Re: Optimize update query

Den 28/11/2012 kl. 17.54 skrev Shaun Thomas <sthomas(at)optionshouse(dot)com>:

> On 11/28/2012 10:19 AM, Niels Kristian Schjødt wrote:
>
>> https://rpm.newrelic.com/public/charts/h2dtedghfsv
>
> Doesn't this answer your question?
>
> That iowait is crushing your server into the ground. It's no surprise updates are taking several seconds. That update you sent us *should* execute on the order of only a few milliseconds.
>
> So I'll reiterate that you *must* move your pg_xlog location elsewhere. You've got row lookup bandwidth conflicting with writes. There are a couple other changes you should probably make to your config:
>
>> checkpoint_segments = 16
>
> This is not enough for the workload you describe. Every time the database checkpoints, all of those changes in pg_xlog are applied to the backend data files. You should set these values:
>
> checkpoint_segments = 100
> checkpoint_timeout = 10m
> checkpoint_completion_target = 0.9
>
> This will reduce your overall write workload, and make it less active. Too many checkpoints massively reduce write throughput. With the settings you have, it's probably checkpointing constantly while your load runs. Start with this, but experiment with increasing checkpoint_segments further.
>
> If you check your logs now, you probably see a ton of "checkpoint starting: xlog" in there. That's very bad. It should say "checkpoint starting: time" meaning it's keeping up with your writes naturally.
>
>> work_mem = 160MB
>
> This is probably way too high. work_mem is used every sort operation in a query. So each connection could have several of these allocated, thus starting your system of memory which will reduce that available for page cache. Change it to 8mb, and increase it in small increments if necessary.
>
>> So correct me if I'm wrong here: my theory is, that I have too many
>> too slow update queries, that then often end up in a situation, where
>> they "wait" for each other to finish, hence the sometimes VERY long
>> execution times.
>
> Sometimes this is the case, but for you, you're running into IO contention, not lock contention. Your 3TB RAID-1 is simply insufficient for this workload.
>
> If you check your logs after making the changes I've suggested, take a look at your checkpoint sync times. That will tell you how long it took the kernel to physically commit those blocks to disk and get a confirmation back from the controller. If those take longer than a second or two, you're probably running into controller buffer overflows. You have a large amount of RAM, so you should also make these two kernel changes to sysctl.conf:
>
> vm.dirty_ratio = 10
> vm.dirty_writeback_ratio = 1
>
> Then run this:
>
> sysctl -p
>
> This will help prevent large IO write spikes caused when the kernel decides to write out dirty memory. That can make checkpoints take minutes to commit in some cases, which basically stops all write traffic to your database entirely.
>
> That should get you going, anyway. You still need more/better disks so you can move your pg_xlog directory. With your write load, that will make a huge difference.
>
> --
> Shaun Thomas
> OptionsHouse | 141 W. Jackson Blvd. | Suite 500 | Chicago IL, 60604
> 312-444-8534
> sthomas(at)optionshouse(dot)com
>
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Okay, now I'm done the updating as described above. I did the postgres.conf changes. I did the kernel changes, i added two SSD's in a software RAID1 where the pg_xlog is now located - unfortunately the the picture is still the same :-(
When the database is under "heavy" load, there is almost no improvement to see in the performance compared to before the changes. A lot of both read and writes takes more than a 1000 times as long as they usually do, under "lighter" overall load.

I added All the overview charts I can get hold on from new relic beneath. What am I overlooking? There must be an obvious bottleneck? Where should I dive in?

Database server CPU usage
https://rpm.newrelic.com/public/charts/cEdIvvoQZCr

Database server load average
https://rpm.newrelic.com/public/charts/cMNdrYW51QJ

Database server physical memory
https://rpm.newrelic.com/public/charts/c3dZBntNpa1

Database server disk I/O utulization
https://rpm.newrelic.com/public/charts/9YEVw6RekFG

Database server network I/O (Mb/s)
https://rpm.newrelic.com/public/charts/lKiZ0Szmwe7

Top 5 database operations by wall clock time
https://rpm.newrelic.com/public/charts/dCt45YH12FK

Database throughput
https://rpm.newrelic.com/public/charts/bIbtQ1mDzMI

Database response time
https://rpm.newrelic.com/public/charts/fPcNL8WA6xx