Text Search Functions and Operators

Table 9-39, Table 9-40 and Table 9-41 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 9-39. Text Search Operators

Operator Return Type Description Example Result
@@ boolean tsvector matches tsquery ? to_tsvector('fat cats ate rats') @@ to_tsquery('cat & rat') t
@@@ boolean deprecated synonym for @@ to_tsvector('fat cats ate rats') @@@ to_tsquery('cat & rat') t
|| tsvector concatenate tsvectors 'a:1 b:2'::tsvector || 'c:1 d:2 b:3'::tsvector 'a':1 'b':2,5 'c':3 'd':4
&& tsquery AND tsquerys together 'fat | rat'::tsquery && 'cat'::tsquery ( 'fat' | 'rat' ) & 'cat'
|| tsquery OR tsquerys together 'fat | rat'::tsquery || 'cat'::tsquery ( 'fat' | 'rat' ) | 'cat'
!! tsquery negate a tsquery !! 'cat'::tsquery !'cat'
<-> tsquery tsquery followed by tsquery to_tsquery('fat') <-> to_tsquery('rat') 'fat' <-> 'rat'
@> boolean tsquery contains another ? 'cat'::tsquery @> 'cat & rat'::tsquery f
<@ boolean tsquery is contained in ? 'cat'::tsquery <@ 'cat & rat'::tsquery t

Note: The tsquery containment operators consider only the lexemes listed in the two queries, ignoring the combining operators.

In addition to the operators shown in the table, the ordinary B-tree comparison operators (=, <, etc) are defined 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 9-40. Text Search Functions

Function Return Type Description Example Result
array_to_tsvector(text[]) tsvector convert array of lexemes to tsvector array_to_tsvector('{fat,cat,rat}'::text[]) 'cat' 'fat' 'rat'
get_current_ts_config() regconfig get default text search configuration get_current_ts_config() english
length(tsvector) integer number of lexemes in tsvector length('fat:2,4 cat:3 rat:5A'::tsvector) 3
numnode(tsquery) integer number of lexemes plus operators in tsquery numnode('(fat & rat) | cat'::tsquery) 5
plainto_tsquery([ config regconfig , ] query text) tsquery produce tsquery ignoring punctuation plainto_tsquery('english', 'The Fat Rats') 'fat' & 'rat'
phraseto_tsquery([ config regconfig , ] query text) tsquery produce tsquery that searches for a phrase, ignoring punctuation phraseto_tsquery('english', 'The Fat Rats') 'fat' <-> 'rat'
querytree(query tsquery) text get indexable part of a tsquery querytree('foo & ! bar'::tsquery) 'foo'
setweight(vector tsvector, weight "char") tsvector assign weight to each element of 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 assign weight to elements of vector that are listed in lexemes setweight('fat:2,4 cat:3 rat:5B'::tsvector, 'A', '{cat,rat}') 'cat':3A 'fat':2,4 'rat':5A
strip(tsvector) tsvector remove positions and weights from tsvector strip('fat:2,4 cat:3 rat:5A'::tsvector) 'cat' 'fat' 'rat'
to_tsquery([ config regconfig , ] query text) tsquery normalize words and convert to tsquery to_tsquery('english', 'The & Fat & Rats') 'fat' & 'rat'
to_tsvector([ config regconfig , ] document text) tsvector reduce document text to tsvector to_tsvector('english', 'The Fat Rats') 'fat':2 'rat':3
ts_delete(vector tsvector, lexeme text) tsvector remove given lexeme from vector ts_delete('fat:2,4 cat:3 rat:5A'::tsvector, 'fat') 'cat':3 'rat':5A
ts_delete(vector tsvector, lexemes text[]) tsvector remove any occurrence of lexemes in lexemes from vector ts_delete('fat:2,4 cat:3 rat:5A'::tsvector, ARRAY['fat','rat']) 'cat':3
ts_filter(vector tsvector, weights "char"[]) tsvector select only elements with given weights from vector ts_filter('fat:2,4 cat:3b rat:5A'::tsvector, '{a,b}') 'cat':3B 'rat':5A
ts_headline([ config regconfig, ] document text, query tsquery [, options text ]) text display a query match ts_headline('x y z', 'z'::tsquery) x y <b>z</b>
ts_rank([ weights float4[], ] vector tsvector, query tsquery [, normalization integer ]) float4 rank document for query ts_rank(textsearch, query) 0.818
ts_rank_cd([ weights float4[], ] vector tsvector, query tsquery [, normalization integer ]) float4 rank document for query using cover density ts_rank_cd('{0.1, 0.2, 0.4, 1.0}', textsearch, query) 2.01317
ts_rewrite(query tsquery, target tsquery, substitute tsquery) tsquery replace target with substitute within query ts_rewrite('a & b'::tsquery, 'a'::tsquery, 'foo|bar'::tsquery) 'b' & ( 'foo' | 'bar' )
ts_rewrite(query tsquery, select text) tsquery replace using targets and substitutes from a SELECT command SELECT ts_rewrite('a & b'::tsquery, 'SELECT t,s FROM aliases') 'b' & ( 'foo' | 'bar' )
tsquery_phrase(query1 tsquery, query2 tsquery) tsquery make query that searches for query1 followed by query2 (same as <-> operator) tsquery_phrase(to_tsquery('fat'), to_tsquery('cat')) 'fat' <-> 'cat'
tsquery_phrase(query1 tsquery, query2 tsquery, distance integer) tsquery make query that searches for query1 followed by query2 at maximum distance distance tsquery_phrase(to_tsquery('fat'), to_tsquery('cat'), 10) 'fat' <10> 'cat'
tsvector_to_array(tsvector) text[] convert tsvector to array of lexemes tsvector_to_array('fat:2,4 cat:3 rat:5A'::tsvector) {cat,fat,rat}
tsvector_update_trigger() trigger trigger function for automatic tsvector column update CREATE TRIGGER ... tsvector_update_trigger(tsvcol, 'pg_catalog.swedish', title, body)
tsvector_update_trigger_column() trigger trigger function for automatic tsvector column update CREATE TRIGGER ... tsvector_update_trigger_column(tsvcol, configcol, title, body)
unnest(tsvector, OUT lexeme text, OUT positions smallint[], OUT weights text) setof record expand a tsvector to a set of rows unnest('fat:2,4 cat:3 rat:5A'::tsvector) (cat,{3},{D}) ...

