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| author | Tom Lane <tgl@sss.pgh.pa.us> | 2004-11-27 00:01:02 +0000 |
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| committer | Tom Lane <tgl@sss.pgh.pa.us> | 2004-11-27 00:01:02 +0000 |
| commit | b82323e05e57d7c4fb7a8eab9f27eb059d28309a (patch) | |
| tree | 9ec63971295146e7dc4033744db129e2921893a1 | |
| parent | c2e563176049e514b8af1af4b759ef4e64850cdc (diff) | |
| download | postgresql-b82323e05e57d7c4fb7a8eab9f27eb059d28309a.tar.gz postgresql-b82323e05e57d7c4fb7a8eab9f27eb059d28309a.zip | |
This adds mention of my latest tweak to the tsearch2/pg_trgm
integration. It is much better to create a word list of unstemmed words
than stemmed ones.
Chris K-L
| -rw-r--r-- | contrib/pg_trgm/README.pg_trgm | 14 |
1 files changed, 9 insertions, 5 deletions
diff --git a/contrib/pg_trgm/README.pg_trgm b/contrib/pg_trgm/README.pg_trgm index ac2eb012de5..608c30c455c 100644 --- a/contrib/pg_trgm/README.pg_trgm +++ b/contrib/pg_trgm/README.pg_trgm @@ -100,11 +100,15 @@ Tsearch2 Integration 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 vector FROM documents'); - - Where 'documents' is the table that contains the Tsearch2 index - column 'vector', of type 'tsvector'. + 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: |