3

Background:

I have a live Django app that utilizes 4 Redis instances alongwith PostgreSQL 9.6.5.

Note that the first two Redis instances are big in size: back ups amount to ~2GB and ~4.4GB respectively.


The problem:

PG data and Redis backups are both saved in the secondary drive xvdb.

I've noticed that whenever my big Redis instances start backing up, disk I/O naturally spikes and PostgreSQL commit statements start piling up in the slow log. Behold:

21:49:26.171 UTC [44861] ubuntu@myapp LOG:  duration: 3063.262 ms  statement: COMMIT
21:49:26.171 UTC [44890] ubuntu@myapp LOG:  duration: 748.307 ms  statement: COMMIT
21:49:26.171 UTC [44882] ubuntu@myapp LOG:  duration: 1497.461 ms  statement: COMMIT
21:49:26.171 UTC [44893] ubuntu@myapp LOG:  duration: 655.063 ms  statement: COMMIT
21:49:26.171 UTC [44894] ubuntu@myapp LOG:  duration: 559.743 ms  statement: COMMIT
21:49:26.172 UTC [44883] ubuntu@myapp LOG:  duration: 1415.733 ms  statement: COMMIT

As a consequence, this is how my PostgreSQL commits look like every day:

enter image description here


The question:

Is there anything I can do on the PostgreSQL side to help smoothe out this spikey situation?

I'd like Redis and PostgreSQL to live in as much harmony as they possibly can on a single machine. If you feel this situation can only be helped from the Redis side, write that as an answer and I'll accept that too.


More information:

Ask for more information if you need it.

Machine specs:

AWS EC2 m4.4xlarge (16 cores, 64GB RAM)
Elastic Block Store gp2 volumes (105 IOPS, burst upto 3000 IOPS)

redis-server --version yields Redis server v=4.0.2 sha=00000000:0 malloc=jemalloc-4.0.3 bits=64 build=401ce53d7b0383ca.

Typical iostat -xmt 3 values are:

10/15/2017 08:28:35 PM
avg-cpu:  %user   %nice %system %iowait  %steal   %idle
          10.44    0.00    0.93    0.15    0.06   88.43

Device:         rrqm/s   wrqm/s     r/s     w/s    rMB/s    wMB/s avgrq-sz avgqu-sz   await r_await w_await  svctm  %util
xvda              0.00     0.00    0.00    2.00     0.00     0.04    38.67     0.00    0.00    0.00    0.00   0.00   0.00
xvdb              0.00     2.67    0.00   44.67     0.00     0.41    18.99     0.13    2.81    0.00    2.81   1.07   4.80

Compare that to the same around the time slow commits are logged:

10/15/2017 10:18:11 PM

avg-cpu:  %user   %nice %system %iowait  %steal   %idle
           8.16    0.00    0.65   11.90    0.04   79.24

Device:         rrqm/s   wrqm/s     r/s     w/s    rMB/s    wMB/s avgrq-sz avgqu-sz   await r_await w_await  svctm  %util
xvda              0.00     4.00    0.00    1.00     0.00     0.02    48.00     0.00    1.33    0.00    1.33   1.33   0.13
xvdb              0.00     0.00    1.67 1312.00     0.01   163.50   254.90   142.56  107.64   25.60  107.75   0.76 100.00

If needed, here are some relevant lines from postgresql.conf:

shared_buffers = 2GB  
checkpoint_timeout = 30min              # range 30s-1d
max_wal_size = 2GB
min_wal_size = 700MB
checkpoint_completion_target = 0.9      # checkpoint target duration, 0.0 - 1.0
#checkpoint_flush_after = 256kB         # measured in pages, 0 disables
#checkpoint_warning = 30s               # 0 disables

Note: I've asked a similar question - but focused on Redis - separately on SO as well.

9
  • If the delayed commits are a problem, I'd definitely move either Redis or Postgres onto its own host. It's much easier to manage them separately than trying to recocile them. Commented Oct 22, 2017 at 14:16
  • What's on xvda? Also, what filesystem is being used?
    – jjanes
    Commented Oct 23, 2017 at 1:09
  • @jjanes: xvda houses the OS, webserver and logs etc. The filesystem is ext4. Commented Oct 23, 2017 at 2:30
  • Could you try moving pg_xlog to xvda, if it is big enough?
    – jjanes
    Commented Oct 23, 2017 at 15:33
  • @jjanes: Yea I suppose I'll do that, or rather how about the redis instances? My postgresql DB is larger than my redis instances, and xvda is smaller than xvdb (35GB vs 175 GB) Commented Oct 24, 2017 at 20:12

0

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy.