Re: bad query performance - Mailing list pgsql-sql

At 18:54 5/14/2003, Luis Sousa wrote:
>Stephan Szabo wrote:
>
>>On Mon, 12 May 2003, Didrik Pinte wrote:
>>
>>
>>
>>>Here is the query :
>>>------------------------------------------------------------------------------------
>>>SELECT profiles_et.username, profiles_et.name, profiles_et.firstname,
>>>profiles_et.email, company_et.name AS company, count(logs_et.dt) AS cnt,
>>>pro_invoice_addr_at.id
>>>
>>>
>>>FROM
>>>(
>>>      (
>>>                  (
>>>                            secu.company_et  JOIN secu.pro_invoice_addr_at
>>>ON (pro_invoice_addr_at.company = company_et.id)
>>>                  )
>>>
>>>                JOIN secu.profiles_et ON (pro_invoice_addr_at.profile =
>>>profiles_et.id)
>>>      )
>>>     JOIN  secu.logs_et ON (logs_et.invaddr = pro_invoice_addr_at.id)
>>>)
>>>
>>>
>>>  GROUP BY profiles_et.username, profiles_et.name, profiles_et.firstname,
>>>profiles_et.email, company_et.name, pro_invoice_addr_at.id
>>>
>>>ORDER BY count(logs_et.dt) DESC;
>>>------------------------------------------------------------------------------------
>>>
>>>
>>>
>>>The secu_company, secu_prov_invoice_addr_at and secu_profiles contains only
>>>informations about the users.
>>>
>>>The query is executing in 8,6 minutes.... Indexes are defined on all the
>>>field used in the different joins.
>>>
>>
>>Have you recently analyzed the tables involved?
>>I'd guess that the two outer sorts and the sort on logs_et are probably
>>the killers, but can you send explain analyze output?  Looking at the
>>estimated row numbers and width, it seems to me that with 16Mb of sort_mem
>>it's going to have to sort on disk (although you don't have enough memory
>>to up it far enough probably if the estimates are right)
>>
>>
>>
>>
>>>Here is the query plan :
>>>
>>>------------------------------------------------------------------------------------
>>>Sort  (cost=895649.54..896073.23 rows=169474 width=145)
>>>   Sort Key: count(logs_et.dt)
>>>   ->  Aggregate  (cost=831240.24..865135.10 rows=169474 width=145)
>>>         ->  Group  (cost=831240.24..860898.24 rows=1694743 width=145)
>>>               ->  Sort  (cost=831240.24..835477.10 rows=1694743 width=145)
>>>                     Sort Key: profiles_et.username, profiles_et.name,
>>>profiles_et.firstname, profiles_et.email, company_et.name,
>>>pro_invoice_addr_at.id
>>>                     ->  Merge Join  (cost=274406.73..304066.75
>>>rows=1694743 width=145)
>>>                           Merge Cond: ("outer".id = "inner".invaddr)
>>>                           ->  Sort  (cost=143.81..144.92 rows=446 
>>> width=126)
>>>                                 Sort Key: pro_invoice_addr_at.id
>>>                                 ->  Merge Join  (cost=90.27..124.18
>>>rows=446 width=126)
>>>                                       Merge Cond: ("outer".id =
>>>"inner".profile)
>>>                                       ->  Index Scan using profiles_pk on
>>>profiles_et  (cost=0.00..24.98 rows=449 width=66)
>>>                                       ->  Sort  (cost=90.27..91.39
>>>rows=446 width=60)
>>>                                             Sort Key:
>>>pro_invoice_addr_at.profile
>>>                                             ->  Merge
>>>Join  (cost=37.82..70.65 rows=446 width=60)
>>>                                                   Merge Cond:
>>>("outer".company = "inner".id)
>>>                                                   ->  Index Scan using
>>>invaddr_at_company_idx on pro_invoice_addr_at  (cost=0.00..24.68 rows=446
>>>width=33)
>>>                                                   ->  Sort
>>>(cost=37.82..38.55 rows=291 width=27)
>>>                                                         Sort Key:
>>>company_et.id
>>>                                                         ->  Seq Scan on
>>>company_et  (cost=0.00..25.91 rows=291 width=27)
>>>                           ->  Sort  (cost=274262.92..278499.78
>>>rows=1694743 width=19)
>>>                                 Sort Key: logs_et.invaddr
>>>                                 ->  Seq Scan on
>>>logs_et  (cost=0.00..55404.43 rows=1694743 width=19)
>>>------------------------------------------------------------------------------------
>>>
>>>The computer is a Pentium III 850 Mhz with 256 mb RAM (Sort memory for
>>>postres is 16 mb, and 64 mb of shared memory).
>>>
>>
>>
>>
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>>
>>
>->  Seq Scan on
>company_et  (cost=0.00..25.91 rows=291 width=27)
>                           ->  Sort  (cost=274262.92..278499.78
>rows=1694743 width=19)
>                                 Sort Key: logs_et.invaddr
>
>
>Do you have any indexes defined for logs_et.invaddr and for 
>pro_invoice_addr_at.id ?
>
>Luis Sousa


