pg.ddx.io  pgsql-performance@postgresql.org mailing list archive  
help / color / mirror / Atom feed
From: Justin Pryzby <pryzby@telsasoft.com>
To: Saurabh Nanda <saurabhnanda@gmail.com>
Cc: Jeff Janes <jeff.janes@gmail.com>
Cc: pgsql-performance@lists.postgresql.org
Subject: Re: Benchmarking: How to identify bottleneck (limiting factor) and achieve "linear scalability"?
Date: Sun, 27 Jan 2019 10:04:06 -0600
Message-ID: <20190127160406.GL13248@telsasoft.com> (raw)
In-Reply-To: <CAPz=2oE7HBJo59ANsYoEwyJU3AbjXU1opu_p3MuYZbcja_LCAg@mail.gmail.com>
References: <CAPz=2oGdmvirLNX5kys+uiY7LKzCP4sTiXXob39qq6eDkEuk2Q@mail.gmail.com>
	<CAMkU=1yNvhDow9QvKeG5nzv2fDG9VXJ3gi8JbX2h0t8_MY1hBA@mail.gmail.com>
	<CAPz=2oF8C-JAny9eM_gNkzQDj1CDjGfoQ17rcHm5-N-hOFAhUg@mail.gmail.com>
	<CAPz=2oE7HBJo59ANsYoEwyJU3AbjXU1opu_p3MuYZbcja_LCAg@mail.gmail.com>

On Sun, Jan 27, 2019 at 01:09:16PM +0530, Saurabh Nanda wrote:
> It seems that PGOPTIONS="-c synchronous_commit=off" has a significant
> impact. However, I still can not understand why the TPS for the optimised
> case is LOWER than the default for higher concurrency levels!

Do you know which of the settings is causing lower TPS ?

I suggest to check shared_buffers.

If you haven't done it, disabling THP and KSM can resolve performance issues,
esp. with large RAM like shared_buffers, at least with older kernels.
https://www.postgresql.org/message-id/20170718180152.GE17566%40telsasoft.com

Justin




view thread (22+ messages)  latest in thread

Message-ID: <20190127160406.GL13248@telsasoft.com>
Permalink:  ../20190127160406.GL13248@telsasoft.com/
Also on:    postgresql.org/message-id/20190127160406.GL13248@telsasoft.com

 · 

reply

Reply instructions:

You may reply publicly to this message via plain-text email
using any one of the following methods:

* Reply to all the recipients using the --to and --cc options:
  reply via email

  To: pgsql-performance@postgresql.org
  Cc: pryzby@telsasoft.com, saurabhnanda@gmail.com, jeff.janes@gmail.com, pgsql-performance@lists.postgresql.org
  Subject: Re: Benchmarking: How to identify bottleneck (limiting factor) and achieve "linear scalability"?
  In-Reply-To: <20190127160406.GL13248@telsasoft.com>

* Save the following mbox file, import it into your mail client,
  and reply-to-all from there: mbox

This inbox is served by DDX for PostgreSQL; see mirroring instructions
for how to clone and mirror all data and code used for this inbox