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9.13. Text Search Functions and Operators

Table 9.41, Table 9.42 and Table 9.43 summarize the functions and operators that are provided for full text searching. See Chapter 12 for a detailed explanation of PostgreSQL's text search facility.

Table 9.41. Text Search Operators

Operator

Description

Example(s)

tsvector @@ tsqueryboolean

tsquery @@ tsvectorboolean

Does tsvector match tsquery? (The arguments can be given in either order.)

to_tsvector('fat cats ate rats') @@ to_tsquery('cat & rat')t

text @@ tsqueryboolean

Does text string, after implicit invocation of to_tsvector(), match tsquery?

'fat cats ate rats' @@ to_tsquery('cat & rat')t

tsvector @@@ tsqueryboolean

tsquery @@@ tsvectorboolean

This is a deprecated synonym for @@.

to_tsvector('fat cats ate rats') @@@ to_tsquery('cat & rat')t

tsvector || tsvectortsvector

Concatenates two tsvectors. If both inputs contain lexeme positions, the second input's positions are adjusted accordingly.

'a:1 b:2'::tsvector || 'c:1 d:2 b:3'::tsvector'a':1 'b':2,5 'c':3 'd':4

tsquery && tsquerytsquery

ANDs two tsquerys together, producing a query that matches documents that match both input queries.

'fat | rat'::tsquery && 'cat'::tsquery( 'fat' | 'rat' ) & 'cat'

tsquery || tsquerytsquery

ORs two tsquerys together, producing a query that matches documents that match either input query.

'fat | rat'::tsquery || 'cat'::tsquery'fat' | 'rat' | 'cat'

!! tsquerytsquery

Negates a tsquery, producing a query that matches documents that do not match the input query.

!! 'cat'::tsquery!'cat'

tsquery <-> tsquerytsquery

Constructs a phrase query, which matches if the two input queries match at successive lexemes.

to_tsquery('fat') <-> to_tsquery('rat')'fat' <-> 'rat'

tsquery @> tsqueryboolean

Does first tsquery contain the second? (This considers only whether all the lexemes appearing in one query appear in the other, ignoring the combining operators.)

'cat'::tsquery @> 'cat & rat'::tsqueryf

tsquery <@ tsqueryboolean

Is first tsquery contained in the second? (This considers only whether all the lexemes appearing in one query appear in the other, ignoring the combining operators.)

'cat'::tsquery <@ 'cat & rat'::tsqueryt

'cat'::tsquery <@ '!cat & rat'::tsqueryt


In addition to these specialized operators, the usual comparison operators shown in Table 9.1 are available for types tsvector and tsquery. These are not very useful for text searching but allow, for example, unique indexes to be built on columns of these types.

Table 9.42. Text Search Functions

Function

Description

Example(s)

array_to_tsvector ( text[] ) → tsvector

Converts an array of lexemes to a tsvector. The given strings are used as-is without further processing.

array_to_tsvector('{fat,cat,rat}'::text[])'cat' 'fat' 'rat'

get_current_ts_config ( ) → regconfig

Returns the OID of the current default text search configuration (as set by default_text_search_config).

get_current_ts_config()english

length ( tsvector ) → integer

Returns the number of lexemes in the tsvector.

length('fat:2,4 cat:3 rat:5A'::tsvector)3

numnode ( tsquery ) → integer

Returns the number of lexemes plus operators in the tsquery.

numnode('(fat & rat) | cat'::tsquery)5

plainto_tsquery ( [ config regconfig, ] query text ) → tsquery

Converts text to a tsquery, normalizing words according to the specified or default configuration. Any punctuation in the string is ignored (it does not determine query operators). The resulting query matches documents containing all non-stopwords in the text.

plainto_tsquery('english', 'The Fat Rats')'fat' & 'rat'

phraseto_tsquery ( [ config regconfig, ] query text ) → tsquery

Converts text to a tsquery, normalizing words according to the specified or default configuration. Any punctuation in the string is ignored (it does not determine query operators). The resulting query matches phrases containing all non-stopwords in the text.

phraseto_tsquery('english', 'The Fat Rats')'fat' <-> 'rat'

phraseto_tsquery('english', 'The Cat and Rats')'cat' <2> 'rat'

websearch_to_tsquery ( [ config regconfig, ] query text ) → tsquery

Converts text to a tsquery, normalizing words according to the specified or default configuration. Quoted word sequences are converted to phrase tests. The word or is understood as producing an OR operator, and a dash produces a NOT operator; other punctuation is ignored. This approximates the behavior of some common web search tools.

websearch_to_tsquery('english', '"fat rat" or cat dog')'fat' <-> 'rat' | 'cat' & 'dog'

querytree ( tsquery ) → text

Produces a representation of the indexable portion of a tsquery. A result that is empty or just T indicates a non-indexable query.

