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Displaying posts with tag: sysbench (reset)
SAN vs Local-disk :: innodb_flush_method performance benchmarks

If you’ve been tuning your MySQL database and have wondered what effect the innodb_flush_method settings have on write performance, then this information might help. I’ve recently been doing a lot of baseline load tests to show performance differences between localdisk and the new SAN we’re deploying. Since we run InnoDB for everything in production, and writes are very heavy, I decided to run comparison tests between two identical servers to find the best setting for innodb_flush_method. We have the following specs for the hardware:

  • Dell R610
  • 24 core Intel Xeon X5670 @ 2.93ghz
  • 72GB ECC RAM
  • Brocade 825 HBA
  • Local disk: RAID-10 15K SAS Ext3 (ugh)
  • SAN: Oracle 7420 with four Intel Xeon X7550 @ 2.00GHz, 512GB RAM, 2TB read-cache(MLC-SSD), 36GB write cache (SLC-SSD), 3 disk shelves populated with 60x2TB 7200RM SATA drives setup in mirrored format with striped …
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Re-doing Galera disk bound benchmark

I've been promising I should re-visit once more the disk bound sysbench tests I ran on Galera. In December I finally had some lab time to do that. If you remember what troubled me then it was that in all my other Galera benchmarks performance with Galera was equal or much better compared to performance on a single MySQL node. (And this is very unusual wrt high availability solutions, usually they come with a performance penalty. This is why Galera is so great.) However, on the tests with a disk bound workload, there was performance degradation, and what was even more troubling was the performance seemed to decrease more when adding more write masters.

In these tests I was able to understand the performance decrease and it had nothing to do with Galera and not even …

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Slides for Choosing a MySQL High Availability solution

Here are the slides to my first talk at Percona Live UK 2011: Choosing a MySQL High Availability solution.1

  1. 1. See this for a review of the conference as a whole: http://openlife.cc/blogs/2011/october/thanks-percona-and-attendees-great-percona-live-uk-2011

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Galera disk bound workload revisited

Update 2012-01-09: I have now been able to understand the poor(ish) results in this benchmark. They are very likely due to a bad hardware setup and neither Galera nor InnoDB is to blame. See http://openlife.cc/blogs/2012/january/re-doing-galera-disk-bound-benchmark

People commenting on my results for benchmarking Galera on a disk bound workload seemed to be confused by the performance degrading when writing to more than one master, and not convinced at my speculations on the reasons. Since sysbench 0.5 has the benchmarks in the form of LUA scripts, it was temptingly easy to tweak those a little to see if my speculations were correct. So yesterday I did run tests again with a slightly modified sysbench workload. …

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One-liner for condensing sysbench output into a csv file

An important part of benchmarking is to draw graphs. A graph can reveal results you wouldn't have spotted just by looking at raw numbers. By the way, the process of massaging the raw numbers into graphs will often reveal things too.

Sysbench output tends to be quite wordy, especially when you have a script that runs 1, 2, 4, 8... threads with the same test. To manually copy paste the numbers into a spreadsheet is tiresome. So I came up with this monster shell one-liner to condense the output into a csv file. I'm posting it here so I will find it the next time I need it:

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Quadrant Framework – rev7 update adds DyGraphs support

Quick update to the framework that was released yesterday; I’ve added automatic graph generation. I chose DyGraphs due to the quick ability to enable support – the HTML is very quick and simply loads the CSV data. It has the same zooming features of Highcharts without the JS overhead.

Now when you run a load test you will get (in the output directory) a mixture of files: the main cumulative CSV and HTML file for the hostname that was tested, and then one CSV and HTML per report variable that was tested. This means you don’t have to drag the main CSV file into an alternate program or spend time parsing out certain variables one at a time to generate specific graphs.  I’ve also added support for limiting output of SNMP variables (LOAD,CPU,MEM). Head over here and download the update: http://code.google.com/p/quadrant-framework/

To enable …

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MySQL Load Testing Framework – initial release

It seems that everyone loves load testing these days. Problem is that everyone is using their own quick scripts, simple or complex, to drive their tests without the ability for other DBAs to duplicate those tests. Let’s say I write a great test and share my results and graphs on the blog – you want to run the same tests to see how your new DB servers compare in performance: this framework allows you to do that without duplicating any work or writing code. This is a basic release that will get the ball rolling. I’ve included some sample tests in the README file, so give them a try.

This codebase offers a user friendly framework for creating and visualizing MySQL database load test jobs. It is based around Sysbench, which is generally considered the industry standard load test application. The framework allows you to do the following:

  • standardize your tests without requiring you to write one-off bash scripts to handle …
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4 performance fixes to MySQL on large servers

Yesterday I posted results from some MySQL benchmarks I had been doing on a large server. In this post I'd like to list 4 important fixes that were done to avoid bad performance:

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DRBD and Semi-sync shootout on large server

DRBD and semi-sync benchmarks on a 2x8 132 GB server

I recently had the opportunity to run some benchmarks against a relatively large server, to learn how it was behaving in its specific configuration. I got some interesting results that I'll share here.

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Modeling InnoDB Scalability on Multi-Core Servers

Mat Keep’s blog post on InnoDB-vs-MyISAM benchmarks that Oracle recently published prompted me to do some mathematical modeling of InnoDB’s scalability as the number of cores in the server increases. Vadim runs lots of benchmarks that measure what happens under increasing concurrency while holding the hardware constant, but not as many with varying numbers of cores, so I decided to use Mat Keep’s data for this. The modeling I performed is Universal Scalability Law modeling, which can predict both software and hardware scalability, depending on how it is used.

In brief, the benchmarks are sysbench’s read-only and read-write tests, and the server has two Intel SSDs, 64GB of memory, and 4 x 12-core …

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Showing entries 31 to 40 of 63
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