Re: Slow search.. quite clueless

> 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.

Seconded. We use tsearch2 to earch about 40,000 rows containing
manufacturer, brand, and product name and it returns a result almost
instantly. Before when we did normal SQL "manufacture LIKE ..., etc." it
would take 20-30 seconds.

One thing to check is the english.stop file which contains words to skip
(i, a, the, etc.). In our case we removed almost all of them since one of
our products is "7 up" (the drink) and it would remove "up". Made it
really hard to pull up 7 up in the results :)

-philip

>
> 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
>>
>>
>> ---------------------------(end of broadcast)---------------------------
>> TIP 1: if posting/reading through Usenet, please send an appropriate
>> subscribe-nomail command to majordomo(at)postgresql(dot)org so that your
>> message can get through to the mailing list cleanly
>>
>
> Regards,
> Oleg
> _____________________________________________________________
> Oleg Bartunov, sci.researcher, hostmaster of AstroNet,
> Sternberg Astronomical Institute, Moscow University (Russia)
> Internet: oleg(at)sai(dot)msu(dot)su, http://www.sai.msu.su/~megera/
> phone: +007(095)939-16-83, +007(095)939-23-83
>
> ---------------------------(end of broadcast)---------------------------
> TIP 9: In versions below 8.0, the planner will ignore your desire to
> choose an index scan if your joining column's datatypes do not
> match
>