We had a problem in the 8.X series with COPY IN - it did not respect any configured maximums and just kept allocating memory until it could fit the entire COPY contents down to the \. into RAM. Could there be a similar issue with COPY OUT?
----- Dan On Wed, Jun 11, 2014 at 6:02 PM, Timothy Garnett <tgarn...@panjiva.com> wrote: > Hi, > > 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). > The final csv file is large (~75GB, 86 million rows). The query is also > large, consisting of one table (86 million rows) left joined to a total of > 30 other tables (of mixed size), 3 of which are CTE supplied by a WITH > clause of and consist of 3 joins each for a total of 39 joins in the plan. > work_mem on the system is set to 256MB. > > 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. The > query plan from explain comes to 186 rows, which assuming that each row > requires the full work_mem (which should be a significant overestimate of > the number operations and size) is < 50GB and we're observing substantially > more then that. Is it reasonable to expect that a query will take ~ < > work_mem * # of operations, or are there other factors in play? > > The plan looks reasonable (though there are some odd right join uses, see > below) and the row estimates look pretty accurate with the exception that > one of the CTE queries is under-estimated row count wise by a little over 2 > orders of magnitude (260k vs. 86 million rows). That query does a group by > (plans as a sort then group aggregate, there are no hash aggregates in the > plan which is something that might increase memory) and the group part > miss-estimates the final number of rows for that CTE. Unlike the other CTEs > when it's merged joined into the main query there's no materialize line in > the plan (no idea if that's relevant). > > 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. > > Tim >