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 9-41 are listed separately because they are not usually used in everyday text searching operations. They are helpful for development and debugging of new text search configurations.

Table 9-41. Text Search Debugging Functions

Function Return Type Description Example Result
ts_debug([ config regconfig, ] document text, OUT alias text, OUT description text, OUT token text, OUT dictionaries regdictionary[], OUT dictionary regdictionary, OUT lexemes text[]) setof record test a configuration ts_debug('english', 'The Brightest supernovaes') (asciiword,"Word, all ASCII",The,{english_stem},english_stem,{}) ...
ts_lexize(dict regdictionary, token text) text[] test a dictionary ts_lexize('english_stem', 'stars') {star}
ts_parse(parser_name text, document text, OUT tokid integer, OUT token text) setof record test a parser ts_parse('default', 'foo - bar') (1,foo) ...
ts_parse(parser_oid oid, document text, OUT tokid integer, OUT token text) setof record test a parser ts_parse(3722, 'foo - bar') (1,foo) ...
ts_token_type(parser_name text, OUT tokid integer, OUT alias text, OUT description text) setof record get token types defined by parser ts_token_type('default') (1,asciiword,"Word, all ASCII") ...
ts_token_type(parser_oid oid, OUT tokid integer, OUT alias text, OUT description text) setof record get token types defined by parser ts_token_type(3722) (1,asciiword,"Word, all ASCII") ...
ts_stat(sqlquery text, [ weights text, ] OUT word text, OUT ndoc integer, OUT nentry integer) setof record get statistics of a tsvector column ts_stat('SELECT vector from apod') (foo,10,15) ...
doc_PostgreSQL
2016-10-12 11:34:23
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