> The AND operator determines the <b>intersection</b> of two sets of documents. + + </li><li> The OR operator calculates the <b>union</b> of two sets of documents. + + </li><li> The NOT operator (or, if using the standard syntax, a unary "-" operator) + may be used to compute the <b>relative complement</b> of one set of + documents with respect to another. +</li></ul> + +<p> + The FTS modules may be compiled to use one of two slightly different versions + of the full-text query syntax, the "standard" query syntax and the "enhanced" + query syntax. The basic term, term-prefix, phrase and NEAR queries described + above are the same in both versions of the syntax. The way in which set + operations are specified is slightly different. The following two sub-sections + describe the part of the two query syntaxes that pertains to set operations. + Refer to the description of how to <a href="fts3.html#compiling_and_enabling_fts3_and_fts4">compile fts</a> for compilation notes. + +</p><a name="_set_operations_using_the_enhanced_query_syntax"></a> +<h2 tags="enhanced query syntax" id="_set_operations_using_the_enhanced_query_syntax"><span>3.1. </span> + Set Operations Using The Enhanced Query Syntax</h2> + +<p> + The enhanced query syntax supports the AND, OR and NOT binary set operators. + Each of the two operands to an operator may be a basic FTS query, or the + result of another AND, OR or NOT set operation. Operators must be entered + using capital letters. Otherwise, they are interpreted as basic term queries + instead of set operators. + +</p><p> + The AND operator may be implicitly specified. If two basic queries appear + with no operator separating them in an FTS query string, the results are + the same as if the two basic queries were separated by an AND operator. + For example, the query expression "implicit operator" is a more succinct + version of "implicit AND operator". + +</p><div class="codeblock"><pre><i>-- Virtual table declaration</i> +CREATE VIRTUAL TABLE docs USING fts3(); + +<i>-- Virtual table data</i> +INSERT INTO docs(docid, content) VALUES(1, 'a database is a software system'); +INSERT INTO docs(docid, content) VALUES(2, 'sqlite is a software system'); +INSERT INTO docs(docid, content) VALUES(3, 'sqlite is a database'); + +<i>-- Return the set of documents that contain the term "sqlite", and the</i> +<i>-- term "database". This query will return the document with docid 3 only.</i> +SELECT * FROM docs WHERE docs MATCH 'sqlite AND database'; + +<i>-- Again, return the set of documents that contain both "sqlite" and</i> +<i>-- "database". This time, use an implicit AND operator. Again, document</i> +<i>-- 3 is the only document matched by this query. </i> +SELECT * FROM docs WHERE docs MATCH 'database sqlite'; + +<i>-- Query for the set of documents that contains either "sqlite" or "database".</i> +<i>-- All three documents in the database are matched by this query.</i> +SELECT * FROM docs WHERE docs MATCH 'sqlite OR database'; + +<i>-- Query for all documents that contain the term "database", but do not contain</i> +<i>-- the term "sqlite". Document 1 is the only document that matches this criteria.</i> +SELECT * FROM docs WHERE docs MATCH 'database NOT sqlite'; + +<i>-- The following query matches no documents. Because "and" is in lowercase letters,</i> +<i>-- it is interpreted as a basic term query instead of an operator. Operators must</i> +<i>-- be specified using capital letters. In practice, this query will match any documents</i> +<i>-- that contain each of the three terms "database", "and" and "sqlite" at least once.</i> +<i>-- No documents in the example data above match this criteria.</i> +SELECT * FROM docs WHERE docs MATCH 'database and sqlite'; +</pre></div> + +<p> + The examples above all use basic full-text term queries as both operands of + the set operations demonstrated. Phrase and NEAR queries may also be used, + as may the results of other set operations. When more than one set operation + is present in an FTS query, the precedence of operators is as follows: + +</p><table striped="1" style="margin:1em auto; width:80%; border-spacing:0"> + <tr style="text-align:left"><th>Operator</th><th>Enhanced Query Syntax Precedence + </th></tr><tr style="text-align:left;background-color:#DDDDDD"><td>NOT </td><td> Highest precedence (tightest grouping). + </td></tr><tr style="text-align:left"><td>AND </td><td> + </td></tr><tr style="text-align:left;background-color:#DDDDDD"><td>OR </td><td> Lowest precedence (loosest grouping). +</td></tr></table> + +<p> + When using the enhanced query syntax, parenthesis may be used to override + the default precedence of the various operators. For example: + +</p><div class="codeblock"><pre><i>-- Return the docid values associated with all documents that contain the</i> +<i>-- two terms "sqlite" and "database", and/or contain the term "library".</i> +SELECT docid FROM docs WHERE docs MATCH 'sqlite AND database OR library'; + +<i>-- This query is equivalent to the above.</i> +SELECT docid FROM docs WHERE docs MATCH 'sqlite AND database' + UNION +SELECT docid FROM docs WHERE docs MATCH 'library'; + +<i>-- Query for the set of documents that contains the term "linux", and at least</i> +<i>-- one of the phrases "sqlite database" and "sqlite library".</i> +SELECT docid FROM docs WHERE docs MATCH '("sqlite database" OR "sqlite library") AND linux'; + +<i>-- This query is equivalent to the above.</i> +SELECT docid FROM docs WHERE docs MATCH 'linux' + INTERSECT +SELECT docid FROM ( + SELECT docid FROM docs WHERE docs MATCH '"sqlite library"' + UNION + SELECT docid FROM docs WHERE docs MATCH '"sqlite database"' +); +</pre></div> + + +<h2 id="set_operations_using_the_standard_query_syntax"><span>3.2. </span>Set Operations Using The Standard Query Syntax</h2> + +<p> + FTS query set operations using the standard query syntax are similar, but + not identical, to set operations with the enhanced query syntax. There + are four differences, as follows: + +</p><ol> + <li value="1"><p> Only the implicit version of the AND operator is supported. + Specifying the string "AND" as part of a standard query syntax query is + interpreted as a term query for the set of documents containing the term + "and". +</p></li></ol> + +<ol> + <li value="2"><p> Parenthesis are not supported. +</p></li></ol> + +<ol> + <li value="3"><p> The NOT operator is not supported. Instead of the NOT + operator, the standard query syntax supports a unary "-" operator that + may be applied to basic term and term-prefix queries (but not to phrase + or NEAR queries). A term or term-prefix that has a unary "-" operator + attached to it may not appear as an operand to an OR operator. An FTS + query may not consist entirely of terms or term-prefix queries with unary + "-" operators attached to them. +</p></li></ol> + +<div class="codeblock"><pre><i>-- Search for the set of documents that contain the term "sqlite" but do</i> +<i>-- not contain the term "database".</i> +SELECT * FROM docs WHERE docs MATCH 'sqlite -database'; +</pre></div> + +<ol> + <li value="4"><p> The relative precedence of the set operations is different. + In particular, using the standard query syntax the "OR" operator has a + higher precedence than "AND". The precedence of operators when using the + standard query syntax is: +</p></li></ol> + +<table striped="1" style="margin:1em auto; width:80%; border-spacing:0"> + <tr style="text-align:left"><th>Operator</th><th>Standard Query Syntax Precedence + </th></tr><tr style="text-align:left;background-color:#DDDDDD"><td>Unary "-" </td><td> Highest precedence (tightest grouping). + </td></tr><tr style="text-align:left"><td>OR </td><td> + </td></tr><tr style="text-align:left;background-color:#DDDDDD"><td>AND </td><td> Lowest precedence (loosest grouping). +</td></tr></table> + +<ol><li style="list-style:none"> + The following example illustrates precedence of operators using the standard + query syntax: +</li></ol> + +<div class="codeblock"><pre><i>-- Search for documents that contain at least one of the terms "database"</i> +<i>-- and "sqlite", and also contain the term "library". Because of the differences</i> +<i>-- in operator precedences, this query would have a different interpretation using</i> +<i>-- the enhanced query syntax.</i> +SELECT * FROM docs WHERE docs MATCH 'sqlite OR database library'; +</pre></div> + +<a name="snippet"></a> + +<h1 id="auxiliary_functions_snippet_offsets_and_matchinfo"><span>4. </span>Auxiliary Functions - Snippet, Offsets and Matchinfo</h1> + +<p> + The FTS3 and FTS4 modules provide three special SQL scalar functions that may be useful + to the developers of full-text query systems: "snippet", "offsets" and + "matchinfo". The purpose of the "snippet" and "offsets" functions is to allow + the user to identify the location of queried terms in the returned documents. + The "matchinfo" function provides the user with metrics that may be useful + for filtering or sorting query results according to relevance. + +</p><p> + The first argument to all three special SQL scalar functions + must be the <a href="fts3.html#hiddencol">FTS hidden column</a> of the FTS table that the function is + applied to. The <a href="fts3.html#hiddencol">FTS hidden column</a> is an automatically-generated column found on + all FTS tables that has the same name as the FTS table itself. + For example, given an FTS table named "mail": + +</p><div class="codeblock"><pre>SELECT offsets(mail) FROM mail WHERE mail MATCH <full-text query expression>; +SELECT snippet(mail) FROM mail WHERE mail MATCH <full-text query expression>; +SELECT matchinfo(mail) FROM mail WHERE mail MATCH <full-text query expression>; +</pre></div> + +<p> + The three auxiliary functions are only useful within a SELECT statement that + uses the FTS table's full-text index. If used within a SELECT that uses + the "query by rowid" or "linear scan" strategies, then the snippet and + offsets both return an empty string, and the matchinfo function returns + a blob value zero bytes in size. + +<a name="matchable"></a> + +</p><p id="matchable"> + All three auxiliary functions extract a set of "matchable phrases" from + the FTS query expression to work with. The set of matchable phrases for + a given query consists of all phrases (including unquoted tokens and + token prefixes) in the expression except those that are prefixed with + a unary "-" operator (standard syntax) or are part of a sub-expression + that is used as the right-hand operand of a NOT operator. + +</p><p> + With the following provisos, each series of tokens in the FTS table that + matches one of the matchable phrases in the query expression is known as a + "phrase match": + +</p><ol> + <li> If a matchable phrase is part of a series of phrases connected by + NEAR operators in the FTS query expression, then each phrase match + must be sufficiently close to other phrase matches of the relevant + types to satisfy the NEAR condition. + + </li><li> If the matchable phrase in the FTS query is restricted to matching + data in a specified FTS table column, then only phrase matches that + occur within that column are considered. +</li></ol> + +<a name="offsets"></a> + +<h2 id="the_offsets_function"><span>4.1. </span>The Offsets Function</h2> + +<p> + For a SELECT query that uses the full-text index, the offsets() function + returns a text value containing a series of space-separated integers. For + each term in each <a href="#matchable">phrase match</a> of the current row, + there are four integers in the returned list. Each set of four integers is + interpreted as follows: + +</p><table striped="1" style="margin:1em auto; width:80%; border-spacing:0"> + <tr style="text-align:left"><th>Integer </th><th>Interpretation + </th></tr><tr style="text-align:left;background-color:#DDDDDD"><td>0 + </td><td>The column number that the term instance occurs in (0 for the + leftmost column of the FTS table, 1 for the next leftmost, etc.). + </td></tr><tr style="text-align:left"><td>1 + </td><td>The term number of the matching term within the full-text query + expression. Terms within a query expression are numbered starting + from 0 in the order that they occur. + </td></tr><tr style="text-align:left;background-color:#DDDDDD"><td>2 + </td><td>The byte offset of the matching term within the column. + </td></tr><tr style="text-align:left"><td>3 + </td><td>The size of the matching term in bytes. +</td></tr></table> + +<p> + The following block contains examples that use the offsets function. + +</p><div class="codeblock"><pre>CREATE VIRTUAL TABLE mail USING fts3(subject, body); +INSERT INTO mail VALUES('hello world', 'This message is a hello world message.'); +INSERT INTO mail VALUES('urgent: serious', 'This mail is seen as a more serious mail'); + +<i>-- The following query returns a single row (as it matches only the first</i> +<i>-- entry in table "mail". The text returned by the offsets function is</i> +<i>-- "0 0 6 5 1 0 24 5".</i> +<i>--</i> +<i>-- The first set of four integers in the result indicate that column 0</i> +<i>-- contains an instance of term 0 ("world") at byte offset 6. The term instance</i> +<i>-- is 5 bytes in size. The second set of four integers shows that column 1</i> +<i>-- of the matched row contains an instance of term 0 ("world") at byte offset</i> +<i>-- 24. Again, the term instance is 5 bytes in size.</i> +SELECT offsets(mail) FROM mail WHERE mail MATCH 'world'; + +<i>-- The following query returns also matches only the first row in table "mail".</i> +<i>-- In this case the returned text is "1 0 5 7 1 0 30 7".</i> +SELECT offsets(mail) FROM mail WHERE mail MATCH 'message'; + +<i>-- The following query matches the second row in table "mail". It returns the</i> +<i>-- text "1 0 28 7 1 1 36 4". Only those occurrences of terms "serious" and "mail"</i> +<i>-- that are part of an instance of the phrase "serious mail" are identified; the</i> +<i>-- other occurrences of "serious" and "mail" are ignored.</i> +SELECT offsets(mail) FROM mail WHERE mail MATCH '"serious mail"'; +</pre></div> + +<a name="snippet"></a> + +<h2 id="the_snippet_function"><span>4.2. </span>The Snippet Function</h2> + +<p> + The snippet function is used to create formatted fragments of document text + for display as part of a full-text query results report. The snippet function + may be passed between one and six arguments, as follows: + +</p><table striped="1" style="margin:1em auto; width:80%; border-spacing:0"> + <tr style="text-align:left"><th>Argument </th><th>Default Value </th><th>Description + </th></tr><tr style="text-align:left;background-color:#DDDDDD"><td>0 </td><td>N/A + </td><td> The first argument to the snippet function must always be the <a href="fts3.html#hiddencol">FTS hidden column</a> + of the FTS table being queried and from which the snippet is to be taken. The + <a href="fts3.html#hiddencol">FTS hidden column</a> is an automatically generated column with the same name as the + FTS table itself. + </td></tr><tr style="text-align:left"><td>1 </td><td>"<b>" + </td><td> The "start match" text. + </td></tr><tr style="text-align:left;background-color:#DDDDDD"><td>2 </td><td>"</b>" + </td><td> The "end match" text. + </td></tr><tr style="text-align:left"><td>3 </td><td>"<b>...