Re: speeding up planning with partitions

From: Amit Langote <Langote_Amit_f8(at)lab(dot)ntt(dot)co(dot)jp>
To: David Rowley <david(dot)rowley(at)2ndquadrant(dot)com>, "Imai, Yoshikazu" <imai(dot)yoshikazu(at)jp(dot)fujitsu(dot)com>
Cc: "Tsunakawa, Takayuki" <tsunakawa(dot)takay(at)jp(dot)fujitsu(dot)com>, Alvaro Herrera <alvherre(at)2ndquadrant(dot)com>, Pg Hackers <pgsql-hackers(at)postgresql(dot)org>
Subject: Re: speeding up planning with partitions
Date: 2019-01-23 01:21:00
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On 2019/01/22 18:47, David Rowley wrote:
> On Tue, 22 Jan 2019 at 20:01, Imai, Yoshikazu
>> What I understand so far is about 10,000 while loops at total (4098+4098+some extra) is needed in hash_seq_search() in EXECUTE query after the creation of the generic plan.
>> 10,000 while loops takes about 10 microsec (of course, we can't estimate correct time), and the difference of the latency between 5th and 7th EXECUTE is about 8 microsec, I currently think this causes the difference.
> >
>> I don't know this problem relates to Amit-san's patch, but I'll continue to investigate it.
> I had another thought... when you're making a custom plan you're only
> grabbing locks on partitions that were not pruned (just 1 partition in
> your case), but when making the generic plan, locks will be acquired
> on all partitions (all 4000 of them). This likely means that when
> building the generic plan for the first time that the
> LockMethodLocalHash table is expanded to fit all those locks, and
> since we never shrink those down again, it'll remain that size for the
> rest of your run. I imagine the reason for the slowdown is that
> during LockReleaseAll(), a sequential scan is performed over the
> entire hash table. I see from looking at the hash_seq_search() code
> that the value of max_bucket is pretty critical to how it'll perform.
> The while ((curElem = segp[segment_ndx]) == NULL) loop will need to
> run fewer times with a lower max_bucket.

I too think that that might be behind that slight drop in performance.
So, it's good to know what one of the performance bottlenecks is when
dealing with large number of relations in queries.


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