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12.7.\u00a0Configuration Example
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A text search configuration specifies all options necessary to transform a document into a tsvector: the parser to use to break text into tokens, and the dictionaries to use to transform each token into a lexeme. Every call of to_tsvector or to_tsquery needs a text search configuration to perform its processing. The configuration parameter default_text_search_config specifies the name of the default configuration, which is the one used by text search functions if an explicit configuration parameter is omitted. It can be set in postgresql.conf, or set for an individual session using the SET command.
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Several predefined text search configurations are available, and you can create custom configurations easily. To facilitate management of text search objects, a set of SQL commands is available, and there are several psql commands that display information about text search objects (Section\u00a012.10).
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As an example we will create a configuration pg, starting by duplicating the built-in english configuration:
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CREATE TEXT SEARCH CONFIGURATION public.pg ( COPY = pg_catalog.english );\n
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We will use a PostgreSQL-specific synonym list and store it in $SHAREDIR/tsearch_data/pg_dict.syn. The file contents look like:
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postgres pg\npgsql pg\npostgresql pg\n
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We define the synonym dictionary like this:
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CREATE TEXT SEARCH DICTIONARY pg_dict (\n TEMPLATE = synonym,\n SYNONYMS = pg_dict\n);\n
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Next we register the Ispell dictionary english_ispell, which has its own configuration files:
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CREATE TEXT SEARCH DICTIONARY english_ispell (\n TEMPLATE = ispell,\n DictFile = english,\n AffFile = english,\n StopWords = english\n);\n
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Now we can set up the mappings for words in configuration pg:
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ALTER TEXT SEARCH CONFIGURATION pg\n ALTER MAPPING FOR asciiword, asciihword, hword_asciipart,\n word, hword, hword_part\n WITH pg_dict, english_ispell, english_stem;\n
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We choose not to index or search some token types that the built-in configuration does handle:
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ALTER TEXT SEARCH CONFIGURATION pg\n DROP MAPPING FOR email, url, url_path, sfloat, float;\n
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Now we can test our configuration:
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SELECT * FROM ts_debug('public.pg', '\nPostgreSQL, the highly scalable, SQL compliant, open source object-relational\ndatabase management system, is now undergoing beta testing of the next\nversion of our software.\n');\n\n
The next step is to set the session to use the new configuration, which was created in the public schema:
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=> \\dF\n List of text search configurations\n Schema | Name | Description\n---------+------+-------------\n public | pg |\n\nSET default_text_search_config = 'public.pg';\nSET\n\nSHOW default_text_search_config;\n default_text_search_config\n----------------------------\n public.pg\n
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12.7.\u00a0Configuration Example
\n\n
\n
\n
A text search configuration specifies all options necessary to transform a document into a tsvector: the parser to use to break text into tokens, and the dictionaries to use to transform each token into a lexeme. Every call of to_tsvector or to_tsquery needs a text search configuration to perform its processing. The configuration parameter default_text_search_config specifies the name of the default configuration, which is the one used by text search functions if an explicit configuration parameter is omitted. It can be set in postgresql.conf, or set for an individual session using the SET command.
\n
Several predefined text search configurations are available, and you can create custom configurations easily. To facilitate management of text search objects, a set of SQL commands is available, and there are several psql commands that display information about text search objects (Section\u00a012.10).
\n
As an example we will create a configuration pg, starting by duplicating the built-in english configuration:
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CREATE TEXT SEARCH CONFIGURATION public.pg ( COPY = pg_catalog.english );\n
\n
We will use a PostgreSQL-specific synonym list and store it in $SHAREDIR/tsearch_data/pg_dict.syn. The file contents look like:
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postgres pg\npgsql pg\npostgresql pg\n
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We define the synonym dictionary like this:
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CREATE TEXT SEARCH DICTIONARY pg_dict (\n TEMPLATE = synonym,\n SYNONYMS = pg_dict\n);\n
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Next we register the Ispell dictionary english_ispell, which has its own configuration files:
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CREATE TEXT SEARCH DICTIONARY english_ispell (\n TEMPLATE = ispell,\n DictFile = english,\n AffFile = english,\n StopWords = english\n);\n
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Now we can set up the mappings for words in configuration pg:
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ALTER TEXT SEARCH CONFIGURATION pg\n ALTER MAPPING FOR asciiword, asciihword, hword_asciipart,\n word, hword, hword_part\n WITH pg_dict, english_ispell, english_stem;\n
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We choose not to index or search some token types that the built-in configuration does handle:
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ALTER TEXT SEARCH CONFIGURATION pg\n DROP MAPPING FOR email, url, url_path, sfloat, float;\n
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Now we can test our configuration:
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SELECT * FROM ts_debug('public.pg', '\nPostgreSQL, the highly scalable, SQL compliant, open source object-relational\ndatabase management system, is now undergoing beta testing of the next\nversion of our software.\n');\n\n
The next step is to set the session to use the new configuration, which was created in the public schema:
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=> \\dF\n List of text search configurations\n Schema | Name | Description\n---------+------+-------------\n public | pg |\n\nSET default_text_search_config = 'public.pg';\nSET\n\nSHOW default_text_search_config;\n default_text_search_config\n----------------------------\n public.pg\n
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