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'
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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
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length ( tsvector ) → integer Returns the number of lexemes in the tsvector. length('fat:2,4 cat:3 rat:5A'::tsvector) → 3
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numnode ( tsquery ) → integer Returns the number of lexemes plus operators in the tsquery. numnode('(fat & rat) | cat'::tsquery) → 5
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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'
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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'
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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'
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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'
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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
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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
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strip ( tsvector ) → tsvector Removes positions and weights from the tsvector. strip('fat:2,4 cat:3 rat:5A'::tsvector) → 'cat' 'fat' 'rat'
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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'
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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
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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
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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
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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
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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
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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
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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.
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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"}
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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
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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
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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' )
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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' )
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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'
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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'
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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}
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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}
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