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ts_rank seems very slow (140 ranked documents / second on my machine)

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Hello,

I'm testing PostgreSQL full-text search on a table containing
1.000.000 documents. Document average length is 5.700 chars.
Performance is good and very similar to what I can get with Xapian if
I don't use ts_rank. But response time collapses if I use ts_rank to
select the 50 best matching documents.

This is the table and index definition:

create table posts_1000000 (
  id serial primary key,
  document_vector tsvector
);
create index index_posts_documents_1000000 ON posts_1000000 USING
gin(document_vector);

This is the query without ts_rank (the word 'crare' matches 5 % of documents):

select id
from posts_1000000
where to_tsquery('english', 'crare') @@ document_vector
limit 50

Limit  (cost=0.00..27.93 rows=50 width=4) (actual time=0.303..12.559
rows=50 loops=1)
  Output: id
  ->  Seq Scan on posts_1000000  (cost=0.00..27472.51 rows=49184
width=4) (actual time=0.299..12.451 rows=50 loops=1)
        Output: id
        Filter: ('''crare'''::tsquery @@ document_vector)
Total runtime: 12.642 ms

Now, this is the query using ts_rank:

select id
from posts_1000000
where to_tsquery('english', 'crare') @@ document_vector
order by ts_rank_cd(document_vector, to_tsquery('english', 'crare'), 32) desc
limit 50

Limit  (cost=29229.33..29229.45 rows=50 width=22) (actual
time=355516.233..355516.339 rows=50 loops=1)
  Output: id
  ->  Sort  (cost=29229.33..29352.29 rows=49184 width=22) (actual
time=355516.230..355516.268 rows=50 loops=1)
        Output: id
        Sort Key: (ts_rank_cd(document_vector, '''crare'''::tsquery, 32))
        Sort Method:  top-N heapsort  Memory: 27kB
        ->  Seq Scan on posts_1000000  (cost=0.00..27595.47 rows=49184
width=22) (actual time=0.251..355389.367 rows=49951 loops=1)
              Output: id
              Filter: ('''crare'''::tsquery @@ document_vector)
Total runtime: 355535.063 ms

The ranking is very slow: 140 ranked documents / second on my machine!

I'm afraid this is because ts_rank needs to read document_vector, and
because that column is stored in TOAST table, it triggers a random
access for each matching row. Am I correct? Is it the expected
behavior? Is there a way to reduce the execution time?

I use PostgreSQL 8.4 with shared_buffers = 256 MB, work_mem = 256 MB.

Thanks for your help and advice.

-- 
Nicolas Grilly
Garden
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www.gardentechno.com - Développement web & reporting / Web development
& data analytics
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