PostgreSQL 8.3.1 Documentation
Prev | Fast Backward | Chapter 12. Full Text Search | Fast Forward | Next

# 12.8. Testing and Debugging Text Search

The behavior of a custom text search configuration can easily become complicated enough to be confusing or undesirable. 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 function `ts_debug` allows 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_debug` displays information about every token of `document` as produced by the parser and processed by the configured dictionaries. It uses the configuration specified by `config`, or `default_text_search_config` if that argument is omitted.

`ts_debug` returns one row for each token identified in the text by the parser. The columns returned are

- `alias` `text` — short name of the token type

- `description` `text` — description of the token type

- `token` `text` — text of the token

- `dictionaries` `regdictionary[]` — the dictionaries selected by the configuration for this token type

- `dictionary` `regdictionary` — the dictionary that recognized the token, or `NULL` if none did

- `lexemes` `text[]` — the lexeme(s) produced by the dictionary that recognized the token, or `NULL` if 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 a `public.english` configuration 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 word `Brightest` was recognized by the parser as an `ASCII word` (alias `asciiword`). For this token type the dictionary list is `english_ispell` and `english_stem`. The word was recognized by `english_ispell`, which reduced it to the noun `bright`. The word `supernovaes` is unknown to the `english_ispell` dictionary so it was passed to the next dictionary, and, fortunately, was recognized (in fact, `english_stem` is a Snowball dictionary which recognizes everything; that is why it was placed at the end of the dictionary list).

The word `The` was recognized by the `english_ispell` dictionary 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 volume of output by explicitly specifying which columns you want to see:

    SELECT alias, token, dictionary, lexemes
    FROM ts_debug('public.english','The Brightest supernovaes');
       alias   |    token    |   dictionary   |   lexemes
    -----------+-------------+----------------+-------------
     asciiword | The         | english_ispell | {}
     blank     |             |                |
     asciiword | Brightest   | english_ispell | {bright}
     blank     |             |                |
     asciiword | supernovaes | english_stem   | {supernova}

## 12.8.2. Parser Testing

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_parse` parses the given `document` and returns a series of records, one for each token produced by parsing. Each record includes a `tokid` showing the assigned token type and a `token` which 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_type` returns a table which describes each type of token the specified parser can recognize. For each token type, the table gives the integer `tokid` that the parser uses to label a token of that type, the `alias` that names the token type in configuration commands, and a short `description`. 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

## 12.8.3. Dictionary Testing

The `ts_lexize` function facilitates dictionary testing.

        ts_lexize(dict regdictionary, token text) returns text[]

`ts_lexize` returns 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, or `NULL` if it is an unknown word.

Examples:

    SELECT ts_lexize('english_stem', 'stars');
     ts_lexize
    -----------
     {star}

    SELECT ts_lexize('english_stem', 'a');
     ts_lexize
    -----------
     {}

> Note: The `ts_lexize` function 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 dictionary `thesaurus_astro` does know the phrase `supernovae stars`, but `ts_lexize` fails since it does not parse the input text but treats it as a single token. Use `plainto_tsquery` or `to_tsvector` to test thesaurus dictionaries, for example:

>     SELECT plainto_tsquery('supernovae stars');
>      plainto_tsquery
>     -----------------
>      'sn'

Prev | Home | Next
Configuration Example | Up | GiST and GIN Index Types