</b>" + </td><td> The "ellipses" text. + </td></tr><tr style="text-align:left;background-color:#DDDDDD"><td>4 </td><td>-1 + </td><td> The FTS table column number to extract the returned fragments of + text from. Columns are numbered from left to right starting with + zero. A negative value indicates that the text may be extracted + from any column. + </td></tr><tr style="text-align:left"><td>5 </td><td>-15 + </td><td> The absolute value of this integer argument is used as the + (approximate) number of tokens to include in the returned text + value. The maximum allowable absolute value is 64. The value of + this argument is referred to as <i>N</i> in the discussion below. +</td></tr></table> + +<p> + The snippet function first attempts to find a fragment of text consisting + of <i>|N|</i> tokens within the current row that contains at least one phrase + match for each matchable phrase matched somewhere in the current row, + where <i>|N|</i> is the absolute value of the sixth argument passed to the + snippet function. If the text stored in a single column contains less than + <i>|N|</i> tokens, then the entire column value is considered. Text fragments + may not span multiple columns. + +</p><p> + If such a text fragment can be found, it is returned with the following + modifications: + +</p><ul> + <li> If the text fragment does not begin at the start of a column value, + the "ellipses" text is prepended to it. + </li><li> If the text fragment does not finish at the end of a column value, + the "ellipses" text is appended to it. + </li><li> For each token in the text fragment that is part of a phrase match, + the "start match" text is inserted into the fragment before the token, + and the "end match" text is inserted immediately after it. +</li></ul> + +<p> + If more than one such fragment can be found, then fragments that contain + a larger number of "extra" phrase matches are favored. The start of + the selected text fragment may be moved a few tokens forward or backward + to attempt to concentrate the phrase matches toward the center of the + fragment. + +</p><p> + Assuming <i>N</i> is a positive value, if no fragments can be found that + contain a phrase match corresponding to each matchable phrase, the snippet + function attempts to find two fragments of approximately <i>N</i>/2 tokens + that between them contain at least one phrase match for each matchable phrase + matched by the current row. If this fails, attempts are made to find three + fragments of <i>N</i>/3 tokens each and finally four <i>N</i>/4 token + fragments. If a set of four fragments cannot be found that encompasses the + required phrase matches, the four fragments of <i>N</i>/4 tokens that provide + the best coverage are selected. + +</p><p> + If <i>N</i> is a negative value, and no single fragment can be found + containing the required phrase matches, the snippet function searches + for two fragments of <i>|N|</i> tokens each, then three, then four. In + other words, if the specified value of <i>N</i> is negative, the sizes + of the fragments is not decreased if more than one fragment is required + to provide the desired phrase match coverage. + +</p><p> + After the <i>M</i> fragments have been located, where <i>M</i> is between + two and four as described in the paragraphs above, they are joined together + in sorted order with the "ellipses" text separating them. The three + modifications enumerated earlier are performed on the text before it is + returned. + +</p><div class="codeblock"><pre><b>Note: In this block of examples, newlines and whitespace characters have +been inserted into the document inserted into the FTS table, and the expected +results described in SQL comments. This is done to enhance readability only, +they would not be present in actual SQLite commands or output.</b> + +<i>-- Create and populate an FTS table.</i> +CREATE VIRTUAL TABLE text USING fts4(); +INSERT INTO text VALUES(' + During 30 Nov-1 Dec, 2-3oC drops. Cool in the upper portion, minimum temperature 14-16oC + and cool elsewhere, minimum temperature 17-20oC. Cold to very cold on mountaintops, + minimum temperature 6-12oC. Northeasterly winds 15-30 km/hr. After that, temperature + increases. Northeasterly winds 15-30 km/hr. +'); + +<i>-- The following query returns the text value:</i> +<i>--</i> +<i>-- "<b>...</b>cool elsewhere, minimum temperature 17-20oC. <b>Cold</b> to very </i> +<i>-- <b>cold</b> on mountaintops, minimum temperature 6<b>...</b>".</i> +<i>--</i> +SELECT snippet(text) FROM text WHERE text MATCH 'cold'; + +<i>-- The following query returns the text value:</i> +<i>--</i> +<i>-- "...the upper portion, [minimum] [temperature] 14-16oC and cool elsewhere,</i> +<i>-- [minimum] [temperature] 17-20oC. Cold..."</i> +<i>--</i> +SELECT snippet(text, '[', ']', '...') FROM text WHERE text MATCH '"min* tem*"' +</pre></div> + +<a name="matchinfo"></a> +<h2 id="matchinfo" tags="matchinfo"><span>4.3. </span>The Matchinfo Function</h2> + +<p> + The matchinfo function returns a blob value. If it is used within a query + that does not use the full-text index (a "query by rowid" or "linear scan"), + then the blob is zero bytes in size. Otherwise, the blob consists of zero + or more 32-bit unsigned integers in machine byte-order. The exact number + of integers in the returned array depends on both the query and the value + of the second argument (if any) passed to the matchinfo function. + +</p><p> + The matchinfo function is called with either one or two arguments. As for + all auxiliary functions, the first argument must be the special + <a href="fts3.html#hiddencol">FTS hidden column</a>. The second argument, if it is specified, must be a text value + comprised only of the characters 'p', 'c', 'n', 'a', 'l', 's', 'x', 'y' and 'b'. + If no second argument is explicitly supplied, it defaults to "pcx". The + second argument is referred to as the "format string" below. + +</p><p> + Characters in the matchinfo format string are processed from left to right. + Each character in the format string causes one or more 32-bit unsigned + integer values to be added to the returned array. The "values" column in + the following table contains the number of integer values appended to the + output buffer for each supported format string character. In the formula + given, <i>cols</i> is the number of columns in the FTS table, and + <i>phrases</i> is the number of <a href="#matchable">matchable phrases</a> in + the query. + +</p><table striped="1" style="margin:1em auto; width:80%; border-spacing:0"> + <tr style="text-align:left"><th>Character</th><th>Values</th><th>Description + </th></tr><tr style="text-align:left;background-color:#DDDDDD"><td>p </td><td>1 </td><td>The number of matchable phrases in the query. + </td></tr><tr style="text-align:left"><td>c </td><td>1 </td><td>The number of user defined columns in the FTS + table (i.e. not including the docid or the <a href="fts3.html#hiddencol">FTS hidden column</a>). + </td></tr><tr style="text-align:left;background-color:#DDDDDD"><td>x </td><td style="white-space:nowrap">3 * <i>cols</i> * <i>phrases</i> + </td><td><a name="matchinfo-x"></a> + + For each distinct combination of a phrase and table column, the + following three values: + <ul> + <li> In the current row, the number of times the phrase appears in + the column. + </li><li> The total number of times the phrase appears in the column in + all rows in the FTS table. + </li><li> The total number of rows in the FTS table for which the + column contains at least one instance of the phrase. + </li></ul> + The first set of three values corresponds to the left-most column + of the table (column 0) and the left-most matchable phrase in the + query (phrase 0). If the table has more than one column, the second + set of three values in the output array correspond to phrase 0 and + column 1. Followed by phrase 0, column 2 and so on for all columns of + the table. And so on for phrase 1, column 0, then phrase 1, column 1 + etc. In other words, the data for occurrences of phrase <i>p</i> in + column <i>c</i> may be found using the following formula: +<pre> + hits_this_row = array[3 * (c + p*cols) + 0] + hits_all_rows = array[3 * (c + p*cols) + 1] + docs_with_hits = array[3 * (c + p*cols) + 2] +</pre> + </td></tr><tr style="text-align:left"><td>y</td><td style="white-space:nowrap"><i>cols</i> * <i>phrases</i> + </td><td><a name="matchinfo-y"></a> + + For each distinct combination of a phrase and table column, the + number of usable phrase matches that appear in the column. This is + usually identical to the first value in each set of three returned by the + <a href="fts3.html#matchinfo-x">matchinfo 'x' flag</a>. However, the number of hits reported by the + 'y' flag is zero for any phrase that is part of a sub-expression + that does not match the current row. This makes a difference for + expressions that contain AND operators that are descendants of OR + operators. For example, consider the expression: +<pre> + a OR (b AND c) +</pre> + and the document: +<pre> + "a c d" +</pre> + The <a href="fts3.html#matchinfo-x">matchinfo 'x' flag</a> would report a single hit for the phrases "a" and "c". + However, the 'y' directive reports the number of hits for "c" as zero, as + it is part of a sub-expression that does not match the document - (b AND c). + For queries that do not contain AND operators descended from OR + operators, the result values returned by 'y' are always the same as + those returned by 'x'. + +<p style="margin-left:0;margin-right:0"> + The first value in the array of integer values corresponds to the + leftmost column of the table (column 0) and the first phrase in the query + (phrase 0). The values corresponding to other column/phrase combinations + may be located using the following formula: + +</p><pre> + hits_for_phrase_p_column_c = array[c + p*cols] +</pre> + For queries that use OR expressions, or those that use LIMIT or return + many rows, the 'y' matchinfo option may be faster than 'x'. + +</td></tr><tr style="text-align:left;background-color:#DDDDDD"><td>b</td><td style="white-space:nowrap"><i>((cols+31)/32)</i> * <i>phrases</i> +</td><td><a name="matchinfo-b"></a> + + + The matchinfo 'b' flag provides similar information to the + <a href="fts3.html#matchinfo-y">matchinfo 'y' flag</a>, but in a more + compact form. Instead of the precise number of hits, 'b' provides a single + boolean flag for each phrase/column combination. If the phrase is present in + the column at least once (i.e. if the corresponding integer output of 'y' would + be non-zero), the corresponding flag is set. Otherwise cleared. + +<p style="margin-left:0;margin-right:0"> + If the table has 32 or fewer columns, a single unsigned integer is output for + each phrase in the query. The least significant bit of the integer is set if the + phrase appears at least once in column 0. The second least significant bit is + set if the phrase appears once or more in column 1. And so on. + +</p><p style="margin-left:0;margin-right:0"> + If the table has more than 32 columns, an extra integer is added to the output + of each phrase for each extra 32 columns or part thereof. Integers + corresponding to the same phrase are clumped together. For example, if a table + with 45 columns is queried for two phrases, 4 integers are output. The first + corresponds to phrase 0 and columns 0-31 of the table. The second integer + contains data for phrase 0 and columns 32-44, and so on. + +</p><p style="margin-left:0;margin-right:0"> + For example, if nCol is the number of columns in the table, to determine if + phrase p is present in column c: + +</p><pre> + p_is_in_c = array[p * ((nCol+31)/32)] & (1 << (c % 32)) +</pre> + + </td></tr><tr style="text-align:left"><td>n </td><td>1 </td><td>The number of rows in the FTS4 table. This value is + only available when querying FTS4 tables, not FTS3. + </td></tr><tr style="text-align:left;background-color:#DDDDDD"><td>a </td><td><i>cols</i> </td><td>For each column, the average number of + tokens in the text values stored in the column (considering all rows in + the FTS4 table). This value is only available when querying FTS4 tables, + not FTS3. + </td></tr><tr style="text-align:left"><td>l </td><td><i>cols</i> </td><td> + For each column, the length of the value stored in the current row of the + FTS4 table, in tokens. This value is only available when querying + FTS4 tables, not FTS3. And only if the "matchinfo=fts3" directive was not + specified as part of the "CREATE VIRTUAL TABLE" statement used to create + the FTS4 table. + </td></tr><tr style="text-align:left;background-color:#DDDDDD"><td>s </td><td><i>cols</i> </td><td>For each column, the length of the longest + subsequence of phrase matches that the column value has in common + with the query text. For example, if a table column contains the text + 'a b c d e' and the query is 'a c "d e"', then the length of the longest + common subsequence is 2 (phrase "c" followed by phrase "d e"). + + +</td></tr></table> + +<p> + For example: + +</p><div class="codeblock"><pre><i>-- Create and populate an FTS4 table with two columns:</i> +CREATE VIRTUAL TABLE t1 USING fts4(a, b); +INSERT INTO t1 VALUES('transaction default models default', 'Non transaction reads'); +INSERT INTO t1 VALUES('the default transaction', 'these semantics present'); +INSERT INTO t1 VALUES('single request', 'default data'); + +<i>-- In the following query, no format string is specified and so it defaults</i> +<i>-- to "pcx". It therefore returns a single row consisting of a single blob</i> +<i>-- value 80 bytes in size (20 32-bit integers - 1 for "p", 1 for "c" and</i> +<i>-- 3*2*3 for "x"). If each block of 4 bytes in</i> the blob is interpreted +<i>-- as an unsigned integer in machine byte-order, the values will be:</i> +<i>--</i> +<i>-- 3 2 1 3 2 0 1 1 1 2 2 0 1 1 0 0 0 1 1 1</i> +<i>--</i> +<i>-- The row returned corresponds to the second entry inserted into table t1.</i> +<i>-- The first two integers in the blob show that the query contained three</i> +<i>-- phrases and the table being queried has two columns. The next block of</i> +<i>-- three integers describes column 0 (in this case column "a") and phrase</i> +<i>-- 0 (in this case "default"). The current row contains 1 hit for "default"</i> +<i>-- in column 0, of a total of 3 hits for "default" that occur in column</i> +<i>-- 0 of any table row. The 3 hits are spread across 2 different rows.</i> +<i>--</i> +<i>-- The next set of three integers (0 1 1) pertain to the hits for "default"</i> +<i>-- in column 1 of the table (0 in this row, 1 in all rows, spread across </i> +<i>-- 1 rows).</i> +<i>--</i> +SELECT matchinfo(t1) FROM t1 WHERE t1 MATCH 'default transaction "these semantics"'; + +<i>-- The format string for this query is "ns". The output array will therefore</i> +<i>-- contain 3 integer values - 1 for "n" and 2 for "s". The query returns</i> +<i>-- two rows (the first two rows in the table match). The values returned are:</i> +<i>--</i> +<i>-- 3 1 1</i> +<i>-- 3 2 0</i> +<i>--</i> +<i>-- The first value in the matchinfo array returned for both rows is 3 (the </i> +<i>-- number of rows in the table). The following two values are the lengths </i> +<i>-- of the longest common subsequence of phrase matches in each column.</i> +SELECT matchinfo(t1, 'ns') FROM t1 WHERE t1 MATCH 'default transaction'; +</pre></div> + +<p> + The matchinfo function is much faster than either the snippet or offsets + functions. This is because the implementation of both snippet and offsets + is required to retrieve the documents being analyzed from disk, whereas + all data required by matchinfo is available as part of the same portions + of the full-text index that are required to implement the full-text query + itself. This means that of the following two queries, the first may be + an order of magnitude faster than the second: + +</p><div class="codeblock"><pre>SELECT docid, matchinfo(tbl) FROM tbl WHERE tbl MATCH <query expression>; +SELECT docid, offsets(tbl) FROM tbl WHERE tbl MATCH <query expression>; +</pre></div> + +<p> + The matchinfo function provides all the information required to calculate + probabilistic "bag-of-words" relevancy scores such as + <a href="http://en.wikipedia.org/wiki/Okapi_BM25">Okapi BM25/BM25F</a> that may + be used to order results in a full-text search application. Appendix A of this + document, "<a href="fts3.html#appendix_a">search application tips</a>", contains an example of using the + matchinfo() function efficiently. + +</p><a name="fts4aux"></a> +<h1 id="fts4aux" tags="fts4aux"><span>5. </span>Fts4aux - Direct Access to the Full-Text Index</h1> + +<p> + As of <a href="releaselog/3_7_6.html">version 3.7.6</a> (2011-04-12), + SQLite includes a new virtual table module called + "fts4aux", which can be used to inspect the full-text index of an existing + FTS table directly. Despite its name, fts4aux works just as well with FTS3 + tables as it does with FTS4 tables. Fts4aux tables are read-only. The only + way to modify the contents of an fts4aux table is by modifying the + contents of the associated FTS table. The fts4aux module is automatically + included in all <a href="fts3.html#compiling_and_enabling_fts3_and_fts4">builds that include FTS</a>. + +</p><p> + An fts4aux virtual table is constructed with one or two arguments. When + used with a single argument, that argument is the unqualified name of the + FTS table that it will be used to access. To access a table in a different + database (for example, to create a TEMP fts4aux table that will access an + FTS3 table in the MAIN database) use the two-argument form and give the + name of the target database (ex: "main") in the first argument and the name + of the FTS3/4 table as the second argument. (The two-argument form of + fts4aux was added for SQLite <a href="releaselog/3_7_17.html">version 3.7.17</a> (2013-05-20) + and will throw an error in prior releases.) + For example: + +</p><div class="codeblock"><pre><i>-- Create an FTS4 table</i> +CREATE VIRTUAL TABLE ft USING fts4(x, y); + +<i>-- Create an fts4aux table to access the full-text index for table "ft"</i> +CREATE VIRTUAL TABLE ft_terms USING fts4aux(ft); + +<i>-- Create a TEMP fts4aux table accessing the "ft" table in "main"</i> +CREATE VIRTUAL TABLE temp.ft_terms_2 USING fts4aux(main,ft); +</pre></div> + +<p> + For each term present in the FTS table, there are between 2 and N+1 rows + in the fts4aux table, where N is the number of user-defined columns in + the associated FTS table. An fts4aux table always has the same four columns, + as follows, from left to right: + +</p><table striped="1" style="margin:1em auto; width:80%; border-spacing:0"> + <tr style="text-align:left"><th>Column Name</th><th>Column Contents + </th></tr><tr style="text-align:left;background-color:#DDDDDD"><td>term</td><td> + Contains the text of the term for this row. + </td></tr><tr style="text-align:left"><td>col</td><td> + This column may contain either the text value '*' (i.e. a single + character, U+002a) or an integer between 0 and N-1, where N is + again the number of user-defined columns in the corresponding FTS table. + + </td></tr><tr style="text-align:left;background-color:#DDDDDD"><td>documents</td><td> + This column always contains an integer value greater than zero. + <br><br> + If the "col" column contains the value '*', then this column + contains the number of rows of the FTS table that contain at least one + instance of the term (in any column). If col contains an integer + value, then this column contains the number of rows of the FTS table that + contain at least one instance of the term in the column identified by + the col value. As usual, the columns of the FTS table are numbered + from left to right, starting with zero. + + </td></tr><tr style="text-align:left"><td>occurrences</td><td> + This column also always contains an integer value greater than zero. + <br><br> + If the "col" column contains the value '*', then this column + contains the total number of instances of the term in all rows of the + FTS table (in any column). Otherwise, if col contains an integer + value, then this column contains the total number of instances of the + term that appear in the FTS table column identified by the col + value. + + </td></tr><tr style="text-align:left;background-color:#DDDDDD"><td>languageid <i>(hidden)</i></td><td> + <a name="f4alid"></a> + + This column determines which <a href="fts3.html#*fts4languageid">languageid</a> is used to + extract vocabulary from the FTS3/4 table. + <br><br> + The default value for languageid is 0. If an alternative language + is specified in WHERE clause constraints, then that alternative is + used instead of 0. There can only be a single languageid per query. + In other words, the WHERE clause cannot contain a range constraint + or IN operator on the languageid. +</td></tr></table> + +<p> + For example, using the tables created above: + +</p><div class="codeblock"><pre>INSERT INTO ft(x, y) VALUES('Apple banana', 'Cherry'); +INSERT INTO ft(x, y) VALUES('Banana Date Date', 'cherry'); +INSERT INTO ft(x, y) VALUES('Cherry Elderberry', 'Elderberry'); + +<i>-- The following query returns this data:</i> +<i>--</i> +<i>-- apple | * | 1 | 1</i> +<i>-- apple | 0 | 1 | 1</i> +<i>-- banana | * | 2 | 2</i> +<i>-- banana | 0 | 2 | 2</i> +<i>-- cherry | * | 3 | 3</i> +<i>-- cherry | 0 | 1 | 1</i> +<i>-- cherry | 1 | 2 | 2</i> +<i>-- date | * | 1 | 2</i> +<i>-- date | 0 | 1 | 2</i> +<i>-- elderberry | * | 1 | 2</i> +<i>-- elderberry | 0 | 1 | 1</i> +<i>-- elderberry | 1 | 1 | 1</i> +<i>--</i> +SELECT term, col, documents, occurrences FROM ft_terms; +</pre></div> + +<p> + In the example, the values in the "term" column are all lower case, + even though they were inserted into table "ft" in mixed case. This is because + an fts4aux table contains the terms as extracted from the document text + by the <a href="fts3.html#tokenizer">tokenizer</a>. In this case, since table "ft" uses the + <a href="fts3.html#tokenizer">simple tokenizer</a>, this means all terms have been folded to + lower case. Also, there is (for example) no row with column "term" + set to "apple" and column "col" set to 1. Since there are no instances + of the term "apple" in column 1, no row is present in the fts4aux table. + +</p><p> + During a transaction, some of the data written to an FTS table may be + cached in memory and written to the database only when the transaction is + committed. However the implementation of the fts4aux module is only able + to read data from the database. In practice this means that if an fts4aux + table is queried from within a transaction in which the associated + FTS table has been modified, the results of the query are likely to reflect + only a (possibly empty) subset of the changes made. + +</p><a name="fts4_options"></a> +<h1 id="fts4_options" tags="FTS4 options"><span>6. </span>FTS4 Options</h1> + +<p> + If the "CREATE VIRTUAL TABLE" statement specifies module FTS4 (not FTS3), + then special directives - FTS4 options - similar to the "tokenize=*" option + may also appear in place of column names. An FTS4 option consists of the + option name, followed by an "=" character, followed by the option value. + The option value may optionally be enclosed in single or double quotes, with + embedded quote characters escaped in the same way as for SQL literals. There + may not be whitespace on either side of the "=" character. For example, + to create an FTS4 table with the value of option "matchinfo" set to "fts3": + +</p><div class="codeblock"><pre><i>-- Create a reduced-footprint FTS4 table.</i> +CREATE VIRTUAL TABLE papers USING fts4(author, document, matchinfo=fts3); +</pre></div> + +<p> + FTS4 currently supports the following options: + +</p><table striped="1" style="margin:1em auto; width:80%; border-spacing:0"> + <tr style="text-align:left"><th>Option</th><th>Interpretation + </th></tr><tr style="text-align:left;background-color:#DDDDDD"><td>compress</td><td> + The compress option is used to specify the compress function. It is an error to + specify a compress function without also specifying an uncompress + function. <a href="fts3.html#the_compress_and_uncompress_options">See below</a> for details. + + </td></tr><tr style="text-align:left"><td>content</td><td> + The content allows the text being indexed to be + stored in a separate table distinct from the FTS4 table, + or even outside of SQLite. + + </td></tr><tr style="text-align:left;background-color:#DDDDDD"><td>languageid</td><td> + The languageid option causes the FTS4 table to have an additional hidden + integer column that identifies the language of the text contained in + each row. The use of the languageid option allows the same FTS4 table + to hold text in multiple languages or scripts, each with different tokenizer + rules, and to query each language independently of the others. + + </td></tr><tr style="text-align:left"><td>matchinfo</td><td> + When set to the value "fts3", the matchinfo option reduces the amount of + information stored by FTS4 with the consequence that the "l" option of + <a href="fts3.html#matchinfo">matchinfo()</a> is no longer available. + + </td></tr><tr style="text-align:left;background-color:#DDDDDD"><td>notindexed</td><td> + This option is used to specify the name of a column for which data is + not indexed. Values stored in columns that are not indexed are not + matched by MATCH queries. Nor are they recognized by auxiliary functions. + A single CREATE VIRTUAL TABLE statement may have any number of notindexed + options. + + </td></tr><tr style="text-align:left"><td>order</td><td> + <a name="fts4order"></a> + + The "order" option may be set to either "DESC" or "ASC" (in upper or + lower case). If it is set to "DESC", then FTS4 stores its data in such + a way as to optimize returning results in descending order by docid. + If it is set to "ASC" (the default), then the data structures are + optimized for returning results in ascending order by docid. In other + words, if many of the queries run against the FTS4 table use "ORDER BY + docid DESC", then it may improve performance to add the "order=desc" + option to the CREATE VIRTUAL TABLE statement. + + </td></tr><tr style="text-align:left;background-color:#DDDDDD"><td>prefix</td><td> + This option may be set to a comma-separated list of positive non-zero + integers. For each integer N in the list, a separate index is created + in the database file to optimize <a href="fts3.html#termprefix">prefix queries</a> where + the query term is N bytes in length, not including the '*' character, + when encoded using UTF-8. <a href="fts3.html#the_prefix_option">See below</a> for details. + + </td></tr><tr style="text-align:left"><td>uncompress</td><td> + This option is used to specify the uncompress function. It is an error to + specify an uncompress function without also specifying a compress + function. <a href="fts3.html#the_compress_and_uncompress_options">See below</a> for details. +</td></tr></table> + +<p> + When using FTS4, specifying a column name that contains an "=" character + and is not either a "tokenize=*" specification or a recognized FTS4 option + is an error. With FTS3, the first token in the unrecognized directive is + interpreted as a column name. Similarly, specifying multiple "tokenize=*" + directives in a single table declaration is an error when using FTS4, whereas + the second and subsequent "tokenize=*" directives are interpreted as column + names by FTS3. For example: + +</p><div class="codeblock"><pre><i>-- An error. FTS4 does not recognize the directive "xyz=abc".</i> +CREATE VIRTUAL TABLE papers USING fts4(author, document, xyz=abc); + +<i>-- Create an FTS3 table with three columns - "author", "document"</i> +<i>-- and "xyz".</i> +CREATE VIRTUAL TABLE papers USING fts3(author, document, xyz=abc); + +<i>-- An error. FTS4 does not allow multiple tokenize=* directives</i> +CREATE VIRTUAL TABLE papers USING fts4(tokenize=porter, tokenize=simple); + +<i>-- Create an FTS3 table with a single column named "tokenize". The</i> +<i>-- table uses the "porter" tokenizer.</i> +CREATE VIRTUAL TABLE papers USING fts3(tokenize=porter, tokenize=simple); + +<i>-- An error. Cannot create a table with two columns named "tokenize".</i> +CREATE VIRTUAL TABLE papers USING fts3(tokenize=porter, tokenize=simple, tokenize=icu); +</pre></div> + +<a name="*fts4compression"></a> + +<a name="the_compress_and_uncompress_options"></a> +<h2 tags="fts4 compress option" id="the_compress_and_uncompress_options"><span>6.1. </span>The compress= and uncompress= options</h2> + +<p> + The compress and uncompress options allow FTS4 content to be stored in + the database in a compressed form. Both options should be set to the name + of an SQL scalar function registered using <a href="c3ref/create_function.html">sqlite3_create_function()</a> + that accepts a single argument. + +</p><p> + The compress function should return a compressed version of the value + passed to it as an argument. Each time data is written to the FTS4 table, + each column value is passed to the compress function and the result value + stored in the database. The compress function may return any type of SQLite + value (blob, text, real, integer or null). + +</p><p> + The uncompress function should uncompress data previously compressed by + the compress function. In other words, for all SQLite values X, it should + be true that uncompress(compress(X)) equals X. When data that has been + compressed by the compress function is read from the database by FTS4, it + is passed to the uncompress function before it is used. + +</p><p> + If the specified compress or uncompress functions do not exist, the table + may still be created. An error is not returned until the FTS4 table is + read (if the uncompress function does not exist) or written (if it is the + compress function that does not exist). + +</p><div class="codeblock"><pre><i>-- Create an FTS4 table that stores data in compressed form. This</i> +<i>-- assumes that the scalar functions zip() and unzip() have been (or</i> +<i>-- will be) added to the database handle.