querytree('foo & ! bar'::tsquery)'foo'

setweight ( vector tsvector, weight "char" ) → tsvector

Assigns the specified weight to each element of the vector.

setweight('fat:2,4 cat:3 rat:5B'::tsvector, 'A')'cat':3A 'fat':2A,4A 'rat':5A

setweight ( vector tsvector, weight "char", lexemes text[] ) → tsvector

Assigns the specified weight to elements of the vector that are listed in lexemes.

setweight('fat:2,4 cat:3 rat:5,6B'::tsvector, 'A', '{cat,rat}')'cat':3A 'fat':2,4 'rat':5A,6A

strip ( tsvector ) → tsvector

Removes positions and weights from the tsvector.

strip('fat:2,4 cat:3 rat:5A'::tsvector)'cat' 'fat' 'rat'

to_tsquery ( [ config regconfig, ] query text ) → tsquery

Converts text to a tsquery, normalizing words according to the specified or default configuration. The words must be combined by valid tsquery operators.

to_tsquery('english', 'The & Fat & Rats')'fat' & 'rat'

to_tsvector ( [ config regconfig, ] document text ) → tsvector

Converts text to a tsvector, normalizing words according to the specified or default configuration. Position information is included in the result.

to_tsvector('english', 'The Fat Rats')'fat':2 'rat':3

to_tsvector ( [ config regconfig, ] document json ) → tsvector

to_tsvector ( [ config regconfig, ] document jsonb ) → tsvector

Converts each string value in the JSON document to a tsvector, normalizing words according to the specified or default configuration. The results are then concatenated in document order to produce the output. Position information is generated as though one stopword exists between each pair of string values. (Beware that document order of the fields of a JSON object is implementation-dependent when the input is jsonb; observe the difference in the examples.)

to_tsvector('english', '{"aa": "The Fat Rats", "b": "dog"}'::json)'dog':5 'fat':2 'rat':3

to_tsvector('english', '{"aa": "The Fat Rats", "b": "dog"}'::jsonb)'dog':1 'fat':4 'rat':5

json_to_tsvector ( [ config regconfig, ] document json, filter jsonb ) → tsvector

jsonb_to_tsvector ( [ config regconfig, ] document jsonb, filter jsonb ) → tsvector

Selects each item in the JSON document that is requested by the filter and converts each one to a tsvector, normalizing words according to the specified or default configuration. The results are then concatenated in document order to produce the output. Position information is generated as though one stopword exists between each pair of selected items. (Beware that document order of the fields of a JSON object is implementation-dependent when the input is jsonb.) The filter must be a jsonb array containing zero or more of these keywords: "string" (to include all string values), "numeric" (to include all numeric values), "boolean" (to include all boolean values), "key" (to include all keys), or "all" (to include all the above). As a special case, the filter can also be a simple JSON value that is one of these keywords.

json_to_tsvector('english', '{"a": "The Fat Rats", "b": 123}'::json, '["string", "numeric"]')'123':5 'fat':2 'rat':3

json_to_tsvector('english', '{"cat": "The Fat Rats", "dog": 123}'::json, '"all"')'123':9 'cat':1 'dog':7 'fat':4 'rat':5

ts_delete ( vector tsvector, lexeme text ) → tsvector

Removes any occurrence of the given lexeme from the vector.

ts_delete('fat:2,4 cat:3 rat:5A'::tsvector, 'fat')'cat':3 'rat':5A

ts_delete ( vector tsvector, lexemes text[] ) → tsvector

Removes any occurrences of the lexemes in lexemes from the vector.

ts_delete('fat:2,4 cat:3 rat:5A'::tsvector, ARRAY['fat','rat'])'cat':3

ts_filter ( vector tsvector, weights "char"[] ) → tsvector

Selects only elements with the given weights from the vector.

ts_filter('fat:2,4 cat:3b,7c rat:5A'::tsvector, '{a,b}')'cat':3B 'rat':5A

ts_headline ( [ config regconfig, ] document text, query tsquery [, options text ] ) → text

Displays, in an abbreviated form, the match(es) for the query in the document, which must be raw text not a tsvector. Words in the document are normalized according to the specified or default configuration before matching to the query. Use of this function is discussed in Section 12.3.4, which also describes the available options.

ts_headline('The fat cat ate the rat.', 'cat')The fat <b>cat</b> ate the rat.

ts_headline ( [ config regconfig, ] document json, query tsquery [, options text ] ) → text

ts_headline ( [ config regconfig, ] document jsonb, query tsquery [, options text ] ) → text

Displays, in an abbreviated form, match(es) for the query that occur in string values within the JSON document. See Section 12.3.4 for more details.

ts_headline('{"cat":"raining cats and dogs"}'::jsonb, 'cat'){"cat": "raining <b>cats</b> and dogs"}

ts_rank ( [ weights real[], ] vector tsvector, query tsquery [, normalization integer ] ) → real

