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Displaying posts with tag: Benchmarking (reset)

dbbenchmark.com – vote on next supported OS now!
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So far the benchmarking script supports Linux, FreeBSD, and OSX. I’m installing virtual machines today to get ready for development on the next OS that the community wants to have supported. Vote today for your choice. Development will begin Friday 2010-09-03.

Note: There is a poll embedded within this post, please visit the site to participate in this post's poll.
dbbenchmark.com – MySQL benchmarking now with FreeBSD support
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The development cycle is moving right along for the community’s newest MySQL benchmarking script. I’m pleased to announce that we now officially support FreeBSD (version 8.1 tested) so go ahead and download now and test your FreeBSD, Linux, or OSX MySQL server! Click here for the download.

Courtesy of Darren Cassar and some generous coding this weekend, we’re going to be releasing a auto-installer / updater for the application which you can use to automate that part of the process. Stay tuned for information on that release.

dbbenchmark.com – MySQL benchmarking now supports multiple threads!
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We had a very successful weekend of Planet.mysql users submitting their database statistics so I’ve pushed some code into a new release today so that everyone can benefit from some new features. The biggest change is to the threading logic. Previously the benchmarking script was serializing MySQL operations and only making use of a secondary thread (not the invoking thread) to query the database. Now you have the option of running with “–threads=x” to make use of your multi-core server. A good example of this improvement was on my Macbook Pro; before the threading change it was inserting ~700/sec, after the code change I tried –threads=4 and saw an improvement to ~900/sec. Rather significant.

Download the new script now and see how your server compares to the ones in the central database!

dbbenchmark.com – now supporting MySQL on OSX 10.6
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Just a quick note to let everyone know that our new benchmarking script now supports OSX 10.6 on Intel hardware. That means you can run one simple command and get all of the sequential and random INSERT and SELECT performance statistics about your database performance. As usual the script is open source and released under the new BSD license. Give is a try by downloading now! See the download page for more details.

dbbenchmark.com – Benchmarking script now available
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You can download the first release of the benchmarking script here: http://code.google.com/p/dbbenchmark/

Please read the README file or consult the Support page before running the benchmarks.

SSD Market Continues to Heat Up
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I had originally posted this on the 16th of September, but I had been changing hosting providers and such and it has managed to drop through the cracks.  So, if you didn’t see it before here it is..

I have long held the opinon that SSD (Solid State Disk) drives are going to be a major part of the database future. I just checked and I wrote a blog posting about them two years ago. I am not alone in this opinion.  It has long been realized that both I/O access speed and throughput increases have not kept pace with the increases in CPU power and the steadily decreasing cost of RAM. Storage space has increased, but both access speed and throughput performance have only had marginal increases in performance.

Solid state disks have long held the promise of lowered access speeds, especially when it comes to random access.  Even so, prices for SSD drives

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MySQL related bookmark collection
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I am publishing my MySQL related bookmark collection http://www.mysqlpreacher.com/bookmarks/.

Feel free to send me links you think might be good to add in order to help others.

Remember, SHARING IS CARING!!! …. we get so much for free, why shouldn’t we give some back?

Cheers,
Darren

Seeking public data for benchmarks
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I have several side projects when time permits and one is that of benchmarking various MySQL technologies (e.g. MySQL 5.0,5.1,5.4), variants (e.g. MariaDB, Drizzle) and storage engines (e.g. Tokutek, Innodb plugin) and even other products like Tokyo Cabinet which is gaining large implementations.

You have two options with benchmarks, the brute force approach such as Sysbench, TPC, sysbench, Juice Benchmark, iibench, mysqlslap, skyload. I prefer the realistic approach however these are always on client’s private data. What is first needed is better access to public data for benchmarks. I have compiled this list to date and I am seeking additional sources for reference.

  • Feebase – Data is in clean loadable format
  • IMDB – Not
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Importing times in MySQL
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One of the ways to import data into MySQL is using the LOAD DATA INFILE. It is a faster method than recovering from a dump, as it’s raw data instead of SQL sentences.

The import time depends on the table engine, for example, MyISAM can be 40 times faster than Innodb. Let’s benchmark this:

Preparation

I’m gonna make some benchmarking using MySQL 5.1.36 (64 bits MacOS X). I’ll need a big table, so I’ll take City from the World Database and create a huge table called “city_huge”:

CREATE TABLE city_huge LIKE CITY;

INSERT INTO city_huge 
    SELECT NULL, name, CountryCode, District, Population FROM city;
# Run this sentence 100 times,
# so city_huge table will be 100 times bigger than city.
# Tip: use a script, temporary table,
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Understanding your RAID Configuration
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For any production MySQL Database system, running RAID is a given these days. Do you know what RAID your database is? Are you sure?. Ask for quantifiable reproducible output from your systems provider or your System Administrator.

As a consultant I don’t always know the specific tools for the clients deployed H/W, but I ask the question. On more the one occasion the actual result differed from the clients’ perspective or what they were told, and twice I’ve discovered that clients when asked if their RAID was running in a degraded mode, it actually was and they didn’t know.

