Le 03 mars 2017 à 14:08, Artur Zakirov écrivait :
> On 03.03.2017 15:49, Nicolas Paris wrote:
> >
> >Hi Oleg,
> >
> >Thanks. I thought pgtrgm was not able to index my long texts because of
> >limitation of 8191 bytes per index row for btree.
> >
> >Then I found out it is possible to use pgtrgm over a GIN/GIST index.
> >My final use case is phrase mining in texts.
> >
> >I want my application returns texts that contains approximatly the user
> >entry:
> >
> >Eg: user search "Hello Word"
> >a text containing "blah blah blah hello world blah blah blah" would be
> >returned.
> >
> >Test:
> >postgres=# CREATE table test_trgm (texts text);
> >CREATE TABLE
> >postgres=# CREATE INDEX ON test_trgm USING GIN(texts gin_trgm_ops);
> >CREATE INDEX
> >postgres=# SET enable_seqscan = OFF;
> >SET
> >postgres=# insert into test_trgm VALUES ('blah blah blah hello world blah
> >blah blah');
> >INSERT 0 1
> >postgres=# insert into test_trgm VALUES ('blah blah blah hello word blah
> >blah blah');
> >INSERT 0 1
> >postgres=# SELECT texts, similarity(texts, 'hello word') FROM test_trgm
> >WHERE texts % 'hello word';
> > texts | similarity
> >-------------------------------------------+------------
> > blah blah blah hello world blah blah blah | 0.473684
> > blah blah blah hello word blah blah blah | 0.6875
> >(2 rows)
> >
> >postgres=# EXPLAIN SELECT texts, similarity(texts, 'hello word') FROM
> >test_trgm WHERE texts % 'hello word';
> > QUERY PLAN
> >-----------------------------------------------------------------------------------
> > Bitmap Heap Scan on test_trgm (cost=52.01..56.03 rows=1 width=32)
> > Recheck Cond: (texts % 'hello word'::text)
> > -> Bitmap Index Scan on test_trgm_texts_idx (cost=0.00..52.01 rows=1
> > width=0)
> > Index Cond: (texts % 'hello word'::text)
> >(4 rows)
> >
> >Conclusion: If I d'say 0.4 is my threshold, would this methodology meet
> >my requirements ?
> >
> >Thanks for the help !
> >
>
> Hello,
>
> If you use PostgreSQL 9.6, then word_similarity() can help you [1]. For
> example:
>
> postgres=# SELECT texts, word_similarity('hello word', texts) FROM test_trgm
> WHERE 'hello word' <% texts;
> texts | word_similarity
> -------------------------------------------+-----------------
> blah blah blah hello world blah blah blah | 0.818182
> blah blah blah hello word blah blah blah | 1
> (2 rows)
>
> 1. https://www.postgresql.org/docs/9.6/static/pgtrgm.html
>
Nice ! I do have 9.6 version.
Would this kind of index could handle more than 20M large texts ? The
recheck condition looks ressource consuming.
The full text index + phrase search + synonym dictionnary is the only
other alternativ to deal with typo-phrase mining ?
Is there any possibility in the future to add typo in the full text
road-map ?
Thanks,
> --
> Artur Zakirov
> Postgres Professional: http://www.postgrespro.com
> Russian Postgres Company
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