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' |
websearch_to_tsquery([ config regconfig , ] query text) | tsquery | produce tsquery from a web search style query | websearch_to_tsquery('english', '"fat rat" or rat') | 'fat' <-> 'rat' | '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 |
to_tsvector([ config regconfig , ] document json(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([ config regconfig, ] document json(b), filter json(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(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_headline([ config regconfig, ] document json(b), query tsquery [, options text ]) | text | display a query match | ts_headline('{"a":"x y z"}'::json, 'z'::tsquery) | {"a":"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 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}) ... |
