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Postgres backend using huge amounts of ram

From: Gary Doades <gpd(at)gpdnet(dot)co(dot)uk>
To: pgsql-performance(at)postgresql(dot)org
Subject: Postgres backend using huge amounts of ram
Date: 2004-11-25 20:35:25
Message-ID: (view raw, whole thread or download thread mbox)
Lists: pgsql-performance
How much RAM can a single postgres backend use?

I've just loaded a moderately sized dataset into postgres and was
applying RI constraints to the tables (using pgadmin on windows). Part
way though I noticed the (single) postgres backend had shot up to using
300+ MB of my RAM!

The two tables are:

create table reqt_dates
	reqt_date_id	serial,
	reqt_id     	integer not null,
	reqt_date	date not null,
	primary key (reqt_date_id)
) without oids;


create table booking_plan
	booking_plan_id		serial,
	reqt_date_id		integer not null,
	booking_id     		integer not null,
	booking_date		date not null,
	datetime_from		timestamp not null,
	datetime_to		timestamp not null,
	primary key (booking_plan_id)
) without oids;

and I was was trying to do:

alter table booking_plan add
	 foreign key
	) references reqt_dates (
	) on delete cascade;

Since I can't get an explain of what the alter table was doing I used this:

select count(*) from booking_plan,reqt_dates where
booking_plan.reqt_date_id = reqt_dates.reqt_date_id

and sure enough this query caused the backend to use 300M RAM. The plan
for this was:

Aggregate  (cost=37.00..37.00 rows=1 width=0) (actual
time=123968.000..123968.000 rows=1 loops=1)
   ->  Hash Join  (cost=15.50..36.50 rows=1000 width=0) (actual
time=10205.000..120683.000 rows=1657709 loops=1)
         Hash Cond: ("outer".reqt_date_id = "inner".reqt_date_id)
         ->  Seq Scan on booking_plan  (cost=0.00..15.00 rows=1000
width=4) (actual time=10.000..4264.000 rows=1657709 loops=1)
         ->  Hash  (cost=15.00..15.00 rows=1000 width=4) (actual
time=10195.000..10195.000 rows=0 loops=1)
               ->  Seq Scan on reqt_dates  (cost=0.00..15.00 rows=1000
width=4) (actual time=0.000..6607.000 rows=2142184 loops=1)
Total runtime: 124068.000 ms

I then analysed the database. Note, there are no indexes at this stage
except the primary keys.

the same query then gave:
Aggregate  (cost=107213.17..107213.17 rows=1 width=0) (actual
time=57002.000..57002.000 rows=1 loops=1)
   ->  Hash Join  (cost=35887.01..106384.32 rows=1657709 width=0)
(actual time=9774.000..54046.000 rows=1657709 loops=1)
         Hash Cond: ("outer".reqt_date_id = "inner".reqt_date_id)
         ->  Seq Scan on booking_plan  (cost=0.00..22103.55 rows=1657709
width=4) (actual time=10.000..19648.000 rows=1657709 loops=1)
         ->  Hash  (cost=24355.92..24355.92 rows=2142184 width=4)
(actual time=9674.000..9674.000 rows=0 loops=1)
               ->  Seq Scan on reqt_dates  (cost=0.00..24355.92
rows=2142184 width=4) (actual time=0.000..4699.000 rows=2142184 loops=1)
Total runtime: 57002.000 ms

This is the same set of hash joins, BUT the backend only used 30M of
private RAM.

Platform is Windows XP, Postgres 8.0 beta 5

shared_buffers = 4000
work_mem = 8192

Any explanations?



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