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PostgreSQL High Performance Cookbook

You're reading from  PostgreSQL High Performance Cookbook

Product type Book
Published in Mar 2017
Publisher Packt
ISBN-13 9781785284335
Pages 360 pages
Edition 1st Edition
Languages
Authors (2):
Chitij Chauhan Chitij Chauhan
Profile icon Chitij Chauhan
Dinesh Kumar Dinesh Kumar
Profile icon Dinesh Kumar
View More author details
Toc

Table of Contents (19) Chapters close

PostgreSQL High Performance Cookbook
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
1. Database Benchmarking 2. Server Configuration and Control 3. Device Optimization 4. Monitoring Server Performance 5. Connection Pooling and Database Partitioning 6. High Availability and Replication 7. Working with Third-Party Replication Management Utilities 8. Database Monitoring and Performance 9. Vacuum Internals 10. Data Migration from Other Databases to PostgreSQL and Upgrading the PostgreSQL Cluster 11. Query Optimization 12. Database Indexing

Checking IOPS


In this recipe, we will be discussing how to benchmark the disk IOPS using open source tools.

Getting ready

As mentioned previously, a disk can be read in either sequential or random orders. To measure the disk accurately, we need to perform more random read/write operations, which gives more stress to the disk. To calculate the IOPS (Input/Output Per Second) of a disk, we can either use fio or bonnie++ tools, which do sequential/random operations over the disk. In this chapter, let's use the fio (Flexible I/O) tool to calculate the IOPS for the disk.

How to do it...

Let's download the latest version of the fio module from http://brick.kernel.dk/snaps/, also download libaio-devel, which would be the ioengine we will be using for the IOPS. This ioengine defines, how the fio module needs to submit the I/O requests to the kernel. There are multiple ioengines you can specify for the I/O requests such as sync, mmap, and so on. You can refer to the main page of fio for all the supported ioengines. After downloading the fio module, let's follow the regular Linux source installation method as configure, make, and make install.

Sequential mixed read and write

Let's run a sample sequential mixed read/write, as shown here:

$ ./fio --ioengine=libaio --direct=1 --name=test_seq_mix_rw --filename=test_seq --bs=8k --iodepth=32 --size=1G --readwrite=rw --rwmixread=50
test_seq_mix_rw: (g=0): rw=rw, bs=8K-8K/8K-8K/8K-8K, ioengine=libaio, iodepth=32
...
...
test_seq_mix_rw: (groupid=0, jobs=1): err= 0: pid=43596: Fri Dec 30 23:31:11 2016
  read : io=525088KB, bw=1948.1KB/s, iops=243 , runt=269430msec
...
    bw (KB/s)  : min=   15, max= 6183, per=100.00%, avg=2002.59, stdev=1253.68
  write: io=523488KB, bw=1942.1KB/s, iops=242 , runt=269430msec
...
    bw (KB/s)  : min=  192, max= 5888, per=100.00%, avg=2001.74, stdev=1246.19
...
Run status group 0 (all jobs):
   READ: io=525088KB, aggrb=1948KB/s, minb=1948KB/s, maxb=1948KB/s, mint=269430msec, maxt=269430msec
  WRITE: io=523488KB, aggrb=1942KB/s, minb=1942KB/s, maxb=1942KB/s, mint=269430msec, maxt=269430msec
Disk stats (read/write):
  sda: ios=65608/65423, merge=0/5, ticks=869519/853644, in_queue=1723445, util=99.85%

Random mixed read and write

Let's run a sample random mixed read/write, as shown here:

$ ./fio --ioengine=libaio --direct=1 --name=test_rand_mix_rw --filename=test_rand --bs=8k --iodepth=32 --size=1G --readwrite=randrw --rwmixread=50
test_rand_mix_rw: (g=0): rw=randrw, bs=8K-8K/8K-8K/8K-8K, ioengine=libaio, iodepth=32
...
...
test_rand_mix_rw: (groupid=0, jobs=1): err= 0: pid=43893: Fri Dec 30 23:49:19 2016
  read : io=525088KB, bw=1018.9KB/s, iops=127 , runt=515375msec
...
    bw (KB/s)  : min=    8, max= 6720, per=100.00%, avg=1124.47, stdev=964.38
  write: io=523488KB, bw=1015.8KB/s, iops=126 , runt=515375msec
...
    bw (KB/s)  : min=    8, max= 6904, per=100.00%, avg=1125.46, stdev=975.04
...
Run status group 0 (all jobs):
   READ: io=525088KB, aggrb=1018KB/s, minb=1018KB/s, maxb=1018KB/s, mint=515375msec, maxt=515375msec
  WRITE: io=523488KB, aggrb=1015KB/s, minb=1015KB/s, maxb=1015KB/s, mint=515375msec, maxt=515375msec
Disk stats (read/write):
  sda: ios=65609/65456, merge=0/4, ticks=7382037/5520238, in_queue=12902772, util=100.00%

How it works...

We ran the preceding test cases to work on 1 GB (--size) file without any cache (--direct), by doing 32 concurrent I/O requests (--iodepth), with a block size of 8 KB (--bs) as 50% read and 50% write operations (--rwmixread). From the preceding sequential test results, the bw (bandwidth), IOPS values are pretty high when compared with random test results. That is, in sequential test cases, we gain approximately 50% more IOPS (read=243, read=242) than with the random IOPS (read=127, write=126).

Fio also provides more information such, as I/O submission latency and complete latency, along with CPU usage on the conducted test cases. I would encourage you to read more useful information about fio's features from its man pages.

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PostgreSQL High Performance Cookbook
Published in: Mar 2017 Publisher: Packt ISBN-13: 9781785284335
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