From: | Valerie Schneider DSI/DEV <Valerie(dot)Schneider(at)meteo(dot)fr> |
---|---|
To: | chriskl(at)familyhealth(dot)com(dot)au |
Cc: | pgsql-performance(at)postgresql(dot)org |
Subject: | Re: [GENERAL] Tuning queries on large database |
Date: | 2004-08-05 08:16:59 |
Message-ID: | 200408050816.i758GxO21560@mu.meteo.fr |
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Thread: | |
Lists: | pgsql-performance |
Hi,
I 've decreased the sort_mem to 5000 instead of 50000.
I recreated ma table using integer and real types instead of
numeric : the result is very improved for the disk space :
schema | relfilenode | table | index | reltuples | size
--------+-------------+------------------+------------+-------------+----------
public | 253442696 | data | | 1.25113e+08 | 29760016
public | 378639579 | data | i_data_dat | 1.25113e+08 | 2744400
public | 378555698 | data | pk_data | 1.25113e+08 | 3295584
so it takes about 28 Gb instead of 68 Gb !
For my different queries, it's better but less performant than oracle :
oracle PG yesterday(numeric) PG today(integer/real)
Q1 <1s <1s <1s
Q2 3s 8s 4s
Q3 8s 1m20s 27s
Q4 28s 17m20s 6m47s
Result of EXPLAIN ANALYZE :
Q1 :bench=> explain analyze select 'Q1',min(td),max(u) from data where
num_poste=1000 and dat between
(date_trunc('month',to_timestamp('31012004','ddmmyyyy')-interval '2000
days'))::timestamp and
(date_trunc('month',to_timestamp('31012004','ddmmyyyy')-interval '2000 days') +
interval '1 month' - interval '1 hour')::timestamp;
QUERY PLAN
--------------------------------------------------------------------------------
Aggregate (cost=2466.47..2466.47 rows=1 width=8) (actual time=261.777..261.778
rows=1 loops=1)
-> Index Scan using pk_data on data (cost=0.00..2463.41 rows=611 width=8)
(actual time=20.106..259.924 rows=744 loops=1)
Index Cond: ((num_poste = 1000) AND (dat >= (date_trunc('month'::text,
(to_timestamp('31012004'::text, 'ddmmyyyy'::text) - '2000
days'::interval)))::timestamp without time zone) AND (dat <=
(((date_trunc('month'::text, (to_timestamp('31012004'::text, 'ddmmyyyy'::text) -
'2000 days'::interval)) + '1 mon'::interval) - '01:00:00'::interval))::timestamp
without time zone))
Total runtime: 262.145 ms
(4 rows)
Q2 : bench=> explain analyze select 'Q2',count(*) from data where num_poste
between 100 and 100+10 and dat between
(date_trunc('month',to_timestamp('31012004','ddmmyyyy')-interval '3000
days'))::timestamp and
(date_trunc('month',to_timestamp('31012004','ddmmyyyy')-interval '3000 days') +
interval '1 month' - interval '1 hour')::timestamp;
QUERY PLAN
--------------------------------------------------------------------------------
Aggregate (cost=24777.68..24777.68 rows=1 width=0) (actual
time=4253.977..4253.978 rows=1 loops=1)
-> Index Scan using pk_data on data (cost=0.00..24762.34 rows=6138 width=0)
(actual time=46.602..4244.984 rows=7920 loops=1)
Index Cond: ((num_poste >= 100) AND (num_poste <= 110) AND (dat >=
(date_trunc('month'::text, (to_timestamp('31012004'::text, 'ddmmyyyy'::text) -
'3000 days'::interval)))::timestamp without time zone) AND (dat <=
(((date_trunc('month'::text, (to_timestamp('31012004'::text, 'ddmmyyyy'::text) -
'3000 days'::interval)) + '1 mon'::interval) - '01:00:00'::interval))::timestamp
without time zone))
Total runtime: 4254.233 ms
(4 rows)
Q3 : bench=> explain analyze select 'Q3',sum(rr1),count(ff) from data where
