Re: [HACKERS] Partition-wise aggregation/grouping

From: Rafia Sabih <rafia(dot)sabih(at)enterprisedb(dot)com>
To: Jeevan Chalke <jeevan(dot)chalke(at)enterprisedb(dot)com>
Cc: Robert Haas <robertmhaas(at)gmail(dot)com>, Ashutosh Bapat <ashutosh(dot)bapat(at)enterprisedb(dot)com>, Dilip Kumar <dilipbalaut(at)gmail(dot)com>, David Rowley <david(dot)rowley(at)2ndquadrant(dot)com>, Rajkumar Raghuwanshi <rajkumar(dot)raghuwanshi(at)enterprisedb(dot)com>, PostgreSQL Hackers <pgsql-hackers(at)postgresql(dot)org>
Subject: Re: [HACKERS] Partition-wise aggregation/grouping
Date: 2018-02-27 06:32:24
Message-ID: CAOGQiiPysxtT6spykX7UewDg11amFeFG_H+6MGVpJq=oV+oUPw@mail.gmail.com
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On Wed, Feb 14, 2018 at 8:35 PM, Jeevan Chalke <
jeevan(dot)chalke(at)enterprisedb(dot)com> wrote:

>
>
> On Wed, Feb 14, 2018 at 12:17 PM, Rafia Sabih <
> rafia(dot)sabih(at)enterprisedb(dot)com> wrote:
>
>> On Tue, Feb 13, 2018 at 6:21 PM, Jeevan Chalke <
>> jeevan(dot)chalke(at)enterprisedb(dot)com> wrote:
>>
>>>
>>> I see that partition-wise aggregate plan too uses parallel index, am I
>>> missing something?
>>>
>>>
>> You're right, I missed that, oops.
>>
>>>
>>>> Q18 takes some 390 secs with patch and some 147 secs without it.
>>>>
>>>
>>> This looks strange. This patch set does not touch parallel or seq scan
>>> as such. I am not sure why this is happening. All these three queries
>>> explain plan shows much higher execution time for parallel/seq scan.
>>>
>>> Yeah strange it is.
>>
>
> Off-list I have asked Rafia to provide me the perf machine access where
> she is doing this bench-marking to see what's going wrong.
> Thanks Rafia for the details.
>
> What I have observed that, there are two sources, one with HEAD and other
> with HEAD+PWA. However the configuration switches were different. Sources
> with HEAD+PWA has CFLAGS="-ggdb3 -O0" CXXFLAGS="-ggdb3 -O0" flags in
> addition with other sources. i.e. HEAD+PWA is configured with
> debugging/optimization enabled which account for the slowness.
>
> I have run EXPLAIN for these three queries on both the sources having
> exactly same configuration switches and I don't find any slowness with PWA
> patch-set.
>
> Thus, it will be good if you re-run the benchmark by keeping configuration
> switches same on both the sources and share the results.
>
> Thanks
>
> Interesting. I checked with keeping configure flags same for both the
repos,
on head:
CONFIGURE = '--enable-cassert' 'CFLAGS=-ggdb3 -O0' 'CXXFLAGS=-ggdb3 -O0'
'prefix=/data/rafia.sabih/pg_head/install/'
On head+PWA:
CONFIGURE = '--enable-cassert' 'CFLAGS=-ggdb3 -O0' 'CXXFLAGS=-ggdb3 -O0'
'prefix=/data/rafia.sabih/pg_part_pa/install/'

The queries I previously reported are now performing same as on head with
the above mentioned configuration. However, I further experimented with
partitionwise_join set to true, and found following cases of regression,
Q17 was taking some 1400 secs on head but with PWA it's taking some 1600
secs, looks like append of scan+aggregates is coming to be costlier than
that of just scan.
Q20 took 470 secs on head and with PWA it's taking 630 secs, the execution
plan is changed a lot, one thing in particular with the patch is not using
parallel bitmap heap scan on lineitem table.

The experimental settings were kept same as before with the change of
partitionwise_join = 1.

Please find the attached zip for the explain analyse outputs.

>
>
>> However, do you see similar behaviour with patches applied,
>>> "enable_partition_wise_agg = on" and "enable_partition_wise_agg = off" ?
>>>
>>
>> I tried that for query 18, with patch and enable_partition_wise_agg =
>> off, query completes in some 270 secs. You may find the explain analyse
>> output for it in the attached file. I noticed that on head the query plan
>> had parallel hash join however with patch and no partition-wise agg it is
>> using nested loop joins. This might be the issue.
>>
>>>
>>> Also, does rest of the queries perform better with partition-wise
>>> aggregates?
>>>
>>>
>> As far as this setting goes, there wasn't any other query using
>> partition-wise-agg, so, no.
>>
>> BTW, just an FYI, this experiment is on scale factor 20.
>>
>> --
>> Regards,
>> Rafia Sabih
>> EnterpriseDB: http://www.enterprisedb.com/
>>
>
>
> --
> Jeevan Chalke
> Technical Architect, Product Development
> EnterpriseDB Corporation
> The Enterprise PostgreSQL Company
>
>

--
Regards,
Rafia Sabih
EnterpriseDB: http://www.enterprisedb.com/

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