Re: Query memory usage greatly in excess of work_mem * query plan steps

Timothy Garnett <tgarnett(at)panjiva(dot)com> writes:
> I have a query that's pulling data for another system using COPY (query) to
> STDOUT CSV on a 9.2.4 db (we're in the process of upgrading to 9.3).
> ...
> We're running into problems with the machine running out of memory with
> this single query process consuming over 100GB resident memory before the
> machine exhausts swap and the Linux OOM handling eventually kills it.

I wonder if you're hitting some sort of memory leak. What I'd suggest
doing to help diagnose that is to show us a memory map. Do this:

(1) Set a ulimit so that the process will get ENOMEM sometime before
the OOM killer awakens (this is good practice anyway, if you've not
disabled OOM kills). On Linux systems, ulimit -m or -v generally
does the trick. The easiest way to enforce this is to add a ulimit
command to the script that launches the postmaster, then restart.

(2) Make sure your logging setup will collect anything printed to
stderr by a backend. If you use logging_collector you're good to go;
if you use syslog you need to check where the postmaster's stderr
was redirected, making sure it's not /dev/null.

(3) Run the failing query. Collect the memory map it dumps to stderr
when it fails, and send it in. What you're looking for is a couple
hundred lines looking like this:

TopMemoryContext: 69984 total in 10 blocks; 6152 free (16 chunks); 63832 used
MessageContext: 8192 total in 1 blocks; 7112 free (1 chunks); 1080 used
Operator class cache: 8192 total in 1 blocks; 1640 free (0 chunks); 6552 used
smgr relation table: 24576 total in 2 blocks; 13872 free (3 chunks); 10704 used
... lots more in the same vein ...

> As to the right join (used for a few of the joins, most are left join or
> merge):
> -> Hash Right Join (cost=225541299.19..237399743.38
> rows=86681834 width=1108)
> Hash Cond: (xxx.xxx = yyy.yyy)
> -> Seq Scan on xxx (cost=0.00..6188.18
> rows=9941 width=20)
> Filter: (mode = 'live'::text)
> -> Hash (cost=212606744.27..212606744.27
> rows=86681834 width=1096)
> ....
> I'm not sure if I'm reading it right, but it looks like it's hashing the 86
> million row set and scanning over the 10k row set which seems to me like
> the opposite of what you'd want to do, but I haven't seen a lot of hash
> right joins in plans and I'm not sure if that's how it works.

That looks pretty odd to me too, though I guess the planner might think it
was sensible if xxx's join column had very low cardinality. Still, it's
weird. What have you got work_mem set to exactly?

regards, tom lane