num_poste in (50,50+2);
QUERY PLAN
--------------------------------------------------------------------------------
Aggregate (cost=963455.87..963455.87 rows=1 width=8) (actual
time=27668.666..27668.667 rows=1 loops=1)
-> Index Scan using pk_data, pk_data on data (cost=0.00..962236.31
rows=243910 width=8) (actual time=16.251..27275.468 rows=250226 loops=1)
Index Cond: ((num_poste = 50) OR (num_poste = 52))
Total runtime: 27673.837 ms
(4 rows)
Q4 : bench=> explain analyze select 'Q4',count(*) from data where num_poste
between 600 and 625;
QUERY PLAN
--------------------------------------------------------------------------------
Aggregate (cost=14086174.57..14086174.57 rows=1 width=0) (actual
time=428235.024..428235.025 rows=1 loops=1)
-> Index Scan using pk_data on data (cost=0.00..14076910.99 rows=3705431
width=0) (actual time=45.283..424634.826 rows=3252938 loops=1)
Index Cond: ((num_poste >= 600) AND (num_poste <= 625))
Total runtime: 428235.224 ms
(4 rows)
Thanks for all, Valerie.
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>Date: Wed, 4 Aug 2004 21:21:51 +0800 (WST)
>From: Christopher Kings-Lynne <chriskl(at)familyhealth(dot)com(dot)au>
>To: Valerie Schneider DSI/DEV <Valerie(dot)Schneider(at)meteo(dot)fr>
>Cc: pgsql-performance(at)postgresql(dot)org, <pgsql-general(at)postgresql(dot)org>
>Subject: Re: [GENERAL] [PERFORM] Tuning queries on large database
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>
>> sort_mem = 50000
>
>That is way, way too large. Try more like 5000 or lower.
>
>> num_poste | numeric(9,0) | not null
>
>For starters numerics are really, really slow compared to integers. Why
>aren't you using an integer for this field since youhave '0' decimal
>places.
>
>> schema | relfilenode | table | index | reltuples | size
>>
--------+-------------+------------------+------------+-------------+----------
>> public | 125615917 | data | | 1.25113e+08 |
72312040
>> public | 251139049 | data | i_data_dat | 1.25113e+08 |
2744400
>> public | 250870177 | data | pk_data | 1.25113e+08 |
4395480
>>
>> My first remark is that the table takes a lot of place on disk, about
>> 70 Gb, instead of 35 Gb with oracle.
>
>Integers will take a lot less space than numerics.
>
>> The different queries of the bench are "simple" queries (no join,
>> sub-query, ...) and are using indexes (I "explained" each one to
>> be sure) :
>> Q1 select_court : access to about 700 rows : 1 "num_poste" and 1 month
>> (using PK : num_poste=p1 and dat between p2 and p3)
>> Q2 select_moy : access to about 7000 rows : 10 "num_poste" and 1 month
>> (using PK : num_poste between p1 and p1+10 and dat between p2 and p3)
>> Q3 select_long : about 250 000 rows : 2 "num_poste"
>> (using PK : num_poste in (p1,p1+2))
>> Q4 select_tres_long : about 3 millions rows : 25 "num_poste"
>> (using PK : num_poste between p1 and p1 + 25)
>>
>> The result is that for "short queries" (Q1 and Q2) it runs in a few
>> seconds on both Oracle and PG. The difference becomes important with
>> Q3 : 8 seconds with oracle
>> 80 sec with PG
>> and too much with Q4 : 28s with oracle
>> 17m20s with PG !
>>
>> Of course when I run 100 or 1000 parallel queries such as Q3 or Q4,
>> it becomes a disaster !
>
>Please reply with the EXPLAIN ANALYZE output of these queries so we can
>have some idea of how to help you.
>
>Chris
>
>
>
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