Re: Contention preventing locking

From: Konstantin Knizhnik <k(dot)knizhnik(at)postgrespro(dot)ru>
To: Michail Nikolaev <michail(dot)nikolaev(at)gmail(dot)com>
Cc: PostgreSQL Hackers <pgsql-hackers(at)postgresql(dot)org>
Subject: Re: Contention preventing locking
Date: 2018-02-19 14:10:52
Message-ID: cf0fc37d-2ddd-5c1e-a03e-7020610097dc@postgrespro.ru
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On 16.02.2018 11:59, Michail Nikolaev wrote:
> Hello.
>
> Just want to notice - this work also correlates with
> https://www.postgresql.org/message-id/CAEepm%3D18buPTwNWKZMrAXLqja1Tvezw6sgFJKPQ%2BsFFTuwM0bQ%40mail.gmail.com paper.
> It provides more general way to address the issue comparing to single
> optimisations (but they could do the work too, of course).
>

Certainly, contention-aware lock scheduler is much more general way of
addressing this problem.
But amount of efforts needed to implement such scheduler and integrate
it in Postgres core is almost non-comparable.

I did some more tests with much simple benchmark than YCSB: it just
execute specified percent of single record updates and selects for
relatively small table.
I used 50% of updates, 100 records table size and vary number of
connections from 10 to 1000 with step 10.
This benchmark (pgrw.c) and updated version of xlock patch are attached
to this mail.

Results are present at the following spreadsheet:

https://docs.google.com/spreadsheets/d/1QOYfUehy8U3sdasMjGnPGQJY8JiRfZmlS64YRBM0YTo/edit?usp=sharing

I repeated tests several times. Dips on the chart corresponds to the
auto-vacuum periods. For some reasons them are larger for xlock
optimization.
But, you can notice that xlock optimization significantly reduce
degradation speed although doesn't completely eliminate this negative
trend.

> Thanks,
> Michail.
>
>
> чт, 15 февр. 2018 г. в 19:00, Konstantin Knizhnik
> <k(dot)knizhnik(at)postgrespro(dot)ru <mailto:k(dot)knizhnik(at)postgrespro(dot)ru>>:
>
> Hi,
>
> PostgreSQL performance degrades signficantly in case of high
> contention.
> You can look at the attached YCSB results (ycsb-zipf-pool.png) to
> estimate the level of this degradation.
>
> Postgres is acquiring two kind of heavy weight locks during update: it
> locks TID of the updated tuple and XID of transaction created this
> version.
> In debugger I see the following picture: if several transactions are
> trying to update the same record, then first of all they compete for
> SnapshotDirty.xmax transaction lock in EvalPlanQualFetch.
> Then in heap_tuple_update they are trying to lock TID of the updated
> tuple: heap_acquire_tuplock in heapam.c
> After that transactions wait completion of the transaction updated the
> tuple: XactLockTableWait in heapam.c
>
> So in heap_acquire_tuplock all competing transactions are waiting for
> TID of the updated version. When transaction which changed this
> tuple is
> committed, one of the competitors will grant this lock and proceed,
> creating new version of the tuple. Then all other competitors will be
> awaken and ... find out that locked tuple is not the last version
> any more.
> Then they will locate new version and try to lock it... The more
> competitors we have, then more attempts they all have to perform
> (quadratic complexity).
>
> My idea was that we can avoid such performance degradation if we
> somehow
> queue competing transactions so that they will get control one-by-one,
> without doing useless work.
> First of all I tried to replace TID  lock with PK (primary key) lock.
> Unlike TID, PK of record  is not changed during hot update. The second
> idea is that instead immediate releasing lock after update we can hold
> it until the end of transaction. And this optimization really provides
> improve of performance - it corresponds to pg_f1_opt configuration at
> the attached diagram.
> For some workloads it provides up to two times improvement comparing
> with vanilla Postgres. But there are many problems with correct
> (non-prototype) implementation of this approach:
> handling different types of PK, including compound keys, PK
> updates,...
>
> Another approach,  which I have recently implemented, is much simpler
> and address another lock kind: transaction lock.
> The idea o this approach is mostly the same: all competing transaction
> are waiting for transaction which is changing the tuple.
> Then one of them is given a chance to proceed and now all other
> transactions are waiting for this transaction and so on:
>
> T1<-T2,T3,T4,T5,T6,T7,T8,T9
> T2<-T3,T4,T5,T6,T7,T8,T9
> T3<-T4,T5,T6,T7,T8,T9
> ...
>
> <- here corresponds to "wait for" dependency between transactions.
>
> If we change this picture to
>
> T1<-T2, T2<-T3, T3<-T4, T4<-T5, T5<-T6, T6<-T7, T7<-T8, T8<-T9
>
> then number of lock requests can be significantly reduced.
> And it can be implemented using very simple patch (attached
> xlock.patch).
> I hope that I have not done something incorrect here.
> Effect of this simple patch is even larger:  more than 3 times for
> 50..70 clients.
> Please look at the attached xlock.pdf spreadsheet.
>
> Unfortunately combination of this two approaches gives worser result
> than just single xlock.patch.
> Certainly this patch also requires further improvement, for example it
> will not correctly work in case of aborting transactions due to
> deadlock
> or some other reasons.
> I just want to know option of community if the proposed approaches to
> reduce contention are really promising and it makes sense to continue
> work in this direction.
>
> --
> Konstantin Knizhnik
> Postgres Professional: http://www.postgrespro.com
> The Russian Postgres Company
>

--
Konstantin Knizhnik
Postgres Professional: http://www.postgrespro.com
The Russian Postgres Company

Attachment Content-Type Size
xlock.patch text/x-patch 4.1 KB
pgrw.c text/x-csrc 4.9 KB

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