Hi,
On 01/29/2016 04:17 PM, Albe Laurenz wrote:
I have a query that runs *slower* if I increase work_mem.
The execution plans are identical in both cases, except that a temp file
is used when work_mem is smaller.
The relevant lines of EXPLAIN ANALYZE output are:
With work_mem='100MB':
-> Hash Join (cost=46738.74..285400.61 rows=292 width=8) (actual time=4296.986..106087.683 rows=187222 loops=1)
Hash Cond: ("*SELECT* 1_2".postadresse_id = p.postadresse_id)
Buffers: shared hit=1181177 dirtied=1, temp read=7232 written=7230
With work_mem='500MB':
-> Hash Join (cost=46738.74..285400.61 rows=292 width=8) (actual time=3802.849..245970.049 rows=187222 loops=1)
Hash Cond: ("*SELECT* 1_2".postadresse_id = p.postadresse_id)
Buffers: shared hit=1181175 dirtied=111
I ran operf on both backends, and they look quite similar, except that the
number of samples is different (this is "opreport -c" output):
CPU: Intel Sandy Bridge microarchitecture, speed 2899.8 MHz (estimated)
Counted CPU_CLK_UNHALTED events (Clock cycles when not halted) with a unit mask of 0x00 (No unit mask) count 90000
samples % image name symbol name
-------------------------------------------------------------------------------
112 0.0019 postgres ExecProcNode
3020116 49.9904 postgres ExecScanHashBucket
3021162 50.0077 postgres ExecHashJoin
3020116 92.8440 postgres ExecScanHashBucket
3020116 49.9207 postgres ExecScanHashBucket [self]
3020116 49.9207 postgres ExecScanHashBucket
8190 0.1354 vmlinux apic_timer_interrupt
What could be an explanation for this?
Is this known behaviour?
There is a bunch of possible causes for such behavior, but it's quite
impossible to say if this is an example of one of them as you have not
posted the interesting parts of the explain plan. Also, knowing
PostgreSQL version would be useful.
I don't think the example you posted is due to exceeding on-CPU cache as
that's just a few MBs per socket, so the smaller work_mem is
significantly larger.
What I'd expect to be the issue here is under-estimate of the hash table
size, resulting in too few buckets and thus long chains of tuples that
need to be searched sequentially. Smaller work_mem values usually limit
the length of those chains in favor of batching.
Please, post the whole explain plan - especially the info about number
of buckets/batches and the Hash node details.
regards
--
Tomas Vondra http://www.2ndQuadrant.com
PostgreSQL Development, 24x7 Support, Remote DBA, Training & Services
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