On 02/01/2016 10:38 AM, Albe Laurenz wrote:
Tomas Vondra wrote:
...
I didn't post the whole plan since it is awfully long, I'll include hyperlinks
for the whole plan.
work_mem = '100MB' (http://explain.depesz.com/s/7b6a):
-> 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
[...]
-> Hash (cost=18044.92..18044.92 rows=4014 width=8) (actual
time=4206.892..4206.892 rows=3096362 loops=1)
Buckets: 1024 Batches: 2 (originally 1) Memory Usage: 102401kB
Buffers: shared hit=1134522 dirtied=1, temp written=5296
work_mem = '500MB' (http://explain.depesz.com/s/Cgkl):
-> 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
[...]
-> Hash (cost=18044.92..18044.92 rows=4014 width=8) (actual
time=3709.584..3709.584 rows=3096360 loops=1)
Buckets: 1024 Batches: 1 Memory Usage: 120952kB
Buffers: shared hit=1134520 dirtied=111
Does that support your theory?
There is clearly an underestimate here, caused by correlated attributes, but
is that the cause for the bad performance with increased work_mem?
Yes, that's clearly the culprit here. In both cases we estimate here are
only ~4000 tuples in the hash, and 9.3 sizes the hash table to have at
most ~10 tuples per bucket (in a linked list).
However we actually get ~3M rows, so there will be ~3000 tuples per
bucket, and that's extremely expensive to walk. The reason why 100MB is
faster is that it's using 2 batches, thus making the lists "just" ~1500
tuples long.
This is pretty much exactly the reason why I reworked hash joins in 9.5.
I'd bet it's going to be ~20x faster on that version.
regards
--
Tomas Vondra http://www.2ndQuadrant.com
PostgreSQL Development, 24x7 Support, Remote DBA, Training & Services
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