Along these lines, some of the key advances and features available in MySQL 5.5 and InnoDB are:
- Faster Index Creation - MySQL 5.5 can now add or drop indexes without copying the underlying data of the entire
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Lately I’ve had to do some environment load testing so I wrote this quick script. It can be modified as needed but the basic idea is that it spawns $x threads (–threads) and then sends two connections (or however many you want with –per-connection=) per thread to the URL (–url=). You can have it wait a configurable time between connections as well (–wait=).
The url is appended with a 32 character randomized string so that any database/caching on the backend of the site isn’t serving data from a warm cache. You can hunt down the string length for 32 and change it to whatever you want. Feel free to change and use as needed, just keep my info at top.
#!/usr/bin/python ################################################################################ ## DATE: 2010-10-26 ## AUTHOR: Matt Reid ## MAIL: firstname.lastname@example.org ## SITE:[Read more...]
There’s a new version of the dbbenchmark tool available. Now we’re creating the MySQL connection pool thread count based on automatic reporting of core quantity. There is still the same method to set the thread count manually if you are interested in finding your system’s thread limits. Download the MySQL benchmarking script now and add your server performance to the community database of results!
If you’ve ever needed to know how the data and index percentages per table engine were laid out on your MySQL server, but didn’t have the time to write out a query… here it is!
select (select (sum(DATA_LENGTH)+sum(INDEX_LENGTH))/(POW(1024,3)) as total_size from tables) as total_size_gb, (select sum(INDEX_LENGTH)/(POW(1024,3)) as index_size from tables) as total_index_gb, (select sum(DATA_LENGTH)/(POW(1024,3)) as data_size from tables) as total_data_gb, (select ((sum(INDEX_LENGTH) / ( sum(DATA_LENGTH) + sum(INDEX_LENGTH)))*100) as perc_index from tables) as perc_index, (select ((sum(DATA_LENGTH) / ( sum(DATA_LENGTH) + sum(INDEX_LENGTH)))*100) as perc_data from tables) as perc_data, (select ((sum(INDEX_LENGTH) / ( sum(DATA_LENGTH) + sum(INDEX_LENGTH)))*100) as perc_index from tables where ENGINE='innodb') as innodb_perc_index, (select ((sum(DATA_LENGTH) / ([Read more...]
The MySQL Community is a world of command-line aficionados. Many people, including myself, show their love to the simple-but-powerful interface of the mysql command-line client, but not everybody is keen to use a bash shell and give up its GUI, no matter how powerful the software is.
Until recently, GUI tools for MySQL were half baked solutions: in the end, there was always something that you had to do via the command line. Today, you can install, set up and use MySQL on your Mac with Snow Leopard without using Terminal, at all.
Before digging into the details of the installation, let me describe what I need on my Mac. I use various versions of MySQL and I often need to run 2 or more[Read more...]
Clients often ask what the differences are between the various InnoDB isolation levels, or what ACID means. Here are some simple explanations for those that have not yet read the manual and committed it to memory.
Every select operates without locks so you don’t get consistency and might have dirt reads, which are potentially earlier versions of data. So, no ACID support here.
Has consistent reads without locks. Each consistent read, even within the same transaction, sets and reads its own fresh snapshot.
The InnoDB default isolation level for ACID compliance. All reads within the same transaction will be consistent between each other – ie, the C in ACID. All writes will be durable, etc etc.
In this latest release I’ve added a basic MySQL connection pool to the benchmarking script which improves the method in which connections to MySQL are handled and reused. In addition, there have been some optimizations made to the thread handler functions for better debug reporting. Download the latest release now and see how your MySQL server performs against the rest of the community! Download here: download page.
Here are some quick commands for installing the proper packages and requirements for the MySQL dbbenchmark program.
export PKG_PATH="ftp://openbsd.mirrors.tds.net/pub/OpenBSD/4.7/packages/amd64/" pkg_add -i -v wget wget http://dbbenchmark.googlecode.com/files/dbbenchmark-version-0.1.beta_rev26.tar.gz pkg_add -i -v python Ambiguous: choose package for python a 0: 1: python-2.4.6p2 2: python-2.5.4p3 3: python-2.6.3p1 Your choice: 2 pkg_add -i -v py-mysql pkg_add -i -v mysql pkg_add -i -v mysql-server ln -s /usr/local/bin/python2.5 /usr/bin/python gzip -d dbbenchmark-version-0.1.beta_rev26.tar.gz tar -xvf dbbenchmark-version-0.1.beta_rev26.tar cd dbbenchmark-version-0.1.beta_rev26 ./dbbenchmark.py --print-sql - login to mysql and execute sql commands ./dbbenchmark.py
As previously mentioned, Darren Cassar has been working on a new automated installer for the DBbenchmark program. It’s now available for download: click here. All you need to do is save it to the directory that you want to install to and then make sure it’s executable: “chmod 700 installer.sh”, then run it “./installer.sh”.