Computes a score showing how well the vector matches the query. See Section 12.3.3 for details.

ts_rank(to_tsvector('raining cats and dogs'), 'cat')0.06079271

ts_rank_cd ( [ weights real[], ] vector tsvector, query tsquery [, normalization integer ] ) → real

Computes a score showing how well the vector matches the query, using a cover density algorithm. See Section 12.3.3 for details.

ts_rank_cd(to_tsvector('raining cats and dogs'), 'cat')0.1

ts_rewrite ( query tsquery, target tsquery, substitute tsquery ) → tsquery

Replaces occurrences of target with substitute within the query. See Section 12.4.2.1 for details.

ts_rewrite('a & b'::tsquery, 'a'::tsquery, 'foo|bar'::tsquery)'b' & ( 'foo' | 'bar' )

ts_rewrite ( query tsquery, select text ) → tsquery

Replaces portions of the query according to target(s) and substitute(s) obtained by executing a SELECT command. See Section 12.4.2.1 for details.

SELECT ts_rewrite('a & b'::tsquery, 'SELECT t,s FROM aliases')'b' & ( 'foo' | 'bar' )

tsquery_phrase ( query1 tsquery, query2 tsquery ) → tsquery

Constructs a phrase query that searches for matches of query1 and query2 at successive lexemes (same as <-> operator).

tsquery_phrase(to_tsquery('fat'), to_tsquery('cat'))'fat' <-> 'cat'

tsquery_phrase ( query1 tsquery, query2 tsquery, distance integer ) → tsquery

Constructs a phrase query that searches for matches of query1 and query2 that occur exactly distance lexemes apart.

tsquery_phrase(to_tsquery('fat'), to_tsquery('cat'), 10)'fat' <10> 'cat'

tsvector_to_array ( tsvector ) → text[]

Converts a tsvector to an array of lexemes.

tsvector_to_array('fat:2,4 cat:3 rat:5A'::tsvector){cat,fat,rat}

unnest ( tsvector ) → setof record ( lexeme text, positions smallint[], weights text )

Expands a tsvector into a set of rows, one per lexeme.

select * from unnest('cat:3 fat:2,4 rat:5A'::tsvector)

 lexeme | positions | weights
--------+-----------+---------
 cat    | {3}       | {D}
 fat    | {2,4}     | {D,D}
 rat    | {5}       | {A}

Note

All the text search functions that accept an optional regconfig argument will use the configuration specified by default_text_search_config when that argument is omitted.

The functions in Table 9.43 are listed separately because they are not usually used in everyday text searching operations. They are primarily helpful for development and debugging of new text search configurations.

Table 9.43. Text Search Debugging Functions

Function

Description

Example(s)

ts_debug ( [ config regconfig, ] document text ) → setof record ( alias text, description text, token text, dictionaries regdictionary[], dictionary regdictionary, lexemes text[] )

Extracts and normalizes tokens from the document according to the specified or default text search configuration, and returns information about how each token was processed. See Section 12.8.1 for details.

ts_debug('english', 'The Brightest supernovaes')(asciiword,"Word, all ASCII",The,{english_stem},english_stem,{}) ...

ts_lexize ( dict regdictionary, token text ) → text[]

Returns an array of replacement lexemes if the input token is known to the dictionary, or an empty array if the token is known to the dictionary but it is a stop word, or NULL if it is not a known word. See Section 12.8.3 for details.

ts_lexize('english_stem', 'stars'){star}

ts_parse ( parser_name text, document text ) → setof record ( tokid integer, token text )

Extracts tokens from the document using the named parser. See Section 12.8.2 for details.

ts_parse('default', 'foo - bar')(1,foo) ...

ts_parse ( parser_oid oid, document text ) → setof record ( tokid integer, token text )

Extracts tokens from the document using a parser specified by OID. See Section 12.8.2 for details.

ts_parse(3722, 'foo - bar')(1,foo) ...

ts_token_type ( parser_name text ) → setof record ( tokid integer, alias text, description text )

Returns a table that describes each type of token the named parser can recognize. See Section 12.8.2 for details.

ts_token_type('default')(1,asciiword,"Word, all ASCII") ...

ts_token_type ( parser_oid oid ) → setof record ( tokid integer, alias text, description text )

Returns a table that describes each type of token a parser specified by OID can recognize. See Section 12.8.2 for details.

ts_token_type(3722)(1,asciiword,"Word, all ASCII") ...

ts_stat ( sqlquery text [, weights text ] ) → setof record ( word text, ndoc integer, nentry integer )

Executes the sqlquery, which must return a single tsvector column, and returns statistics about each distinct lexeme contained in the data. See Section 12.4.4 for details.

ts_stat('SELECT vector FROM apod')(foo,10,15) ...


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