</i> +CREATE VIRTUAL TABLE papers USING fts4(author, document, compress=zip, uncompress=unzip); +</pre></div> + +<p> + When implementing the compress and uncompress functions it is important to + pay attention to data types. Specifically, when a user reads a value from + a compressed FTS table, the value returned by FTS is exactly the same + as the value returned by the uncompress function, including the data type. + If that data type is not the same as the data type of the original value as + passed to the compress function (for example if the uncompress function is + returning BLOB when compress was originally passed TEXT), then the users + query may not function as expected. + +<a name="*fts4content"></a> + +</p><a name="the_content_option_"></a> +<h2 tags="fts4 content option" id="the_content_option_"><span>6.2. </span>The content= option </h2> + +<p> + The content option allows FTS4 to forego storing the text being indexed. + The content option can be used in two ways: + +</p><ul> +<li><p> The indexed documents are not stored within the SQLite database + at all (a "contentless" FTS4 table), or + +</p></li><li><p> The indexed documents are stored in a database table created and + managed by the user (an "external content" FTS4 table). +</p></li></ul> + +<p> + Because the indexed documents themselves are usually much larger than + the full-text index, the content option can be used to achieve + significant space savings. + +</p><a name="_contentless_fts4_tables_"></a> +<h3 tags="contentless fts4 tables" id="_contentless_fts4_tables_"><span>6.2.1. </span> Contentless FTS4 Tables </h3> + +<p> + In order to create an FTS4 table that does not store a copy of the indexed + documents at all, the content option should be set to an empty string. + For example, the following SQL creates such an FTS4 table with three + columns - "a", "b", and "c": + +</p><div class="codeblock"><pre>CREATE VIRTUAL TABLE t1 USING fts4(content="", a, b, c); +</pre></div> + +<p> + Data can be inserted into such an FTS4 table using an INSERT statements. + However, unlike ordinary FTS4 tables, the user must supply an explicit + integer docid value. For example: + +</p><div class="codeblock"><pre><i>-- This statement is Ok:</i> +INSERT INTO t1(docid, a, b, c) VALUES(1, 'a b c', 'd e f', 'g h i'); + +<i>-- This statement causes an error, as no docid value has been provided:</i> +INSERT INTO t1(a, b, c) VALUES('j k l', 'm n o', 'p q r'); +</pre></div> + +<p> + It is not possible to UPDATE or DELETE a row stored in a contentless FTS4 + table. Attempting to do so is an error. + +</p><p> + Contentless FTS4 tables also support SELECT statements. However, it is + an error to attempt to retrieve the value of any table column other than + the docid column. The auxiliary function matchinfo() may be used, but + snippet() and offsets() may not. For example: + +</p><div class="codeblock"><pre><i>-- The following statements are Ok:</i> +SELECT docid FROM t1 WHERE t1 MATCH 'xxx'; +SELECT docid FROM t1 WHERE a MATCH 'xxx'; +SELECT matchinfo(t1) FROM t1 WHERE t1 MATCH 'xxx'; + +<i>-- The following statements all cause errors, as the value of columns</i> +<i>-- other than docid are required to evaluate them.</i> +SELECT * FROM t1; +SELECT a, b FROM t1 WHERE t1 MATCH 'xxx'; +SELECT docid FROM t1 WHERE a LIKE 'xxx%'; +SELECT snippet(t1) FROM t1 WHERE t1 MATCH 'xxx'; +</pre></div> + +<p> + Errors related to attempting to retrieve column values other than docid + are runtime errors that occur within sqlite3_step(). In some cases, for + example if the MATCH expression in a SELECT query matches zero rows, there + may be no error at all even if a statement does refer to column values + other than docid. + +</p><a name="_external_content_fts4_tables_"></a> +<h3 tags="external content fts4 tables" id="_external_content_fts4_tables_"><span>6.2.2. </span> External Content FTS4 Tables </h3> + +<p> + An "external content" FTS4 table is similar to a contentless table, except + that if evaluation of a query requires the value of a column other than + docid, FTS4 attempts to retrieve that value from a table (or view, or + virtual table) nominated by the user (hereafter referred to as the "content + table"). The FTS4 module never writes to the content table, and writing + to the content table does not affect the full-text index. It is the + responsibility of the user to ensure that the content table and the + full-text index are consistent. + +</p><p> + An external content FTS4 table is created by setting the content option + to the name of a table (or view, or virtual table) that may be queried by + FTS4 to retrieve column values when required. If the nominated table does + not exist, then an external content table behaves in the same way as + a contentless table. For example: + +</p><div class="codeblock"><pre>CREATE TABLE t2(id INTEGER PRIMARY KEY, a, b, c); +CREATE VIRTUAL TABLE t3 USING fts4(content="t2", a, c); +</pre></div> + +<p> + Assuming the nominated table does exist, then its columns must be the same + as or a superset of those defined for the FTS table. The external table + must also be in the same database file as the FTS table. In other words, + The external table cannot be in a different database file connected using + <a href="lang_attach.html">ATTACH</a> nor may one of the FTS table and the external content be in the + TEMP database when the other is in a persistent database file such as MAIN. + +</p><p> + When a users query on the FTS table requires a column value other than + docid, FTS attempts to read the requested value from the corresponding column of + the row in the content table with a rowid value equal to the current FTS + docid. Only the subset of content-table columns duplicated in the FTS/34 + table declaration can be queried for - to retrieve values from any other + columns the content table must be queried directly. Or, if such a row cannot + be found in the content table, a NULL value is used instead. For example: + +</p><div class="codeblock"><pre>CREATE TABLE t2(id INTEGER PRIMARY KEY, a, b, c); +CREATE VIRTUAL TABLE t3 USING fts4(content="t2", b, c); + +INSERT INTO t2 VALUES(2, 'a b', 'c d', 'e f'); +INSERT INTO t2 VALUES(3, 'g h', 'i j', 'k l'); +INSERT INTO t3(docid, b, c) SELECT id, b, c FROM t2; +<i>-- The following query returns a single row with two columns containing +-- the text values "i j" and "k l". +-- +-- The query uses the full-text index to discover that the MATCH +-- term matches the row with docid=3. It then retrieves the values +-- of columns b and c from the row with rowid=3 in the content table +-- to return. +--</i> +SELECT * FROM t3 WHERE t3 MATCH 'k'; + +<i>-- Following the UPDATE, the query still returns a single row, this +-- time containing the text values "xxx" and "yyy". This is because the +-- full-text index still indicates that the row with docid=3 matches +-- the FTS4 query 'k', even though the documents stored in the content +-- table have been modified. +--</i> +UPDATE t2 SET b = 'xxx', c = 'yyy' WHERE rowid = 3; +SELECT * FROM t3 WHERE t3 MATCH 'k'; + +<i>-- Following the DELETE below, the query returns one row containing two +-- NULL values. NULL values are returned because FTS is unable to find +-- a row with rowid=3 within the content table. +--</i> +DELETE FROM t2; +SELECT * FROM t3 WHERE t3 MATCH 'k'; +</pre></div> + +<p> + When a row is deleted from an external content FTS4 table, FTS4 needs to + retrieve the column values of the row being deleted from the content table. + This is so that FTS4 can update the full-text index entries for each token + that occurs within the deleted row to indicate that row has been + deleted. If the content table row cannot be found, or if it contains values + inconsistent with the contents of the FTS index, the results can be difficult + to predict. The FTS index may be left containing entries corresponding to the + deleted row, which can lead to seemingly nonsensical results being returned + by subsequent SELECT queries. The same applies when a row is updated, as + internally an UPDATE is the same as a DELETE followed by an INSERT. + +</p><p> + This means that in order to keep an FTS in sync with an external content + table, any UPDATE or DELETE operations must be applied first to the FTS + table, and then to the external content table. For example: + +</p><div class="codeblock"><pre>CREATE TABLE t1_real(id INTEGER PRIMARY KEY, a, b, c, d); +CREATE VIRTUAL TABLE t1_fts USING fts4(content="t1_real", b, c); + +<i>-- This works. When the row is removed from the FTS table, FTS retrieves +-- the row with rowid=123 and tokenizes it in order to determine the entries +-- that must be removed from the full-text index. +--</i> +DELETE FROM t1_fts WHERE rowid = 123; +DELETE FROM t1_real WHERE rowid = 123; + +--<i> This <b>does not work</b>. By the time the FTS table is updated, the row +-- has already been deleted from the underlying content table. As a result +-- FTS is unable to determine the entries to remove from the FTS index and +-- so the index and content table are left out of sync. +--</i> +DELETE FROM t1_real WHERE rowid = 123; +DELETE FROM t1_fts WHERE rowid = 123; +</pre></div> + +<p> + Instead of writing separately to the full-text index and the content table, + some users may wish to use database triggers to keep the full-text index + up to date with respect to the set of documents stored in the content table. + For example, using the tables from earlier examples: + +</p><div class="codeblock"><pre>CREATE TRIGGER t2_bu BEFORE UPDATE ON t2 BEGIN + DELETE FROM t3 WHERE docid=old.rowid; +END; +CREATE TRIGGER t2_bd BEFORE DELETE ON t2 BEGIN + DELETE FROM t3 WHERE docid=old.rowid; +END; + +CREATE TRIGGER t2_au AFTER UPDATE ON t2 BEGIN + INSERT INTO t3(docid, b, c) VALUES(new.rowid, new.b, new.c); +END; +CREATE TRIGGER t2_ai AFTER INSERT ON t2 BEGIN + INSERT INTO t3(docid, b, c) VALUES(new.rowid, new.b, new.c); +END; +</pre></div> + +<p> + The DELETE trigger must be fired before the actual delete takes place + on the content table. This is so that FTS4 can still retrieve the original + values in order to update the full-text index. And the INSERT trigger must + be fired after the new row is inserted, so as to handle the case where the + rowid is assigned automatically within the system. The UPDATE trigger must + be split into two parts, one fired before and one after the update of the + content table, for the same reasons. + +</p><p> + The <a href="fts3.html#*fts4rebuidcmd">FTS4 "rebuild" command</a> + deletes the entire full-text index and rebuilds it based on the current + set of documents in the content table. Assuming again that "t3" is the + name of the external content FTS4 table, the rebuild command looks like this: + +</p><div class="codeblock"><pre>INSERT INTO t3(t3) VALUES('rebuild'); +</pre></div> + +<p> + This command may also be used with ordinary FTS4 tables, for example if + the implementation of the tokenizer changes. It is an + error to attempt to rebuild the full-text index maintained by a contentless + FTS4 table, since no content will be available to do the rebuilding. + + +<a name="*fts4languageid"></a> + +</p><a name="the_languageid_option"></a> +<h2 tags="fts4 languageid option" id="the_languageid_option"><span>6.3. </span>The languageid= option</h2> + +<p> + When the languageid option is present, it specifies the name of + another <a href="vtab.html#hiddencol">hidden column</a> that is added to the FTS4 + table and which is used to specify the language stored in each row + of the FTS4 table. The name of the languageid hidden column must + be distinct from all other column names in the FTS4 table. Example: + +</p><div class="codeblock"><pre>CREATE VIRTUAL TABLE t1 USING fts4(x, y, languageid="lid") +</pre></div> + +<p> + The default value of a languageid column is 0. Any value inserted + into a languageid column is converted to a 32-bit (not 64) signed + integer. + +</p><p> + By default, FTS queries (those that use the MATCH operator) + consider only those rows with the languageid column set to 0. To + query for rows with other languageid values, a constraint of the + form "</p><language-id> = <integer>" must be added to the queries + WHERE clause. For example: + +<div class="codeblock"><pre>SELECT * FROM t1 WHERE t1 MATCH 'abc' AND lid=5; +</pre></div> + +<p> + It is not possible for a single FTS query to return rows with + different languageid values. The results of adding WHERE clauses + that use other operators (e.g. lid!=5, or lid<=5) are undefined. + +</p><p> + If the content option is used along with the languageid option, + then the named languageid column must exist in the content= table + (subject to the usual rules - if a query never needs to read the + content table then this restriction does not apply). + +</p><p> + When the languageid option is used, SQLite invokes the xLanguageid() + on the sqlite3_tokenizer_module object immediately after the object + is created in order to pass in the language id that the + tokenizer should use. The xLanguageid() method will never be called + more than once for any single tokenizer object. The fact that different + languages might be tokenized differently is one reason why no single + FTS query can return rows with different languageid values. + + + +<a name="fts4matchinfo"></a> + +</p><a name="the_matchinfo_option"></a> +<h2 tags="fts4 matchinfo option" id="the_matchinfo_option"><span>6.4. </span>The matchinfo= option</h2> + +<p> + The matchinfo option may only be set to the value "fts3". + Attempting to set matchinfo to anything other than "fts3" is an error. + If this option is specified, then some of the extra information stored by + FTS4 is omitted. This reduces the amount of disk space consumed by + an FTS4 table until it is almost the same as the amount that would + be used by the equivalent FTS3 table, but also means that the data + accessed by passing the 'l' flag to the <a href="fts3.html#matchinfo">matchinfo()</a> function is + not available. + +<a name="fts4notindexed"></a> + +</p><a name="the_notindexed_option"></a> +<h2 tags="fts4 notindexed option" id="the_notindexed_option"><span>6.5. </span>The notindexed= option</h2> + +<p> + Normally, the FTS module maintains an inverted index of all terms in + all columns of the table. This option is used to specify the name of + a column for which entries should not be added to the index. Multiple + "notindexed" options may be used to specify that multiple columns should + be omitted from the index. For example: + +</p><div class="codeblock"><pre><i>-- Create an FTS4 table for which only the contents of columns c2 and c4</i> +<i>-- are tokenized and added to the inverted index.