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([configregconfig , ] querytext) | tsquery | produce tsquery ignoring punctuation | plainto_tsquery('english', 'The Fat Rats') | 'fat' & 'rat' |
phraseto_tsquery([configregconfig , ] querytext) | tsquery | produce tsquery that searches for a phrase, ignoring punctuation | phraseto_tsquery('english', 'The Fat Rats') | 'fat' <-> 'rat' |
websearch_to_tsquery([configregconfig , ] querytext) | tsquery | produce tsquery from a web search style query | websearch_to_tsquery('english', '"fat rat" or rat') | 'fat' <-> 'rat' | 'rat' |
querytree(querytsquery) | text | get indexable part of a tsquery | querytree('foo & ! bar'::tsquery) | 'foo' |
setweight(vectortsvector, 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(vectortsvector, weight"char", lexemestext[]) | 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([configregconfig , ] querytext) | tsquery | normalize words and convert to tsquery | to_tsquery('english', 'The & Fat & Rats') | 'fat' & 'rat' |
to_tsvector([configregconfig , ] documenttext) | tsvector | reduce document text to tsvector | to_tsvector('english', 'The Fat Rats') | 'fat':2 'rat':3 |
to_tsvector([configregconfig , ] documentjson(b)) | tsvector | reduce each string value in the document to a tsvector, and then concatenate those in document order to produce a single tsvector | to_tsvector('english', '{"a": "The Fat Rats"}'::json) | 'fat':2 'rat':3 |
json(b)_to_tsvector([configregconfig, ] documentjson(b), filterjson(b)) | tsvector | reduce each value in the document, specified by filter to a tsvector, and then concatenate those in document order to produce a single tsvector. filter is a jsonb array, that enumerates what kind of elements need to be included into the resulting tsvector. Possible values for filter are "string" (to include all string values), "numeric" (to include all numeric values in the string format), "boolean" (to include all Boolean values in the string format "true"/"false"), "key" (to include all keys) or "all" (to include all above). These values can be combined together to include, e.g., all string and numeric values. | json_to_tsvector('english', '{"a": "The Fat Rats", "b": 123}'::json, '["string", "numeric"]') | '123':5 'fat':2 'rat':3 |
ts_delete(vectortsvector, lexemetext) | tsvector | remove given lexeme from vector | ts_delete('fat:2,4 cat:3 rat:5A'::tsvector, 'fat') | 'cat':3 'rat':5A |
ts_delete(vectortsvector, lexemestext[]) | 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(vectortsvector, 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([configregconfig, ] documenttext, querytsquery [, optionstext]) | text | display a query match | ts_headline('x y z', 'z'::tsquery) | x y <b>z</b> |
ts_headline([configregconfig, ] documentjson(b), querytsquery [, optionstext]) | text | display a query match | ts_headline('{"a":"x y z"}'::json, 'z'::tsquery) | {"a":"x y <b>z</b>"} |
ts_rank([weightsfloat4[], ] vectortsvector, querytsquery [, normalizationinteger]) | float4 | rank document for query | ts_rank(textsearch, query) | 0.818 |
ts_rank_cd([weightsfloat4[], ] vectortsvector, querytsquery [, normalizationinteger]) | 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(querytsquery, targettsquery, substitutetsquery) | tsquery | replace target with substitute within query | ts_rewrite('a & b'::tsquery, 'a'::tsquery, 'foo|bar'::tsquery) | 'b' & ( 'foo' | 'bar' ) |
ts_rewrite(querytsquery, selecttext) | 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(query1tsquery, query2tsquery) | 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(query1tsquery, query2tsquery, distanceinteger) | tsquery | make query that searches for query1 followed by query2 at 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 lexemetext, OUT positionssmallint[], OUT weightstext) | setof record | expand a tsvector to a set of rows | unnest('fat:2,4 cat:3 rat:5A'::tsvector) | (cat,{3},{D}) ... |