You can read about various benchmarks at MySQL blogs such as BigDBAHead and MySQL Performance Blog however

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Leveraging the power of Twitter
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Last week I posted the following twitter request“Can somebody loan me (or buy me) a Dell 2950 decked out so I can run and publish some benchmarks. Please!”

In a same day response I was offered access to use 2 x Dell 1950’s, and today I’m now actually using these machines for my own testing. I would like to thank cafemom (Barry, Anthony & Dan) for the loan of hardware.

And now the chance to better understand the RAID configuration of the DELL PERC Controllers, trying out some different RAID types, LVM configurations and disk tests. When I’m done with my System Administrator refresher, I’m then be trying some different MySQL Benchmarks to test various MySQL configuration settings including using the new

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Updated mysql-proxy benchmarking script (for proxy 0.7)
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My previous post contained a lua script for MySQL proxy that would generate benchmarking information. However, just days (or maybe hours?) after I published it, release 0.7 of mysql-proxy was published, making my script obsolete. I’ve fixed this (it needed just a minor tweak), so here‘s a tarball with the following: trace.lua, which is the […] Related posts:
  • Using MySQL Proxy to benchmark query performance By transparently sitting between client and server on each request,...
  • New release of MySQL Proxy GPL MySQL Proxy has a new release, just three days ago,...
  • Using
  •   [Read more...]
    Using MySQL Proxy to benchmark query performance
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    By transparently sitting between client and server on each request, MySQL Proxy offers many possibilities for query manipulation.

    Many are explored in the cookbook, and they even include a histogram recipe. Still, I wanted to learn more about the proxy while working on a script that would let me get some stats on the queries executed against a server (or group of servers).

    First things first, get a brief glimpse of the lua programming language since that’s what the proxy’s scripts are written in. Alternatively, you can jump straight into the sample scripts, extrapolate what you don’t

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    online add node - preliminary numbers (2)
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    Scenario: Grow from two data nodes to four using ONLINE ADD NODE and REORGANIZE PARTITION of a 2GB table, and UPDATE traffic

    Setup for each data node:
    * Dual cpu - quad core running at 2.33GHz.
    * 8GB of RAM
    * DataMemory=4096MB
    * MaxNoOfExecutionThreads=8
    * Configuration generated by Configurator
    * Bound execution threads to cores (LockExec/Maint....Thread..)
    * Completely distributed setup.

    Created the following table and filled it with 2M rows which gives a table (different of last time to simplify further tests) of 2GB in size:

    CREATE TABLE `t1` (
    `a` bigint(20) unsigned NOT NULL AUTO_INCREMENT,
    `b` int(10) unsigned DEFAULT NULL,
    `c` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP,
    `d` varbinary(768) DEFAULT NULL,
    `e`

















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    online add node - preliminary numbers
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    I want to measure the time it takes to do various ONLINE ADD NODE operations in MySQL Cluster 7.0 and especially how long time it takes to repartition the data onto the newly added nodes. So here comes the first post on the subject.

    First off: Go from two data nodes to four using ONLINE ADD NODE and REORGANIZE PARTITION of 2GB tables, and no traffic system.

    Setup for each data node:
    • Dual cpu - quad core running at 2.33GHz.
    • 8GB of RAM
    • DataMemory=4096MB
    • MaxNoOfExecutionThreads=8
    • Configuration generated by Configurator
    • Bound execution threads to cores (LockExec/Maint....Thread..)
    • Completely distributed setup.






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    bencher - a benchmarking utility for MySQL Cluster
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    bencher is a test program that allows you to benchmark requests on MySQL Cluster. I have used this utility a lot of customers, because it lets me:
    • specify a simple query that I want to benchmark on the command line
    • implement more complex use cases.
    • implement NDBAPI requests
    and I don't have to reinvent the wheel every time. It is all there: connectivity, multi-threading support, timers, and some basic statistics, and it compiles on most platforms. I just have to focus on the queries I want to optimize or benchmark.

    The simple use case is to specify the SQL query you want to benchmark, the number of threads, and how many times. You can also customize this very easily to benchmark more elaborate SQL requsts, and NDBAPI requests.




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    Scale out when it makes sense
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    Not to rehash an old argument, but I am watching a recent  video on performance work being done by Sun hosted by Allan Packer (a recorded MySQL University session) and one of his bullet points was “Scale out when it makes sense, rather than just because there is no alternative”. That is what they are working on in his group at Sun.

    You mean I will be able to buy 8 and 16 cores boxes and be able to use all the cores?

    Hallelujah and Amen brother

    Allan, thanks to you and all other who are working on this both inside and outside Sun.

    Slap’em
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    Giving a bunch of mysql instances something you do everyday and you might think ….. how should I do it? Write a bunch of selects and inserts manually? nahh that takes s**tload of time, should I run binlogs collected from a live system on my test server? nahh thats not practical nor is it real since it doesn’t contain selects, should I gather the general query log and try that out? nahhh  …..

    MySQL has been kind enough to supply us with their mysql_slap which does the job for us and given I needed to do a proof of concept on monitoring a group of 4 circular replicated servers I wrote a small script which does the job of slapping them with a varying level of concurrancy, iterations, number of queries and connections for as long as you like.

    Here it is and I hope some of you might find it useful for slapping their own test servers :).

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