</i> +CREATE VIRTUAL TABLE t1 USING fts4(c1, c2, c3, c4, notindexed=c1, notindexed=c3); +</pre></div> + +<p> + Values stored in unindexed columns are not eligible to match MATCH + operators. They do not influence the results of the offsets() or matchinfo() + auxiliary functions. Nor will the snippet() function ever return a + snippet based on a value stored in an unindexed column. + +<a name="fts4prefix"></a> + +</p><a name="the_prefix_option"></a> +<h2 tags="fts4 prefix option" id="the_prefix_option"><span>6.6. </span>The prefix= option</h2> + +<p> + The FTS4 prefix option causes FTS to index term prefixes of specified lengths + in the same way that it always indexes complete terms. The prefix option + must be set to a comma separated list of positive non-zero integers. + For each value N in the list, prefixes of length N bytes (when encoded + using UTF-8) are indexed. FTS4 uses term prefix indexes to speed up + <a href="fts3.html#termprefix">prefix queries</a>. The cost, of course, is that indexing term prefixes as + well as complete terms increases the database size and slows down write + operations on the FTS4 table. + +</p><p> + Prefix indexes may be used to optimize <a href="fts3.html#termprefix">prefix queries</a> in two cases. + If the query is for a prefix of N bytes, then a prefix index created + with "prefix=N" provides the best optimization. Or, if no "prefix=N" + index is available, a "prefix=N+1" index may be used instead. + Using a "prefix=N+1" index is less + efficient than a "prefix=N" index, but is better than no prefix index at all. + +</p><div class="codeblock"><pre><i>-- Create an FTS4 table with indexes to optimize 2 and 4 byte prefix queries.</i> +CREATE VIRTUAL TABLE t1 USING fts4(c1, c2, prefix="2,4"); + +<i>-- The following two queries are both optimized using the prefix indexes.</i> +SELECT * FROM t1 WHERE t1 MATCH 'ab*'; +SELECT * FROM t1 WHERE t1 MATCH 'abcd*'; + +<i>-- The following two queries are both partially optimized using the prefix</i> +<i>-- indexes. The optimization is not as pronounced as it is for the queries</i> +<i>-- above, but still an improvement over no prefix indexes at all.</i> +SELECT * FROM t1 WHERE t1 MATCH 'a*'; +SELECT * FROM t1 WHERE t1 MATCH 'abc*'; +</pre></div> + +<a name="*cmds"></a> + +<a name="commands"></a> +<h1 id="commands" tags="commands"><span>7. </span>Special Commands For FTS3 and FTS4</h1> + +<p> + Special INSERT operates can be used to issue commands to FTS3 and FTS4 tables. + Every FTS3 and FTS4 has a hidden, read-only column which is the same name as + the table itself. INSERTs into this hidden column are interpreted as commands + to the FTS3/4 table. For a table with the name "xyz" the following commands + are supported: + +</p><ul> +<li><p>INSERT INTO xyz(xyz) VALUES('optimize');</p> +</li><li><p>INSERT INTO xyz(xyz) VALUES('rebuild');</p> +</li><li><p>INSERT INTO xyz(xyz) VALUES('integrity-check');</p> +</li><li><p>INSERT INTO xyz(xyz) VALUES('merge=X,Y');</p> +</li><li><p>INSERT INTO xyz(xyz) VALUES('automerge=N');</p> +</li></ul> + +<a name="*fts4optcmd"></a> + +<h2 id="optimize"><span>7.1. </span>The "optimize" command</h2> + +<p> + The "optimize" command causes FTS3/4 to merge together all of its + inverted index b-trees into one large and complete b-tree. Doing + an optimize will make subsequent queries run faster since there are + fewer b-trees to search, and it may reduce disk usage by coalescing + redundant entries. However, for a large FTS table, running optimize + can be as expensive as running <a href="lang_vacuum.html">VACUUM</a>. The optimize command + essentially has to read and write the entire FTS table, resulting + in a large transaction. + +</p><p> + In batch-mode operation, where an FTS table is initially built up + using a large number of INSERT operations, then queried repeatedly + without further changes, it is often a good idea + to run "optimize" after the last INSERT and before the first query. + +<a name="*fts4rebuidcmd"></a> + +</p><h2 id="rebuild"><span>7.2. </span>The "rebuild" command</h2> + +<p> + The "rebuild" command causes SQLite to discard the entire FTS3/4 + table and then rebuild it again from original text. The concept + is similar to <a href="lang_reindex.html">REINDEX</a>, only that it applies to an + FTS3/4 table instead of an ordinary index. + +</p><p> + The "rebuild" command should be run whenever the implementation + of a custom tokenizer changes, so that all content can be retokenized. + The "rebuild" command is also useful when using the + <a href="fts3.html#*fts4content">FTS4 content option</a> after changes have been made to the original + content table. + +<a name="*fts4ickcmd"></a> + +</p><h2 id="integcheck"><span>7.3. </span>The "integrity-check" command</h2> + +<p> + The "integrity-check" command causes SQLite to read and verify + the accuracy of all inverted indices in an FTS3/4 table by comparing + those inverted indices against the original content. The + "integrity-check" command silently succeeds if the inverted + indices are all ok, but will fail with an SQLITE_CORRUPT error + if any problems are found. + +</p><p> + The "integrity-check" command is similar in concept to + <a href="pragma.html#pragma_integrity_check">PRAGMA integrity_check</a>. In a working system, the "integrity-command" + should always be successful. Possible causes of integrity-check + failures include: + </p><ul> + <li> The application has made changes to the <a href="fts3.html#*shadowtab">FTS shadow tables</a> + directly, without using the FTS3/4 virtual table, causing + the shadow tables to become out of sync with each other. + </li><li> Using the <a href="fts3.html#*fts4content">FTS4 content option</a> and failing to manually keep + the content in sync with the FTS4 inverted indices. + </li><li> Bugs in the FTS3/4 virtual table. (The "integrity-check" + command was original conceived as part of the test suite + for FTS3/4.) + </li><li> Corruption to the underlying SQLite database file. (See + documentation on <a href="howtocorrupt.html">how to corrupt</a> and SQLite database for + additional information.) + </li></ul> + +<a name="*fts4mergecmd"></a> + +<h2 id="mergecmd"><span>7.4. </span>The "merge=X,Y" command</h2> + +<p> + The "merge=X,Y" command (where X and Y are integers) causes SQLite + to do a limited amount of work toward merging the various inverted + index b-trees of an FTS3/4 table together into one large b-tree. + The X value is the target number of "blocks" to be merged, and Y is + the minimum number of b-tree segments on a level required before + merging will be applied to that level. The value of Y should + be between 2 and 16 with a recommended value of 8. The value of X + can be any positive integer but values on the order of 100 to 300 + are recommended. + +</p><p> + When an FTS table accumulates 16 b-tree segments at the same level, + the next INSERT into that table will cause all 16 segments to be + merged into a single b-tree segment at the next higher level. The + effect of these level merges is that most INSERTs into an FTS table + are very fast and take minimal memory, but an occasional INSERT is + slow and generates a large transaction because of the need to + do merging. This results in "spiky" performance of INSERTs. + +</p><p> + To avoid spiky INSERT performance, an application can run the + "merge=X,Y" command periodically, possibly in an idle thread or + idle process, to ensure that the FTS table never accumulates + too many b-tree segments at the same level. INSERT performance + spikes can generally be avoided, and performance of FTS3/4 can be + maximized, by running "merge=X,Y" after every few thousand + document inserts. Each "merge=X,Y" command will run in a separate + transaction (unless they are grouped together using <a href="lang_transaction.html">BEGIN</a>...<a href="lang_transaction.html">COMMIT</a>, + of course). The transactions can be kept small by choosing a value + for X in the range of 100 to 300. The idle thread that is running + the merge commands can know when it is done by checking the difference + in <a href="c3ref/total_changes.html">sqlite3_total_changes()</a> before and after each "merge=X,Y" + command and stopping the loop when the difference drops below two. + +<a name="*fts4automergecmd"></a> + +</p><h2 id="automerge""><span>7.5. </span>The "automerge=N" command</h2> + +<p> + The "automerge=N" command (where N is an integer between 0 and 15, + inclusive) is used to configure an FTS3/4 tables "automerge" parameter, + which controls automatic incremental inverted index merging. The default + automerge value for new tables is 0, meaning that automatic incremental + merging is completely disabled. If the value of the automerge parameter + is modified using the "automerge=N" command, the new parameter value is + stored persistently in the database and is used by all subsequently + established database connections. + +</p><p> + Setting the automerge parameter to a non-zero value enables automatic + incremental merging. This causes SQLite to do a small amount of inverted + index merging after every INSERT operation. The amount of merging + performed is designed so that the FTS3/4 table never reaches a point + where it has 16 segments at the same level and hence has to do a large + merge in order to complete an insert. In other words, automatic + incremental merging is designed to prevent spiky INSERT performance. + +</p><p> + The downside of automatic incremental merging is that it makes + every INSERT, UPDATE, and DELETE operation on an FTS3/4 table run + a little slower, since extra time must be used to do the incremental + merge. For maximum performance, it is recommended that applications + disable automatic incremental merge and instead use the + <a href="fts3.html#*fts4mergecmd">"merge" command</a> in an idle process to keep the inverted indices + well merged. But if the structure of an application does not easily + allow for idle processes, the use of automatic incremental merge is + a very reasonable fallback solution. + +</p><p> + The actual value of the automerge parameter determines the number of + index segments merged simultaneously by an automatic inverted index + merge. If the value is set to N, the system waits until there are at + least N segments on a single level before beginning to incrementally + merge them. Setting a lower value of N causes segments to be merged more + quickly, which may speed up full-text queries and, if the workload + contains UPDATE or DELETE operations as well as INSERTs, reduce the space + on disk consumed by the full-text index. However, it also increases the + amount of data written to disk. + +</p><p> + For general use in cases where the workload contains few UPDATE or DELETE + operations, a good choice for automerge is 8. If the workload contains + many UPDATE or DELETE commands, + or if query speed is a concern, it may be advantageous to reduce automerge + to 2. + +</p><p> + For reasons of backwards compatibility, the "automerge=1" command sets + the automerge parameter to 8, not 1 (a value of 1 would make no sense + anyway, as merging data from a single segment is a no-op). + + +</p><a name="tokenizer"></a> +<h1 id="tokenizer" tags="tokenizer"><span>8. </span>Tokenizers</h1> + +<p> + An FTS tokenizer is a set of rules for extracting terms from a document + or basic FTS full-text query. + +</p><p> + Unless a specific tokenizer is specified as part of the CREATE + VIRTUAL TABLE statement used to create the FTS table, the default + tokenizer, "simple", is used. The simple tokenizer extracts tokens from + a document or basic FTS full-text query according to the following + rules: + +</p><ul> + <li><p> A term is a contiguous sequence of eligible characters, where + eligible characters are all alphanumeric characters and all characters with + Unicode codepoint values greater than or equal to 128. + All other characters are + discarded when splitting a document into terms. Their only contribution is + to separate adjacent terms. + + </p></li><li><p> All uppercase characters within the ASCII range (Unicode codepoints + less than 128), are transformed to their lowercase equivalents as part + of the tokenization process. Thus, full-text queries are + case-insensitive when using the simple tokenizer. +</p></li></ul> + +<p> + For example, when a document containing the text "Right now, they're very + frustrated.", the terms extracted from the document and added to the + full-text index are, in order, "right now they re very frustrated". Such + a document would match a full-text query such as "MATCH 'Frustrated'", + as the simple tokenizer transforms the term in the query to lowercase + before searching the full-text index. + +</p><p> + As well as the "simple" tokenizer, the FTS source code features a tokenizer + that uses the <a href="http://tartarus.org/~martin/PorterStemmer/">Porter + Stemming algorithm</a>. This tokenizer uses the same rules to separate + the input document into terms including folding all terms into lower case, + but also uses the Porter Stemming algorithm to reduce related English language + words to a common root. For example, using the same input document as in the + paragraph above, the porter tokenizer extracts the following tokens: + "right now thei veri frustrat". Even though some of these terms are not even + English words, in some cases using them to build the full-text index is more + useful than the more intelligible output produced by the simple tokenizer. + Using the porter tokenizer, the document not only matches full-text queries + such as "MATCH 'Frustrated'", but also queries such as "MATCH 'Frustration'", + as the term "Frustration" is reduced by the Porter stemmer algorithm to + "frustrat" - just as "Frustrated" is. So, when using the porter tokenizer, + FTS is able to find not just exact matches for queried terms, but matches + against similar English language terms. For more information on the + Porter Stemmer algorithm, please refer to the page linked above. + +</p><p> + Example illustrating the difference between the "simple" and "porter" + tokenizers: + +</p><div class="codeblock"><pre><i>-- Create a table using the simple tokenizer. Insert a document into it.