Re: Performance weirdness with/without vacuum analyze

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От Harry Broomhall
Тема Re: Performance weirdness with/without vacuum analyze
Дата
Msg-id 200310211140.MAA15046@haeb.noc.uk.easynet.net
обсуждение исходный текст
Ответ на Re: Performance weirdness with/without vacuum analyze  (Josh Berkus <josh@agliodbs.com>)
Ответы Re: Performance weirdness with/without vacuum analyze  (Shridhar Daithankar <shridhar_daithankar@myrealbox.com>)
Re: Performance weirdness with/without vacuum analyze  (Tom Lane <tgl@sss.pgh.pa.us>)
Список pgsql-performance
Josh Berkus writes:
> Harry,


   Many thanks for your response,

>
> >    It has been suggested to me that I resubmit this question to this list,
> > rather than the GENERAL list it was originaly sent to.
> >
> >    I asked earlier about ways of doing an UPDATE involving a left outer
> > join and got some very useful feedback.
>
> The query you posted will always be somewhat slow due to the forced join
> order, which is unavodable with a left outer join.

  Yes - I rather suspected that!  It is a shame it takes two joins to do
the work.

>
> However, regarding your peculiar behaviour, please post:
>
> 1) Your random_page_cost and effective_cache_size settings

#effective_cache_size = 1000    # typically 8KB each
#random_page_cost = 4       # units are one sequential page fetch cost

  i.e. - still set to their defaults.

> 2) The EXPLAIN ANALYZE of each query instead of just the EXPLAIN

  First the case with no vacuum analyze:

                                                                      QUERY PLAN

-------------------------------------------------------------------------------------------------------------------------------------------------------
 Merge Join  (cost=99.32..171.32 rows=1000 width=259) (actual time=18579.92..48277.69 rows=335671 loops=1)
   Merge Cond: ("outer".cdr_id = "inner".cdr_id)
   ->  Index Scan using import_cdrs_cdr_id_key on import_cdrs  (cost=0.00..52.00 rows=1000 width=164) (actual
time=0.42..11479.51rows=335671 loops=1) 
   ->  Sort  (cost=99.32..101.82 rows=1000 width=95) (actual time=18578.71..21155.65 rows=335671 loops=1)
         Sort Key: un.cdr_id
         ->  Hash Join  (cost=6.99..49.49 rows=1000 width=95) (actual time=4.70..10011.35 rows=335671 loops=1)
               Hash Cond: ("outer".interim_cli = "inner".interim_num)
               Join Filter: (("outer".starttime >= "inner".starttime) AND ("outer".starttime <= "inner".endtime))
               ->  Seq Scan on import_cdrs un  (cost=0.00..20.00 rows=1000 width=49) (actual time=0.02..4265.63
rows=335671loops=1) 
               ->  Hash  (cost=6.39..6.39 rows=239 width=46) (actual time=4.57..4.57 rows=0 loops=1)
                     ->  Seq Scan on num_xlate  (cost=0.00..6.39 rows=239 width=46) (actual time=0.12..2.77 rows=239
loops=1)
 Total runtime: 80408.42 msec
(12 rows)

  And now the case *with* the vacuum analyze:

                                                               QUERY PLAN

-----------------------------------------------------------------------------------------------------------------------------------------
 Hash Join  (cost=15335.91..49619.57 rows=335671 width=202) (actual time=12383.44..49297.58 rows=335671 loops=1)
   Hash Cond: ("outer".cdr_id = "inner".cdr_id)
   ->  Seq Scan on import_cdrs  (cost=0.00..8496.71 rows=335671 width=126) (actual time=0.15..9504.24 rows=335671
loops=1)
   ->  Hash  (cost=10398.73..10398.73 rows=335671 width=76) (actual time=12371.13..12371.13 rows=0 loops=1)
         ->  Hash Join  (cost=6.99..10398.73 rows=335671 width=76) (actual time=4.91..9412.55 rows=335671 loops=1)
               Hash Cond: ("outer".interim_cli = "inner".interim_num)
               Join Filter: (("outer".starttime >= "inner".starttime) AND ("outer".starttime <= "inner".endtime))
               ->  Seq Scan on import_cdrs un  (cost=0.00..8496.71 rows=335671 width=30) (actual time=0.09..3813.54
rows=335671loops=1) 
               ->  Hash  (cost=6.39..6.39 rows=239 width=46) (actual time=4.71..4.71 rows=0 loops=1)
                     ->  Seq Scan on num_xlate  (cost=0.00..6.39 rows=239 width=46) (actual time=0.22..2.90 rows=239
loops=1)
 Total runtime: 432543.73 msec
(11 rows)

   Please note that since I first posted I have been slightly adjusting the
schema of the tables, but the disparity remains.

   Many thanks for your assistance.

   Regards,
       Harry.


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