pro_invoice_add_at.id had not index but was a primary key. I've created an 
index on it.  Here is the explain analyse for the query :

Sort  (cost=895649.54..896073.23 rows=169474 width=145) (actual 
time=553423.57..553423.76 rows=259 loops=1)  Sort Key: count(logs_et.dt)  ->  Aggregate  (cost=831240.24..865135.10
rows=169474width=145) (actual 
 
time=463611.22..553421.28 rows=259 loops=1)        ->  Group  (cost=831240.24..860898.24 rows=1694743 width=145) 
(actual time=463610.39..550481.54 rows=1698665 loops=1)              ->  Sort  (cost=831240.24..835477.10 rows=1694743
width=145)
 
(actual time=463610.36..468962.97 rows=1698665 loops=1)                    Sort Key: profiles_et.username,
profiles_et.name,
 
profiles_et.firstname, profiles_et.email, company_et.name, 
pro_invoice_addr_at.id                    ->  Merge Join  (cost=274406.73..304066.75 
rows=1694743 width=145) (actual time=76531.90..97594.64 rows=1698665 loops=1)                          Merge Cond:
("outer".id= "inner".invaddr)                          ->  Sort  (cost=143.81..144.92 rows=446 
 
width=126) (actual time=147.27..147.67 rows=446 loops=1)                                Sort Key:
pro_invoice_addr_at.id                               ->  Merge Join  (cost=90.27..124.18 
 
rows=446 width=126) (actual time=105.69..143.63 rows=446 loops=1)                                      Merge Cond:
("outer".id= 
 
"inner".profile)                                      ->  Index Scan using profiles_pk on 
profiles_et  (cost=0.00..24.98 rows=449 width=66) (actual time=50.53..79.70 
rows=449 loops=1)                                      ->  Sort  (cost=90.27..91.39 
rows=446 width=60) (actual time=55.13..55.54 rows=446 loops=1)                                            Sort Key: 
pro_invoice_addr_at.profile                                            ->  Merge 
Join  (cost=37.82..70.65 rows=446 width=60) (actual time=40.11..49.69 
rows=446 loops=1)                                                  Merge Cond: 
("outer".company = "inner".id)                                                  ->  Index Scan using 
invaddr_at_company_idx on pro_invoice_addr_at  (cost=0.00..24.68 rows=446 
width=33) (actual time=9.91..13.54 rows=446 loops=1)                                                  ->  Sort 
(cost=37.82..38.55 rows=291 width=27) (actual time=30.11..30.49 rows=447 
loops=1)                                                        Sort Key: 
company_et.id                                                        ->  Seq Scan on 
company_et  (cost=0.00..25.91 rows=291 width=27) (actual time=7.24..27.73 
rows=291 loops=1)                          ->  Sort  (cost=274262.92..278499.78 
rows=1694743 width=19) (actual time=76384.57..80077.80 rows=1698665 loops=1)                                Sort Key:
logs_et.invaddr                               ->  Seq Scan on 
 
logs_et  (cost=0.00..55404.43 rows=1694743 width=19) (actual 
time=11.47..13274.68 rows=1698665 loops=1)
Total runtime: 553673.02 msec

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