</i> +CREATE VIRTUAL TABLE simple USING fts3(tokenize=simple); +INSERT INTO simple VALUES('Right now they''re very frustrated'); + +<i>-- The first of the following two queries matches the document stored in</i> +<i>-- table "simple". The second does not.</i> +SELECT * FROM simple WHERE simple MATCH 'Frustrated'; +SELECT * FROM simple WHERE simple MATCH 'Frustration'; + +<i>-- Create a table using the porter tokenizer. Insert the same document into it</i> +CREATE VIRTUAL TABLE porter USING fts3(tokenize=porter); +INSERT INTO porter VALUES('Right now they''re very frustrated'); + +<i>-- Both of the following queries match the document stored in table "porter".</i> +SELECT * FROM porter WHERE porter MATCH 'Frustrated'; +SELECT * FROM porter WHERE porter MATCH 'Frustration'; +</pre></div> + +<p> + If this extension is compiled with the SQLITE_ENABLE_ICU pre-processor + symbol defined, then there exists a built-in tokenizer named "icu" + implemented using the ICU library. The first argument passed to the + xCreate() method (see fts3_tokenizer.h) of this tokenizer may be + an ICU locale identifier. For example "tr_TR" for Turkish as used + in Turkey, or "en_AU" for English as used in Australia. For example: + +</p><div class="codeblock"><pre>CREATE VIRTUAL TABLE thai_text USING fts3(text, tokenize=icu th_TH) +</pre></div> + +<p> + The ICU tokenizer implementation is very simple. It splits the input + text according to the ICU rules for finding word boundaries and discards + any tokens that consist entirely of white-space. This may be suitable + for some applications in some locales, but not all. If more complex + processing is required, for example to implement stemming or + discard punctuation, this can be done by creating a tokenizer + implementation that uses the ICU tokenizer as part of its implementation. + +<a name="unicode61"></a> + +</p><p> + The "unicode61" tokenizer is available beginning with SQLite <a href="releaselog/3_7_13.html">version 3.7.13</a> + (2012-06-11). + Unicode61 works very much like "simple" except that it does simple unicode + case folding according to rules in Unicode Version 6.1 and it recognizes + unicode space and punctuation characters and uses those to separate tokens. + The simple tokenizer only does case folding of ASCII characters and only + recognizes ASCII space and punctuation characters as token separators. + +</p><p> + By default, "unicode61" attempts to remove diacritics from Latin script + characters. This behaviour can be overridden by adding the tokenizer argument + "remove_diacritics=0". For example: + +</p><div class="codeblock"><pre><i>-- Create tables that remove <b>all</b>diacritics from Latin script characters</i> +<i>-- as part of tokenization.</i> +CREATE VIRTUAL TABLE txt1 USING fts4(tokenize=unicode61); +CREATE VIRTUAL TABLE txt2 USING fts4(tokenize=unicode61 "remove_diacritics=2"); + +<i>-- Create a table that does not remove diacritics from Latin script</i> +<i>-- characters as part of tokenization.</i> +CREATE VIRTUAL TABLE txt3 USING fts4(tokenize=unicode61 "remove_diacritics=0"); +</pre></div> + +<p>The remove_diacritics option may be set to "0", "1" or "2". The default + value is "1". If it is set to "1" or "2", then diacritics are removed from + Latin script characters as described above. However, if it is set to "1", + then diacritics are not removed in the fairly uncommon case where a single + unicode codepoint is used to represent a character with more that one + diacritic. For example, diacritics are not removed from codepoint 0x1ED9 + ("LATIN SMALL LETTER O WITH CIRCUMFLEX AND DOT BELOW"). This is technically + a bug, but cannot be fixed without creating backwards compatibility + problems. If this option is set to "2", then diacritics are correctly + removed from all Latin characters. + +</p><p> + It is also possible to customize the set of codepoints that unicode61 treats + as separator characters. The "separators=" option may be used to specify one + or more extra characters that should be treated as separator characters, and + the "tokenchars=" option may be used to specify one or more extra characters + that should be treated as part of tokens instead of as separator characters. + For example: + +</p><div class="codeblock"><pre><i>-- Create a table that uses the unicode61 tokenizer, but considers "."</i> +<i>-- and "=" characters to be part of tokens, and capital "X" characters to</i> +<i>-- function as separators.</i> +CREATE VIRTUAL TABLE txt3 USING fts4(tokenize=unicode61 "tokenchars=.=" "separators=X"); + +<i>-- Create a table that considers space characters (codepoint 32) to be</i> +<i>-- a token character</i> +CREATE VIRTUAL TABLE txt4 USING fts4(tokenize=unicode61 "tokenchars= "); +</pre></div> + +<p> + If a character specified as part of the argument to "tokenchars=" is considered + to be a token character by default, it is ignored. This is true even if it has + been marked as a separator by an earlier "separators=" option. Similarly, if + a character specified as part of a "separators=" option is treated as a separator + character by default, it is ignored. If multiple "tokenchars=" or "separators=" + options are specified, all are processed. For example: + +</p><div class="codeblock"><pre><i>-- Create a table that uses the unicode61 tokenizer, but considers "."</i> +<i>-- and "=" characters to be part of tokens, and capital "X" characters to</i> +<i>-- function as separators. Both of the "tokenchars=" options are processed</i> +<i>-- The "separators=" option ignores the "." passed to it, as "." is by</i> +<i>-- default a separator character, even though it has been marked as a token</i> +<i>-- character by an earlier "tokenchars=" option.</i> +CREATE VIRTUAL TABLE txt5 USING fts4( + tokenize=unicode61 "tokenchars=." "separators=X." "tokenchars==" +); +</pre></div> + +<p> + The arguments passed to the "tokenchars=" or "separators=" options are + case-sensitive. In the example above, specifying that "X" is a separator + character does not affect the way "x" is handled. + +<a name="f3tknzr"></a> + +</p><h2 id="custom_application_defined_tokenizers"><span>8.1. </span>Custom (Application Defined) Tokenizers</h2> + +<p> + In addition to providing built-in "simple", "porter" and (possibly) "icu" and + "unicode61" tokenizers, + FTS provides an interface for applications to implement and register custom + tokenizers written in C. The interface used to create a new tokenizer is defined + and described in the fts3_tokenizer.h source file. + +</p><p> + Registering a new FTS tokenizer is similar to registering a new + virtual table module with SQLite. The user passes a pointer to a + structure containing pointers to various callback functions that + make up the implementation of the new tokenizer type. For tokenizers, + the structure (defined in fts3_tokenizer.h) is called + "sqlite3_tokenizer_module". + +</p><p> + FTS does not expose a C-function that users call to register new + tokenizer types with a database handle. Instead, the pointer must + be encoded as an SQL blob value and passed to FTS through the SQL + engine by evaluating a special scalar function, "fts3_tokenizer()". + The fts3_tokenizer() function may be called with one or two arguments, + as follows: + +</p><div class="codeblock"><pre>SELECT fts3_tokenizer(<tokenizer-name>); +SELECT fts3_tokenizer(<tokenizer-name>, <sqlite3_tokenizer_module ptr>); +</pre></div> + +<p> + Where <tokenizer-name> is <a href="lang_expr.html#varparam">parameter</a> to which a string is bound using + <a href="c3ref/bind_blob.html">sqlite3_bind_text()</a> where the string identifies the tokenizer and + <sqlite3_tokenizer_module ptr> is a <a href="lang_expr.html#varparam">parameter</a> to which a BLOB is + bound using <a href="c3ref/bind_blob.html">sqlite3_bind_blob()</a> where the value of the BLOB is a + pointer to an sqlite3_tokenizer_module structure. + If the second argument is present, + it is registered as tokenizer <tokenizer-name> and a copy of it + returned. If only one argument is passed, a pointer to the tokenizer + implementation currently registered as <tokenizer-name> is returned, + encoded as a blob. Or, if no such tokenizer exists, an SQL exception + (error) is raised. + +</p><p> + Prior to SQLite <a href="releaselog/3_11_0.html">version 3.11.0</a> (2016-02-15), the arguments to + fts3_tokenizer() could be literal strings or BLOBs. They did not have to + be <a href="lang_expr.html#varparam">bound parameters</a>. But that could lead to security problems in the + event of an SQL injection. Hence, the legacy behavior is now disabled + by default. But the old legacy behavior can be enabled, for backwards + compatibility in applications that really need it, + by calling + <a href="c3ref/db_config.html">sqlite3_db_config</a>(db,<a href="c3ref/c_dbconfig_defensive.html#sqlitedbconfigenablefts3tokenizer">SQLITE_DBCONFIG_ENABLE_FTS3_TOKENIZER</a>,1,0). + +</p><p> + The following block contains an example of calling the fts3_tokenizer() + function from C code: + +</p><div class="codeblock"><pre><i>/* +** Register a tokenizer implementation with FTS3 or FTS4. +*/</i> +int registerTokenizer( + sqlite3 *db, + char *zName, + const sqlite3_tokenizer_module *p +){ + int rc; + sqlite3_stmt *pStmt; + const char *zSql = "SELECT fts3_tokenizer(?1, ?2)"; + + rc = sqlite3_prepare_v2(db, zSql, -1, &pStmt, 0); + if( rc!=SQLITE_OK ){ + return rc; + } + + sqlite3_bind_text(pStmt, 1, zName, -1, SQLITE_STATIC); + sqlite3_bind_blob(pStmt, 2, &p, sizeof(p), SQLITE_STATIC); + sqlite3_step(pStmt); + + return sqlite3_finalize(pStmt); +} + +<i>/* +** Query FTS for the tokenizer implementation named zName. +*/</i> +int queryTokenizer( + sqlite3 *db, + char *zName, + const sqlite3_tokenizer_module **pp +){ + int rc; + sqlite3_stmt *pStmt; + const char *zSql = "SELECT fts3_tokenizer(?)"; + + *pp = 0; + rc = sqlite3_prepare_v2(db, zSql, -1, &pStmt, 0); + if( rc!=SQLITE_OK ){ + return rc; + } + + sqlite3_bind_text(pStmt, 1, zName, -1, SQLITE_STATIC); + if( SQLITE_ROW==sqlite3_step(pStmt) ){ + if( sqlite3_column_type(pStmt, 0)==SQLITE_BLOB ){ + memcpy(pp, sqlite3_column_blob(pStmt, 0), sizeof(*pp)); + } + } + + return sqlite3_finalize(pStmt); +} +</pre></div> + + +<a name="fts3tok"></a> + +<h2 id="querying_tokenizers"><span>8.2. </span>Querying Tokenizers</h2> + +<p>The "fts3tokenize" virtual table can be used to directly access any + tokenizer. The following SQL demonstrates how to create an instance + of the fts3tokenize virtual table: + +</p><div class="codeblock"><pre>CREATE VIRTUAL TABLE tok1 USING fts3tokenize('porter'); +</pre></div> + +<p>The name of the desired tokenizer should be substituted in place of + 'porter' in the example, of course. If the tokenizer requires one or + more arguments, they should be separated by commas in the fts3tokenize + declaration (even though they are separated by spaces in declarations + of regular fts4 tables). The following creates fts4 and fts3tokenize + tables that use the same tokenizer: +</p><div class="codeblock"><pre>CREATE VIRTUAL TABLE text1 USING fts4(tokenize=icu en_AU); +CREATE VIRTUAL TABLE tokens1 USING fts3tokenize(icu, en_AU); + +CREATE VIRTUAL TABLE text2 USING fts4(tokenize=unicode61 "tokenchars=@." "separators=123"); +CREATE VIRTUAL TABLE tokens2 USING fts3tokenize(unicode61, "tokenchars=@.", "separators=123"); +</pre></div> + +<p> + Once the virtual table is created, it can be queried as follows: + +</p><div class="codeblock"><pre>SELECT token, start, end, position + FROM tok1 + WHERE input='This is a test sentence.'; +</pre></div> + +<p>The virtual table will return one row of output for each token in the + input string. The "token" column is the text of the token. The "start" + and "end" columns are the byte offset to the beginning and end of the + token in the original input string. + The "position" column is the sequence number + of the token in the original input string. There is also an "input" + column which is simply a copy of the input string that is specified in + the WHERE clause. Note that a constraint of the form "input=?" must + appear in the WHERE clause or else the virtual table will have no input + to tokenize and will return no rows. The example above generates + the following output: + +</p><div class="codeblock"><pre>thi|0|4|0 +is|5|7|1 +a|8|9|2 +test|10|14|3 +sentenc|15|23|4 +</pre></div> + +<p>Notice that the tokens in the result set from the fts3tokenize virtual + table have been transformed according to the rules of the tokenizer. + Since this example used the "porter" tokenizer, the "This" token was + converted into "thi". If the original text of the token is desired, + it can be retrieved using the "start" and "end" columns with the + <a href="lang_corefunc.html#substr">substr()</a> function. For example: + +</p><div class="codeblock"><pre>SELECT substr(input, start+1, end-start), token, position + FROM tok1 + WHERE input='This is a test sentence.'; +</pre></div> + +<p>The fts3tokenize virtual table can be used on any tokenizer, regardless + of whether or not there exists an FTS3 or FTS4 table that actually uses + that tokenizer. + + +</p><a name="data_structures"></a> +<h1 tags="segment btree" id="data_structures"><span>9. </span>Data Structures</h1> + +<p> + This section describes at a high-level the way the FTS module stores its + index and content in the database. It is <b>not necessary to read or + understand the material in this section in order to use FTS</b> in an + application. However, it may be useful to application developers attempting + to analyze and understand FTS performance characteristics, or to developers + contemplating enhancements to the existing FTS feature set. +</p> + +<a name="*shadowtab"></a> + +<a name="shadow_tables"></a> +<h2 tags="shadowtabs" id="shadow_tables"><span>9.1. </span>Shadow Tables</h2> +<p> + For each FTS virtual table in a database, three to five real (non-virtual) tables + are created to store the underlying data. These real tables are called "shadow tables". + The real tables are named "%_content", + "%_segdir", "%_segments", "%_stat", and "%_docsize", where "%" is replaced by the name + of the FTS virtual table. + +</p><p> + The leftmost column of the "%_content" table is an INTEGER PRIMARY KEY field + named "docid". Following this is one column for each column of the FTS + virtual table as declared by the user, named by prepending the column name + supplied by the user with "c<i>N</i>", where <i>N</i> is the index of the + column within the table, numbered from left to right starting with 0. Data + types supplied as part of the virtual table declaration are not used as + part of the %_content table declaration. For example: + +</p><div class="codeblock"><pre><i>-- Virtual table declaration</i> +CREATE VIRTUAL TABLE abc USING fts4(a