The behavior of a custom text search configuration can easily become confusing. The functions described in this section are useful for testing text search objects. You can test a complete configuration, or test parsers and dictionaries separately.
12.8.1. Configuration Testing
The functionts_debugallows easy testing of a text search configuration.
ts_debug([
config
regconfig
,
]
document
text
,
OUT
alias
text
,
OUT
description
text
,
OUT
token
text
,
OUT
dictionaries
regdictionary[]
,
OUT
dictionary
regdictionary
,
OUT
lexemes
text[]
)
returns setof record
ts_debugdisplays information about every token ofdocument_as produced by the parser and processed by the configured dictionaries. It uses the configuration specified byconfig_, ordefault_text_search_configif that argument is omitted.
ts_debugreturns one row for each token identified in the text by the parser. The columns returned are
aliastext— short name of the token type
descriptiontext— description of the token type
tokentext— text of the token
dictionariesregdictionary[]— the dictionaries selected by the configuration for this token type
dictionaryregdictionary— the dictionary that recognized the token, orNULLif none did
lexemestext[]— the lexeme(s) produced by the dictionary that recognized the token, orNULLif none did; an empty array ({}) means it was recognized as a stop word
Here is a simple example:
SELECT * FROM ts_debug('english','a fat cat sat on a mat - it ate a fat rats');
alias | description | token | dictionaries | dictionary | lexemes
-----------+-----------------+-------+----------------+--------------+---------
asciiword | Word, all ASCII | a | {english_stem} | english_stem | {}
blank | Space symbols | | {} | |
asciiword | Word, all ASCII | fat | {english_stem} | english_stem | {fat}
blank | Space symbols | | {} | |
asciiword | Word, all ASCII | cat | {english_stem} | english_stem | {cat}
blank | Space symbols | | {} | |
asciiword | Word, all ASCII | sat | {english_stem} | english_stem | {sat}
blank | Space symbols | | {} | |
asciiword | Word, all ASCII | on | {english_stem} | english_stem | {}
blank | Space symbols | | {} | |
asciiword | Word, all ASCII | a | {english_stem} | english_stem | {}
blank | Space symbols | | {} | |
asciiword | Word, all ASCII | mat | {english_stem} | english_stem | {mat}
blank | Space symbols | | {} | |
blank | Space symbols | - | {} | |
asciiword | Word, all ASCII | it | {english_stem} | english_stem | {}
blank | Space symbols | | {} | |
asciiword | Word, all ASCII | ate | {english_stem} | english_stem | {ate}
blank | Space symbols | | {} | |
asciiword | Word, all ASCII | a | {english_stem} | english_stem | {}
blank | Space symbols | | {} | |
asciiword | Word, all ASCII | fat | {english_stem} | english_stem | {fat}
blank | Space symbols | | {} | |
asciiword | Word, all ASCII | rats | {english_stem} | english_stem | {rat}
For a more extensive demonstration, we first create apublic.englishconfiguration and Ispell dictionary for the English language:
CREATE TEXT SEARCH CONFIGURATION public.english ( COPY = pg_catalog.english );
CREATE TEXT SEARCH DICTIONARY english_ispell (
TEMPLATE = ispell,
DictFile = english,
AffFile = english,
StopWords = english
);
ALTER TEXT SEARCH CONFIGURATION public.english
ALTER MAPPING FOR asciiword WITH english_ispell, english_stem;
SELECT * FROM ts_debug('public.english','The Brightest supernovaes');
alias | description | token | dictionaries | dictionary | lexemes
-----------+-----------------+-------------+-------------------------------+----------------+-------------
asciiword | Word, all ASCII | The | {english_ispell,english_stem} | english_ispell | {}
blank | Space symbols | | {} | |
asciiword | Word, all ASCII | Brightest | {english_ispell,english_stem} | english_ispell | {bright}
blank | Space symbols | | {} | |
asciiword | Word, all ASCII | supernovaes | {english_ispell,english_stem} | english_stem | {supernova}
In this example, the wordBrightestwas recognized by the parser as anASCII word(aliasasciiword). For this token type the dictionary list isenglish_ispellandenglish_stem. The word was recognized byenglish_ispell, which reduced it to the nounbright. The wordsupernovaesis unknown to theenglish_ispelldictionary so it was passed to the next dictionary, and, fortunately, was recognized (in fact,english_stemis a Snowball dictionary which recognizes everything; that is why it was placed at the end of the dictionary list).
The wordThewas recognized by theenglish_ispelldictionary as a stop word (Section 12.6.1) and will not be indexed. The spaces are discarded too, since the configuration provides no dictionaries at all for them.
You can reduce the width of the output by explicitly specifying which columns you want to see:
The following functions allow direct testing of a text search parser.
ts_parse(
parser_name
text
,
document
text
,
OUT
tokid
integer
, OUT
token
text
) returns
setof record
ts_parse(
parser_oid
oid
,
document
text
,
OUT
tokid
integer
, OUT
token
text
) returns
setof record
ts_parseparses the given_document_and returns a series of records, one for each token produced by parsing. Each record includes atokidshowing the assigned token type and atokenwhich is the text of the token. For example:
SELECT * FROM ts_parse('default', '123 - a number');
tokid | token
-------+--------
22 | 123
12 |
12 | -
1 | a
12 |
1 | number
ts_token_type(
parser_name
text
, OUT
tokid
integer
,
OUT
alias
text
, OUT
description
text
) returns
setof record
ts_token_type(
parser_oid
oid
, OUT
tokid
integer
,
OUT
alias
text
, OUT
description
text
) returns
setof record
ts_token_typereturns a table which describes each type of token the specified parser can recognize. For each token type, the table gives the integertokidthat the parser uses to label a token of that type, thealiasthat names the token type in configuration commands, and a shortdescription. For example:
SELECT * FROM ts_token_type('default');
tokid | alias | description
-------+-----------------+------------------------------------------
1 | asciiword | Word, all ASCII
2 | word | Word, all letters
3 | numword | Word, letters and digits
4 | email | Email address
5 | url | URL
6 | host | Host
7 | sfloat | Scientific notation
8 | version | Version number
9 | hword_numpart | Hyphenated word part, letters and digits
10 | hword_part | Hyphenated word part, all letters
11 | hword_asciipart | Hyphenated word part, all ASCII
12 | blank | Space symbols
13 | tag | XML tag
14 | protocol | Protocol head
15 | numhword | Hyphenated word, letters and digits
16 | asciihword | Hyphenated word, all ASCII
17 | hword | Hyphenated word, all letters
18 | url_path | URL path
19 | file | File or path name
20 | float | Decimal notation
21 | int | Signed integer
22 | uint | Unsigned integer
23 | entity | XML entity
ts_lexize(
dict
regdictionary
,
token
text
) returns
text[]
ts_lexizereturns an array of lexemes if the input_token_is known to the dictionary, or an empty array if the token is known to the dictionary but it is a stop word, orNULLif it is an unknown word.
Thets_lexizefunction expects a single_token_, not text. Here is a case where this can be confusing:
SELECT ts_lexize('thesaurus_astro','supernovae stars') is null;
?column?
----------
t
The thesaurus dictionarythesaurus_astrodoes know the phrasesupernovae stars, butts_lexizefails since it does not parse the input text but treats it as a single token. Useplainto_tsqueryorto_tsvectorto test thesaurus dictionaries, for example:
