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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