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.
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.
Quick solution to an issue that the affected Debian Lenny release: the process used to collect the MEMORY_ACTIVE_BYTES variable has been modified to correct a situation where some systems report an array of memory information instead of the expected single integer value. The bug has been fixed in revision 21 and the current download (revision 22) is available for download or svn update. As usual, you can download the MySQL dbbenchmark script here: [downloads].
Thanks goes to Brian Vowell at Evernote.com for bringing this bug to my attention. The original bug report can be found here: [link]
There are many times when writing an application that single threaded database operations are simply too slow. In these cases it’s a matter of course that you’ll use multi-threading or forking to spawn secondary processes to handle the database actions. In this simple example for Python multi-threading you’ll see the how simple it is to improve the performance of your python app.
#!/usr/bin/python ## DATE: 2010-08-30 ## AUTHOR: Matt Reid ## WEBSITE: http://themattreid.com ## LICENSE: BSD http://www.opensource.org/licenses/bsd-license.php ## Copyright 2010-present Matt Reid from __future__ import division from socket import gethostname; import threading import sys import os import MySQLdb class threader(threading.Thread): def __init__(self,method): threading.Thread.__init__(self) self.tx = self.method = method def run(self):[Read more...]
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.
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.
If you need to work with LVM in your scripts but haven’t found a good method to access details about Logical Volume Groups, here’s a simple Python script that will print the details about any volumes on your system. This could be useful for writing a partition check script for your MySQL data directory (if you’re not using a standard monitoring system like Nagios).
import sys import os import commands import subprocess import select def lvm(): print "" LVM_PATH = "/sbin" LVM_BIN = os.path.join(LVM_PATH, 'lvm') argv = list() argv.append(LVM_BIN) argv.append("lvs") argv.append("--nosuffix") argv.append("--noheadings") argv.append("--units") argv.append("b") argv.append("--separator") argv.append(";") argv.append("-o") argv.append("lv_name,vg_name,lv_size") process = subprocess.Popen(argv,[Read more...]
Here’s a simple answer to a simple question. “How do I run a backup of MySQL to another machine without writing to the local server’s filesystem?” – this is especially useful if you are running out of space on the local server and cannot write a temporary file to the filesystem during backups.
Method one – this writes a remote file.
mysqldump [options] [db_name|--all-databases]| gzip -c | ssh email@example.com "cat > /path/to/new/file.sql.gz"
Method two – this writes directly into a remote mysql server
mysqldump [options] [db_name|--all-databases]| mysql --host=[remote host] –user=root –password=[pass] [db_name]
If you’re using the new Arthemia theme for WordPress you might notice that there are two areas of the theme that can have articles promoted to; namely Headline and Featured sections. This is controlled by category association. Basically you have a post and if you want it in the Headline area of the theme you attach the category “headline” to it, similarly for the featured section. Now, let’s say you don’t want to manually change this all the time since it can be time consuming to promote posts to those categories if you want rotating content.
Here’s a simple solution. In this bash script I connect to MySQL and remove the current associations from posts and then randomly choose posts to be promoted to the Headline and Featured categories. This can be[Read more...]
A couple of question I get a lot from MySQL customers is “how will this hardware upgrade improve my transactions per second (TPS)” and “what level of TPS will MySQL perform on this hardware if I’m running ACID settings?” Running sysbench against MySQL with different values for per-thread and global memory buffer sizes, ACID settings, and other settings gives me concrete values to bring to the customer to show the impact that more RAM, faster CPUs, faster disks, or cnf changes have on the server. Here are some examples for a common question: “If I’m using full ACID settings vs non-ACID settings what performance am I going to get from this server?”
Let’s find out by running sysbench with the following settings (most are self explanatory – if not the man page can explain them):
For all of those linux users out there that have moved over to, or tried out, Solaris10 or OpenSolaris because they heard the tales of how MySQL is faster on Solaris… or perhaps you wanted to learn how to use Sol10 for the great features of Zones or the ZFS filesystem? Regardless of why you’re on it you are probably wondering why Linux has colored output of filenames and directories but Solaris does not. The question of ‘why?’ isn’t important, but how to enable colors is. It’s very simple, and here’s how I fixed it. This is a result of digging through multiple semi-related links on Google.
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