contrib/tsearch2 ( http://www.sai.msu.su/~megera/postgres/gist/tsearch/V2/ )
might works for you. It might because performance depends on
cardinality of your keywords.
Oleg
On Tue, 20 Sep 2005, Yonatan Ben-Nes wrote:
Hi all,
Im building a site where the users can search for products with up to 4
diffrent keywords which all MUST match to each product which found as a
result to the search.
I got 2 tables (which are relevant to the issue :)), one is the product table
(5 million rows) and the other is the keyword table which hold the keywords
of each product (60 million rows).
The scheme of the tables is as follows:
Table "public.product"
Column | Type | Modifiers
----------------------------+---------------+---------------------
product_id | text | not null
product_name | text | not null
retail_price | numeric(10,2) | not null
etc...
Indexes:
"product_product_id_key" UNIQUE, btree (product_id)
Table "public.keyword"
Column | Type | Modifiers
-------------+---------------+-----------
product_id | text | not null
keyword | text | not null
Indexes:
"keyword_keyword" btree (keyword)
The best query which I succeded to do till now is adding the keyword table
for each keyword searched for example if someone search for "belt" & "black"
& "pants" it will create the following query:
poweraise.com=# EXPLAIN ANALYZE SELECT
product_id,product_name,product_image_url,short_product_description,long_product_description,discount,discount_type,sale_price,retail_price
FROM product INNER JOIN keyword t1 USING(product_id) INNER JOIN keyword t2
USING(product_id) INNER JOIN keyword t3 USING(product_id) WHERE
t1.keyword='belt' AND t2.keyword='black' AND t3.keyword='pants' LIMIT 13;
QUERY PLAN
-----------------------------------------------------------------------------------------------------------------------------------------------------------------------
Limit (cost=37734.15..39957.20 rows=13 width=578) (actual
time=969.798..1520.354 rows=6 loops=1)
-> Hash Join (cost=37734.15..3754162.82 rows=21733 width=578) (actual
time=969.794..1520.337 rows=6 loops=1)
Hash Cond: ("outer".product_id = "inner".product_id)
-> Nested Loop (cost=18867.07..2858707.34 rows=55309 width=612)
(actual time=82.266..1474.018 rows=156 loops=1)
-> Hash Join (cost=18867.07..2581181.09 rows=55309 width=34)
(actual time=82.170..1462.104 rows=156 loops=1)
Hash Cond: ("outer".product_id = "inner".product_id)
-> Index Scan using keyword_keyword on keyword t2
(cost=0.00..331244.43 rows=140771 width=17) (actual time=0.033..1307.167
rows=109007 loops=1)
Index Cond: (keyword = 'black'::text)
-> Hash (cost=18851.23..18851.23 rows=6337 width=17)
(actual time=16.145..16.145 rows=0 loops=1)
-> Index Scan using keyword_keyword on keyword t1
(cost=0.00..18851.23 rows=6337 width=17) (actual time=0.067..11.050 rows=3294
loops=1)
Index Cond: (keyword = 'belt'::text)
-> Index Scan using product_product_id_key on product
(cost=0.00..5.01 rows=1 width=578) (actual time=0.058..0.060 rows=1
loops=156)
Index Cond: (product.product_id = "outer".product_id)
-> Hash (cost=18851.23..18851.23 rows=6337 width=17) (actual
time=42.863..42.863 rows=0 loops=1)
-> Index Scan using keyword_keyword on keyword t3
(cost=0.00..18851.23 rows=6337 width=17) (actual time=0.073..36.120 rows=3932
loops=1)
Index Cond: (keyword = 'pants'::text)
Total runtime: 1521.441 ms
(17 rows)
Sometimes the query work fast even for 3 keywords but that doesnt help me if
at other times it take ages....
Now to find a result for 1 keyword its really flying so I also tried to make
3 queries and do INTERSECT between them but it was found out to be extremly
slow...
Whats make this query slow as far as I understand is all the merging between
the results of each table... I tried to divide the keyword table into lots of
keywords table which each hold keywords which start only with a specific
letter, it did improve the speeds but not in a real significant way.. tried
clusters,indexes,SET STATISTICS,WITHOUT OIDS on the keyword table and what
not.. im quite clueless...
Actually I even started to look on other solutions and maybe you can say
something about them also.. maybe they can help me:
1. Omega (From the Xapian project) - http://www.xapian.org/
2. mnoGoSearch - http://www.mnogosearch.org/doc.html
3. Swish-e - http://swish-e.org/index.html
To add on everything I want at the end to be able to ORDER BY the results
like order the product by price, but im less concerned about that cause I saw
that with cluster I can do it without any extra overhead.
Thanks alot in advance,
Yonatan Ben-Nes
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Regards,
Oleg
_____________________________________________________________
Oleg Bartunov, sci.researcher, hostmaster of AstroNet,
Sternberg Astronomical Institute, Moscow University (Russia)
Internet: oleg@xxxxxxxxxx, http://www.sai.msu.su/~megera/
phone: +007(095)939-16-83, +007(095)939-23-83
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