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diff --git a/contrib/pg_trgm/README.pg_trgm b/contrib/pg_trgm/README.pg_trgm deleted file mode 100644 index e7ff73e4f1..0000000000 --- a/contrib/pg_trgm/README.pg_trgm +++ /dev/null @@ -1,144 +0,0 @@ -trgm - Trigram matching for PostgreSQL --------------------------------------- - -Introduction - - This module is sponsored by Delta-Soft Ltd., Moscow, Russia. - - The pg_trgm contrib module provides functions and index classes - for determining the similarity of text based on trigram - matching. - -Definitions - - Trigram (or Trigraph) - - A trigram is a set of three consecutive characters taken - from a string. A string is considered to have two spaces - prefixed and one space suffixed when determining the set - of trigrams that comprise the string. - - eg. The set of trigrams in the word "cat" is " c", " ca", - "at " and "cat". - -Public Functions - - real similarity(text, text) - - Returns a number that indicates how closely matches the two - arguments are. A zero result indicates that the two words - are completely dissimilar, and a result of one indicates that - the two words are identical. - - real show_limit() - - Returns the current similarity threshold used by the '%' - operator. This in effect sets the minimum similarity between - two words in order that they be considered similar enough to - be misspellings of each other, for example. - - real set_limit(real) - - Sets the current similarity threshold that is used by the '%' - operator, and is returned by the show_limit() function. - - text[] show_trgm(text) - - Returns an array of all the trigrams of the supplied text - parameter. - -Public Operators - - text % text (returns boolean) - - The '%' operator returns TRUE if its two arguments have a similarity - that is greater than the similarity threshold set by set_limit(). It - will return FALSE if the similarity is less than the current - threshold. - -Public Index Operator Classes - - gist_trgm_ops - - The pg_trgm module comes with an index operator class that allows a - developer to create an index over a text column for the purpose - of very fast similarity searches. - - To use this index, the '%' operator must be used and an appropriate - similarity threshold for the application must be set. - - eg. - - CREATE TABLE test_trgm (t text); - CREATE INDEX trgm_idx ON test_trgm USING gist (t gist_trgm_ops); - - At this point, you will have an index on the t text column that you - can use for similarity searching. - - eg. - - SELECT - t, - similarity(t, 'word') AS sml - FROM - test_trgm - WHERE - t % 'word' - ORDER BY - sml DESC, t; - - This will return all values in the text column that are sufficiently - similar to 'word', sorted from best match to worst. The index will - be used to make this a fast operation over very large data sets. - -Tsearch2 Integration - - Trigram matching is a very useful tool when used in conjunction - with a text index created by the Tsearch2 contrib module. (See - contrib/tsearch2) - - The first step is to generate an auxiliary table containing all - the unique words in the Tsearch2 index: - - CREATE TABLE words AS SELECT word FROM - stat('SELECT to_tsvector(''simple'', bodytext) FROM documents'); - - Where 'documents' is a table that has a text field 'bodytext' - that TSearch2 is used to search. The use of the 'simple' dictionary - with the to_tsvector function, instead of just using the already - existing vector is to avoid creating a list of already stemmed - words. This way, only the original, unstemmed words are added - to the word list. - - Next, create a trigram index on the word column: - - CREATE INDEX words_idx ON words USING gist(word gist_trgm_ops); - or - CREATE INDEX words_idx ON words USING gin(word gist_trgm_ops); - - Now, a SELECT query similar to the example above can be used to - suggest spellings for misspelled words in user search terms. A - useful extra clause is to ensure that the similar words are also - of similar length to the misspelled word. - - Note: Since the 'words' table has been generated as a separate, - static table, it will need to be periodically regenerated so that - it remains up to date with the word list in the Tsearch2 index. - -Authors - - Oleg Bartunov <oleg@sai.msu.su>, Moscow, Moscow University, Russia - Teodor Sigaev <teodor@sigaev.ru>, Moscow, Delta-Soft Ltd.,Russia - -Contributors - - Christopher Kings-Lynne wrote this README file - -References - - Tsearch2 Development Site - http://www.sai.msu.su/~megera/postgres/gist/tsearch/V2/ - - GiST Development Site - http://www.sai.msu.su/~megera/postgres/gist/ - |