NUMBER, b TEXT, c); + +<i>-- Corresponding %_content table declaration</i> +CREATE TABLE abc_content(docid INTEGER PRIMARY KEY, c0a, c1b, c2c); +</pre></div> + +<p> + The %_content table contains the unadulterated data inserted by the user + into the FTS virtual table by the user. If the user does not explicitly + supply a "docid" value when inserting records, one is selected automatically + by the system. + +</p><p> + The %_stat and %_docsize tables are only created if the FTS table uses the + FTS4 module, not FTS3. Furthermore, the %_docsize table is omitted if the + FTS4 table is created with the <a href="fts3.html#fts4matchinfo">"matchinfo=fts3"</a> directive + specified as part of the CREATE VIRTUAL TABLE statement. If they are created, + the schema of the two tables is as follows: +</p><div class="codeblock"><pre>CREATE TABLE %_stat( + id INTEGER PRIMARY KEY, + value BLOB +); + +CREATE TABLE %_docsize( + docid INTEGER PRIMARY KEY, + size BLOB +); +</pre></div> + +<p> + For each row in the FTS table, the %_docsize table contains a corresponding + row with the same "docid" value. The "size" field contains a blob consisting + of <i>N</i> FTS varints, where <i>N</i> is the number of user-defined columns + in the table. Each varint in the "size" blob is the number of tokens in the + corresponding column of the associated row in the FTS table. The %_stat table + always contains a single row with the "id" column set to 0. The "value" + column contains a blob consisting of <i>N+1</i> FTS varints, where <i>N</i> + is again the number of user-defined columns in the FTS table. The first + varint in the blob is set to the total number of rows in the FTS table. The + second and subsequent varints contain the total number of tokens stored in + the corresponding column for all rows of the FTS table. + +</p><p> + The two remaining tables, %_segments and %_segdir, are used to store the + full-text index. Conceptually, this index is a lookup table that maps each + term (word) to the set of docid values corresponding to records in the + %_content table that contain one or more occurrences of the term. To + retrieve all documents that contain a specified term, the FTS module + queries this index to determine the set of docid values for records that + contain the term, then retrieves the required documents from the %_content + table. Regardless of the schema of the FTS virtual table, the %_segments + and %_segdir tables are always created as follows: + +</p><div class="codeblock"><pre>CREATE TABLE %_segments( + blockid INTEGER PRIMARY KEY, <i>-- B-tree node id</i> + block blob <i>-- B-tree node data</i> +); + +CREATE TABLE %_segdir( + level INTEGER, + idx INTEGER, + start_block INTEGER, <i>-- Blockid of first node in %_segments</i> + leaves_end_block INTEGER, <i>-- Blockid of last leaf node in %_segments</i> + end_block INTEGER, <i>-- Blockid of last node in %_segments</i> + root BLOB, <i>-- B-tree root node</i> + PRIMARY KEY(level, idx) +); +</pre></div> + +<p> + The schema depicted above is not designed to store the full-text index + directly. Instead, it is used to store one or more b-tree structures. There + is one b-tree for each row in the %_segdir table. The %_segdir table + row contains the root node and various meta-data associated with the + b-tree structure, and the %_segments table contains all other (non-root) + b-tree nodes. Each b-tree is referred to as a "segment". Once it has + been created, a segment b-tree is never updated (although it may be + deleted altogether). + +</p><p> + The keys used by each segment b-tree are terms (words). As well as the + key, each segment b-tree entry has an associated "doclist" (document list). + A doclist consists of zero or more entries, where each entry consists of: + +</p><ul> + <li> A docid (document id), and + </li><li> A list of term offsets, one for each occurrence of the term within + the document. A term offset indicates the number of tokens (words) + that occur before the term in question, not the number of characters + or bytes. For example, the term offset of the term "war" in the + phrase "Ancestral voices prophesying war!" is 3. +</li></ul> + +<p> + Entries within a doclist are sorted by docid. Positions within a doclist + entry are stored in ascending order. + +</p><p> + The contents of the logical full-text index is found by merging the + contents of all segment b-trees. If a term is present in more than one + segment b-tree, then it maps to the union of each individual doclist. If, + for a single term, the same docid occurs in more than one doclist, then only + the doclist that is part of the most recently created segment b-tree is + considered valid. + +</p><p> + Multiple b-tree structures are used instead of a single b-tree to reduce + the cost of inserting records into FTS tables. When a new record is + inserted into an FTS table that already contains a lot of data, it is + likely that many of the terms in the new record are already present in + a large number of existing records. If a single b-tree were used, then + large doclist structures would have to be loaded from the database, + amended to include the new docid and term-offset list, then written back + to the database. Using multiple b-tree tables allows this to be avoided + by creating a new b-tree which can be merged with the existing b-tree + (or b-trees) later on. Merging of b-tree structures can be performed as + a background task, or once a certain number of separate b-tree structures + have been accumulated. Of course, this scheme makes queries more expensive + (as the FTS code may have to look up individual terms in more than one + b-tree and merge the results), but it has been found that in practice this + overhead is often negligible. + +</p><h2 id="variable_length_integer_varint_format"><span>9.2. </span>Variable Length Integer (varint) Format</h2> + +<p> + Integer values stored as part of segment b-tree nodes are encoded using the + FTS varint format. This encoding is similar, but <b>not identical</b>, to + the <a href="fileformat2.html#varint">SQLite varint format</a>. + +</p><p> + An encoded FTS varint consumes between one and ten bytes of space. The + number of bytes required is determined by the sign and magnitude of the + integer value encoded. More accurately, the number of bytes used to store + the encoded integer depends on the position of the most significant set bit + in the 64-bit twos-complement representation of the integer value. Negative + values always have the most significant bit set (the sign bit), and so are + always stored using the full ten bytes. Positive integer values may be + stored using less space. + +</p><p> + The final byte of an encoded FTS varint has its most significant bit + cleared. All preceding bytes have the most significant bit set. Data + is stored in the remaining seven least significant bits of each byte. + The first byte of the encoded representation contains the least significant + seven bits of the encoded integer value. The second byte of the encoded + representation, if it is present, contains the seven next least significant + bits of the integer value, and so on. The following table contains examples + of encoded integer values: + +</p><table striped="1" style="margin:1em auto; width:80%; border-spacing:0"> + <tr style="text-align:left"><th>Decimal</th><th>Hexadecimal</th><th width="100%">Encoded Representation + </th></tr><tr style="text-align:left;background-color:#DDDDDD"><td>43</td><td>0x000000000000002B</td><td>0x2B + </td></tr><tr style="text-align:left"><td>200815</td><td>0x000000000003106F</td><td>0xEF 0xA0 0x0C + </td></tr><tr style="text-align:left;background-color:#DDDDDD"><td>-1</td><td>0xFFFFFFFFFFFFFFFF</td><td>0xFF 0xFF 0xFF 0xFF 0xFF 0xFF 0xFF 0xFF 0xFF 0x01 +</td></tr></table> + + +<h2 id="segment_b_tree_format"><span>9.3. </span>Segment B-Tree Format</h2> + +<p> + Segment b-trees are prefix-compressed b+-trees. There is one segment b-tree + for each row in the %_segdir table (see above). The root node of the segment + b-tree is stored as a blob in the "root" field of the corresponding row + of the %_segdir table. All other nodes (if any exist) are stored in the + "blob" column of the %_segments table. Nodes within the %_segments table are + identified by the integer value in the blockid field of the corresponding + row. The following table describes the fields of the %_segdir table: + +</p><table striped="1" style="margin:1em auto; width:80%; border-spacing:0"> + <tr style="text-align:left"><th>Column </th><th width="100%">Interpretation + </th></tr><tr style="text-align:left;background-color:#DDDDDD"><td>level </td><td> + Between them, the contents of the "level" and "idx" fields define the + relative age of the segment b-tree. The smaller the value stored in the + "level" field, the more recently the segment b-tree was created. If two + segment b-trees are of the same "level", the segment with the larger + value stored in the "idx" column is more recent. The PRIMARY KEY constraint + on the %_segdir table prevents any two segments from having the same value + for both the "level" and "idx" fields. + </td></tr><tr style="text-align:left"><td>idx </td><td> See above. + </td></tr><tr style="text-align:left;background-color:#DDDDDD"><td>start_block </td><td> + The blockid that corresponds to the node with the smallest blockid that + belongs to this segment b-tree. Or zero if the entire segment b-tree + fits on the root node. If it exists, this node is always a leaf node. + </td></tr><tr style="text-align:left"><td>leaves_end_block </td><td> + The blockid that corresponds to the leaf node with the largest blockid + that belongs to this segment b-tree. Or zero if the entire segment b-tree + fits on the root node. + </td></tr><tr style="text-align:left;background-color:#DDDDDD"><td>end_block </td><td> + This field may contain either an integer or a text field consisting of + two integers separated by a space character (unicode codepoint 0x20). +<p style="margin-left:0;margin-right:0"> + The first, or only, integer is the blockid that corresponds to the interior + node with the largest blockid that belongs to this segment b-tree. Or zero + if the entire segment b-tree fits on the root node. If it exists, this node + is always an interior node. +</p><p style="margin-left:0;margin-right:0;margin-bottom:0"> + The second integer, if it is present, is the aggregate size of all data + stored on leaf pages in bytes. If the value is negative, then the segment + is the output of an unfinished incremental-merge operation, and the + absolute value is current size in bytes. + + </p></td></tr><tr style="text-align:left"><td>root </td><td> + Blob containing the root node of the segment b-tree. +</td></tr></table> + +<p> + Apart from the root node, the nodes that make up a single segment b-tree are + always stored using a contiguous sequence of blockids. Furthermore, the + nodes that make up a single level of the b-tree are themselves stored as + a contiguous block, in b-tree order. The contiguous sequence of blockids + used to store the b-tree leaves are allocated starting with the blockid + value stored in the "start_block" column of the corresponding %_segdir row, + and finishing at the blockid value stored in the "leaves_end_block" + field of the same row. It is therefore possible to iterate through all the + leaves of a segment b-tree, in key order, by traversing the %_segments + table in blockid order from "start_block" to "leaves_end_block". + +</p><h3 id="segment_b_tree_leaf_nodes"><span>9.3.1. </span>Segment B-Tree Leaf Nodes</h3> + +<p> + The following diagram depicts the format of a segment b-tree leaf node. + +</p><center> + <img src="images/fts3_leaf_node.png"> + <p> Segment B-Tree Leaf Node Format +</p></center> + +<p> + The first term stored on each node ("Term 1" in the figure above) is + stored verbatim. Each subsequent term is prefix-compressed with respect + to its predecessor. Terms are stored within a page in sorted (memcmp) + order. + +</p><h3 id="segment_b_tree_interior_nodes"><span>9.3.2. </span>Segment B-Tree Interior Nodes</h3> + +<p> + The following diagram depicts the format of a segment b-tree interior + (non-leaf) node. + +</p><center> + <img src="images/fts3_interior_node.png"> + <p> Segment B-Tree Interior Node Format +</p></center> + + +<h2 id="doclist_format"><span>9.4. </span>Doclist Format</h2> + +<p> + A doclist consists of an array of 64-bit signed integers, serialized using + the FTS varint format. Each doclist entry is made up of a series of two + or more integers, as follows: + +</p><ol> + <li> The docid value. The first entry in a doclist contains the literal docid + value. The first field of each subsequent doclist entry contains the + difference between the new docid and the previous one (always a positive + number). + </li><li> Zero or more term-offset lists. A term-offset list is present for each + column of the FTS virtual table that contains the term. A term-offset + list consists of the following: + <ol> + <li> Constant value 1. This field is omitted for any term-offset list + associated with column 0. + </li><li> The column number (1 for the second leftmost column, etc.). This + field is omitted for any term-offset list associated with column 0. + </li><li> A list of term-offsets, sorted from smallest to largest. Instead + of storing the term-offset value literally, each integer stored + is the difference between the current term-offset and the previous + one (or zero if the current term-offset is the first), plus 2. + </li></ol> + </li><li> Constant value 0. +</li></ol> + +<center> + <img src="images/fts3_doclist2.png"> + <p> FTS3 Doclist Format +</p></center> + +<center> + <img src="images/fts3_doclist.png"> + <p> FTS Doclist Entry Format +</p></center> + +<p> + For doclists for which the term appears in more than one column of the FTS + virtual table, term-offset lists within the doclist are stored in column + number order. This ensures that the term-offset list associated with + column 0 (if any) is always first, allowing the first two fields of the + term-offset list to be omitted in this case. + +</p><a name="limitations"></a> +<h1 tags="bugs" id="limitations"><span>10. </span>Limitations</h1> + +<h2 id="_utf_16_byte_order_mark_problem_"><span>10.1. </span> UTF-16 byte-order-mark problem </h2> + +For UTF-16 databases, when using the "simple" tokenizer, it is possible to use +malformed unicode strings to cause the +<a href="#integcheck">integrity-check special command</a> to falsely report +corruption, or for <a href="#snippet">auxiliary functions</a> to return +incorrect results. More specifically, the bug can be triggered by any of the following: + +<ul> + <li><p>A UTF-16 byte-order-mark (BOM) is embedded at the beginning of an SQL string + literal value inserted into an FTS3 