array_to_tsvector ( text[] )
→ tsvector
Converts an array of text strings to a tsvector.
The given strings are used as lexemes as-is, without further
processing. Array elements must not be empty strings
or NULL.
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.
The strings in lexemes are taken as lexemes
as-is, without further processing. Strings that do not match any
lexeme in vector are ignored.
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.
The lexeme string is treated as a lexeme as-is,
without further processing.
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.
The strings in lexemes are taken as lexemes
as-is, without further processing. Strings that do not match any
lexeme in vector are ignored.
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}
|