table. For example: + +</p><div class="codeblock"><pre>INSERT INTO fts_table(col) VALUES(char(0xfeff)||'text...'); +</pre></div> + + </li><li><p>Malformed UTF-8 that SQLite converts to a UTF-16 byte-order-mark is + embedded at the beginning of an SQL string literal value inserted + into an FTS3 table. + + </p></li><li><p>A text value created by casting a blob that begins with the two + bytes 0xFF and 0xFE, in either possible order, is inserted into an + FTS3 table. For example: + +</p><div class="codeblock"><pre>INSERT INTO fts_table(col) VALUES(CAST(X'FEFF' AS TEXT)); +</pre></div> +</li></ul> + +Everything works correctly if any of the following are true: +<ul> +<li> The <a href="pragma.html#pragma_encoding">database encoding</a> is UTF-8. +</li><li> All text strings are insert using one of the + <a href="c3ref/bind_blob.html">sqlite3_bind_text()</a> family of functions. +</li><li> Literal strings contain no byte-order-marks. +</li><li> A tokenizer is used that recognizes byte-order-marks + as whitespace. (The default "simple" tokenizer for + FTS3/4 does not think that BOMs are whitespace, but + the unicode tokenizer does.) +</li></ul> +All of the above conditions must be false in order for problems +to occur. And even if all of the conditiona above are false, +most things will still operator correctly. Only the +<a href="#integcheck">integrity-check</a> command and the +<a href="#snippet">auxiliary functions</a> might given +unexpected results. + +<a name="appendix_a"></a> +<h1 id="appendix_a" nonumber="1" tags="search application tips"> + Appendix A: Search Application Tips +</h1> + +<p> + FTS is primarily designed to support Boolean full-text queries - queries + to find the set of documents that match a specified criteria. However, many + (most?) search applications require that results are somehow ranked in order + of "relevance", where "relevance" is defined as the likelihood that the user + who performed the search is interested in a specific element of the returned + set of documents. When using a search engine to find documents on the world + wide web, the user expects that the most useful, or "relevant", documents + will be returned as the first page of results, and that each subsequent page + contains progressively less relevant results. Exactly how a machine can + determine document relevance based on a users query is a complicated problem + and the subject of much ongoing research. + +</p><p> + One very simple scheme might be to count the number of instances of the + users search terms in each result document. Those documents that contain + many instances of the terms are considered more relevant than those with + a small number of instances of each term. In an FTS application, the + number of term instances in each result could be determined by counting + the number of integers in the return value of the <a href="fts3.html#offsets">offsets</a> function. + The following example shows a query that could be used to obtain the + ten most relevant results for a query entered by the user: + +</p><div class="codeblock"><pre><i>-- This example (and all others in this section) assumes the following schema</i> +CREATE VIRTUAL TABLE documents USING fts3(title, content); + +<i>-- Assuming the application has supplied an SQLite user function named "countintegers"</i> +<i>-- that returns the number of space-separated integers contained in its only argument,</i> +<i>-- the following query could be used to return the titles of the 10 documents that contain</i> +<i>-- the greatest number of instances of the users query terms. Hopefully, these 10</i> +<i>-- documents will be those that the users considers more or less the most "relevant".</i> +SELECT title FROM documents + WHERE documents MATCH <query> + ORDER BY countintegers(offsets(documents)) DESC + LIMIT 10 OFFSET 0 +</pre></div> + +<p> + The query above could be made to run faster by using the FTS <a href="fts3.html#matchinfo">matchinfo</a> + function to determine the number of query term instances that appear in each + result. The matchinfo function is much more efficient than the offsets + function. Furthermore, the matchinfo function provides extra information + regarding the overall number of occurrences of each query term in the entire + document set (not just the current row) and the number of documents in which + each query term appears. This may be used (for example) to attach a higher + weight to less common terms which may increase the overall computed relevancy + of those results the user considers more interesting. + +</p><div class="codeblock"><pre><i>-- If the application supplies an SQLite user function called "rank" that</i> +<i>-- interprets the blob of data returned by matchinfo and returns a numeric</i> +<i>-- relevancy based on it, then the following SQL may be used to return the</i> +<i>-- titles of the 10 most relevant documents in the dataset for a users query.</i> +SELECT title FROM documents + WHERE documents MATCH <query> + ORDER BY rank(matchinfo(documents)) DESC + LIMIT 10 OFFSET 0 +</pre></div> + +<p> + The SQL query in the example above uses less CPU than the first example + in this section, but still has a non-obvious performance problem. SQLite + satisfies this query by retrieving the value of the "title" column and + matchinfo data from the FTS module for every row matched by the users + query before it sorts and limits the results. Because of the way SQLite's + virtual table interface works, retrieving the value of the "title" column + requires loading the entire row from disk (including the "content" field, + which may be quite large). This means that if the users query matches + several thousand documents, many megabytes of "title" and "content" data + may be loaded from disk into memory even though they will never be used + for any purpose. + +</p><p> + The SQL query in the following example block is one solution to this + problem. In SQLite, when a <a href="optoverview.html#flattening">sub-query + used in a join contains a LIMIT clause</a>, the results of the sub-query are + calculated and stored in temporary table before the main query is executed. + This means that SQLite will load only the docid and matchinfo data for each + row matching the users query into memory, determine the docid values + corresponding to the ten most relevant documents, then load only the title + and content information for those 10 documents only. Because both the matchinfo + and docid values are gleaned entirely from the full-text index, this results + in dramatically less data being loaded from the database into memory. + +</p><div class="codeblock"><pre>SELECT title FROM documents JOIN ( + SELECT docid, rank(matchinfo(documents)) AS rank + FROM documents + WHERE documents MATCH <query> + ORDER BY rank DESC + LIMIT 10 OFFSET 0 +) AS ranktable USING(docid) +ORDER BY ranktable.rank DESC +</pre></div> + +<p> + The next block of SQL enhances the query with solutions to two other problems + that may arise in developing search applications using FTS: + +</p><ol> + <li> <p> + The <a href="fts3.html#snippet">snippet</a> function cannot be used with the above query. Because + the outer query does not include a "WHERE ... MATCH" clause, the snippet + function may not be used with it. One solution is to duplicate the WHERE + clause used by the sub-query in the outer query. The overhead associated + with this is usually negligible. + </p></li><li> <p> + The relevancy of a document may depend on something other than just + the data available in the return value of matchinfo. For example + each document in the database may be assigned a static weight based + on factors unrelated to its content (origin, author, age, number + of references etc.). These values can be stored by the application + in a separate table that can be joined against the documents table + in the sub-query so that the rank function may access them. +</p></li></ol> + +<p> + This version of the query is very similar to that used by the + <a href="https://www.sqlite.org/search?q=fts3">sqlite.org documentation search</a> + application. + +</p><div class="codeblock"><pre><i>-- This table stores the static weight assigned to each document in FTS table</i> +<i>-- "documents". For each row in the documents table there is a corresponding row</i> +<i>-- with the same docid value in this table.</i> +CREATE TABLE documents_data(docid INTEGER PRIMARY KEY, weight); + +<i>-- This query is similar to the one in the block above, except that:</i> +<i>--</i> +<i>-- 1. It returns a "snippet" of text along with the document title for display. So</i> +<i>-- that the snippet function may be used, the "WHERE ... MATCH ..." clause from</i> +<i>-- the sub-query is duplicated in the outer query.</i> +<i>--</i> +<i>-- 2. The sub-query joins the documents table with the document_data table, so that</i> +<i>-- implementation of the rank function has access to the static weight assigned</i> +<i>-- to each document.</i> +SELECT title, snippet(documents) FROM documents JOIN ( + SELECT docid, rank(matchinfo(documents), documents_data.weight) AS rank + FROM documents JOIN documents_data USING(docid) + WHERE documents MATCH <query> + ORDER BY rank DESC + LIMIT 10 OFFSET 0 +) AS ranktable USING(docid) +WHERE documents MATCH <query> +ORDER BY ranktable.rank DESC +</pre></div> + +<p> + All the example queries above return the ten most relevant query results. + By modifying the values used with the OFFSET and LIMIT clauses, a query + to return (say) the next ten most relevant results is easy to construct. + This may be used to obtain the data required for a search applications second + and subsequent pages of results. + +</p><p> + The next block contains an example rank function that uses matchinfo data + implemented in C. Instead of a single weight, it allows a weight to be + externally assigned to each column of each document. It may be registered + with SQLite like any other user function using <a href="c3ref/create_function.html">sqlite3_create_function</a>. + +</p><p><b> Security Warning:</b> Because it is just an ordinary SQL function, + rank() may be invoked as part of any SQL query in any context. This means + that the first argument passed may not be a valid matchinfo blob. + Implementors should take care to handle this case without causing buffer + overruns or other potential security problems. + +</p><div class="codeblock"><pre><i>/*</i> +<i>** SQLite user defined function to use with matchinfo() to calculate the</i> +<i>** relevancy of an FTS match. The value returned is the relevancy score</i> +<i>** (a real value greater than or equal to zero). A larger value indicates </i> +<i>** a more relevant document.</i> +<i>**</i> +<i>** The overall relevancy returned is the sum of the relevancies of each </i> +<i>** column value in the FTS table. The relevancy of a column value is the</i> +<i>** sum of the following for each reportable phrase in the FTS query:</i> +<i>**</i> +<i>** (<hit count> / <global hit count>) * <column weight></i> +<i>**</i> +<i>** where <hit count> is the number of instances of the phrase in the</i> +<i>** column value of the current row and <global hit count> is the number</i> +<i>** of instances of the phrase in the same column of all rows in the FTS</i> +<i>** table. The <column weight> is a weighting factor assigned to each</i> +<i>** column by the caller (see below).</i> +<i>**</i> +<i>** The first argument to this function must be the return value of the FTS </i> +<i>** matchinfo() function. Following this must be one argument for each column </i> +<i>** of the FTS table containing a numeric weight factor for the corresponding </i> +<i>** column. Example:</i> +<i>**</i> +<i>** CREATE VIRTUAL TABLE documents USING fts3(title, content)</i> +<i>**</i> +<i>** The following query returns the docids of documents that match the full-text</i> +<i>** query <query> sorted from most to least relevant. When calculating</i> +<i>** relevance, query term instances in the 'title' column are given twice the</i> +<i>** weighting of those in the 'content' column.</i> +<i>**</i> +<i>** SELECT docid FROM documents </i> +<i>** WHERE documents MATCH <query> </i> +<i>** ORDER BY rank(matchinfo(documents), 1.0, 0.5) DESC</i> +<i>*/</i> +static void rankfunc(sqlite3_context *pCtx, int nVal, sqlite3_value **apVal){ + int *aMatchinfo; <i>/* Return value of matchinfo() */</i> + int nMatchinfo; <i>/* Number of elements in aMatchinfo[] */</i> + int nCol = 0; <i>/* Number of columns in the table */</i> + int nPhrase = 0; <i>/* Number of phrases in the query */</i> + int iPhrase; <i>/* Current phrase */</i> + double score = 0.0; <i>/* Value to return */</i> + + assert( sizeof(int)==4 ); + +<i> /* Check that the number of arguments passed to this function is correct.</i> +<i> ** If not, jump to wrong_number_args. Set aMatchinfo to point to the array</i> +<i> ** of unsigned integer values returned by FTS function matchinfo. Set</i> +<i> ** nPhrase to contain the number of reportable phrases in the users full-text</i> +<i> ** query, and nCol to the number of columns in the table. Then check that the</i> +<i> ** size of the matchinfo blob is as expected. Return an error if it is not.</i> +<i> */</i> + if( nVal<1 ) goto wrong_number_args; + aMatchinfo = (unsigned int *)sqlite3_value_blob(apVal[0]); + nMatchinfo = sqlite3_value_bytes(apVal[0]) / sizeof(int); + if( nMatchinfo>=2 ){ + nPhrase = aMatchinfo[0]; + nCol = aMatchinfo[1]; + } + if( nMatchinfo!=(2+3*nCol*nPhrase) ){ + sqlite3_result_error(pCtx, + "invalid matchinfo blob passed to function rank()", -1); + return; + } + if( nVal!=(1+nCol) ) goto wrong_number_args; + +<i> /* Iterate through each phrase in the users query. */</i> + for(iPhrase=0; iPhrase<nPhrase; iPhrase++){ + int iCol; <i>/* Current column */</i> + +<i> /* Now iterate through each column in the users query. For each column,</i> +<i> ** increment the relevancy score by:</i> +<i> **</i> +<i> ** (<hit count> / <global hit count>) * <column weight></i> +<i> **</i> +<i> ** aPhraseinfo[] points to the start of the data for phrase iPhrase. So</i> +<i> ** the hit count and global hit counts for each column are found in </i> +<i> ** aPhraseinfo[iCol*3] and aPhraseinfo[iCol*3+1], respectively.</i> +<i> */</i> + int *aPhraseinfo = &aMatchinfo[2 + iPhrase*nCol*3]; + for(iCol=0; iCol<nCol; iCol++){ + int nHitCount = aPhraseinfo[3*iCol]; + int nGlobalHitCount = aPhraseinfo[3*iCol+1]; + double weight = sqlite3_value_double(apVal[iCol+1]); + if( nHitCount>0 ){ + score += ((double)nHitCount / (double)nGlobalHitCount) * weight; + } + } + } + + sqlite3_result_double(pCtx, score); + return; + +<i> /* Jump here if the wrong number of arguments are passed to this function */</i> +wrong_number_args: + sqlite3_result_error(pCtx, "wrong number of arguments to function rank()", -1); +} +</pre></div> +</integer></language-id> + |