Here are some common performance tuning concepts that I frequently run into. Please note that this really is only a basic introduction to performance tuning. For more in-depth tuning, it strongly depends on your systems, data and usage.

Server Variables

For tuning InnoDB performance, your primary variable is innodb_buffer_pool_size. This is the chunk of memory that InnoDB uses for caching data, indexes and various pieces of information about your database. The bigger, the better. If you can cache all of your data in memory, you’ll see significant performance improvements.

For MyISAM, there is a similar buffer defined by key_buffer_size, though this is only used for indexes, not data. Again, the bigger, the better.

Other variables that are worth investigating for performance tuning are:

query_cache_size - This can be very useful if you have a small number of read queries that are repeated frequently, …

Running MySQL slave is quite common and regular task which we do every day, taking backups from slave is often recommended solution. However the current state of MySQL replication makes restoring slave a bit tricky (if possible at all). The main problem is that InnoDB transaction state and replication state are not synchronized. If we speak about backup and you can execute SHOW SLAVE STATUS command you can get reliable information about current state, but some solutions does not allow that. Look for example Sun Storage 7410, which provides storage via NFS and where you can make ZFS snapshots without any info what kind of data you are storing there. What makes situation worse is that files with replication state (relay-log.info, master.info) are not synchronized on disk after each update, and even wrose - in case with NFS they are stored on client side OS/NFS cache for long time. As solution we can do patch to execute fsync() for these files after …

DTrace is a dynamic tracing facility built into the Solaris and Open Solaris operating systems and can be used by system administrators and developers alike to observe the runtime behavior of user level programs and of the operating system itself. On one hand, DTrace can be used to identify potential bottlenecks in the running processes on a production system and on the other DTrace can help you understand the runtime behavior of an external program such as MySQL better.

In times of tight budgets, quality is a key success factor to reduce risks in IT projects.

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The PrimeBase PBMS engine now supports user defined metadata.
When the PBMS engine receives a BLOB the HTTP header tag value pairs are stored with the BLOB as metadata. To restrict which headers are stored as metadata an updatable system table 'pbms_http_fields' is provided in which users can add the names of the headers that are to be treated as metadata. When the BLOB is retrieved from the engine the metadata is sent back along with the BLOB as HTTP headers in the same way that it was received.
The metadata can be accessed from within the database via the 'pbms_matadata' system table or altered by performing inserts, updates, or deletes on the table.
A BLOB alias is a special metadata field that allows you to associate a database wide unique name with the BLOB which can then be used later to retrieve it. If you are familiar with Amazon S3 storage it works in a similar manner where you can think of the database as the S3 bucket …

Yeah...title says it all.

Bug bug #11661, Raising Exceptions from within stored procedures: Support for SIGNAL statement.

I can't recall the exact moment of filing this bug, because I filed a lot of them. However, this one is special to me because I filed it when I was in the process of getting involved with MySQL and its community. I remember it as a very intense period of learning, meeting other community members online (mostly through forums.mysql.com and blogging on a regular basis.

A lot has happened since then, and if you ask me, most of it is good stuff. The only thing that casts somewhat of a shadow is that it took so long to fix this. But I don't want to whine about it. Rather, I'd like to use this opportunity and extend my big, BIG THANK YOU!! …

Yesterday, Monty and I were fussing around with lcov and genhtml trying to generate code coverage analysis for Drizzle. After a few hours, I was finally able to get some good output, and I've published the results temporarily on my website.

We're currently at 70.4% code coverage which is less-than-ideal, but at least we now have a baseline from which to improve. We're all about making incremental improvements, and having statistics to tell us whether we're going in the right direction is important. This is a good first step.

So, what exactly do these code coverage numbers mean?

OK, so for those readers not familiar with gcov or lcov, here is what these code coverage numbers actually mean... They represent the percentage of executable source lines which are executed during a run of Drizzle's test suite. Basically, the percent gives us a rough idea of the percent of …

Correctly managing your MySQL database objects such as schemas, tables, indexes, base data etc, is critical to the success of a 24×7 online website. I rarely encounter a robust working solution as part of my consulting so I would like to share my experience in identifying the best practices you should be adopting whether your an existing organization or just an individual with a simple website.

Much of the following concept actually pre dates my involvement in MySQL (since 1999), so this is not just applicable for a MySQL RDBMS. For the purposes of this discussion I’d like to focus on the theory successfully used with clients.

Under version control I have the following directory structure:

NOTE If your first observation was “Arrh, Version Control?”, you are in more trouble then you want to be right from day one. You need Version Control such as svn, cvs, bzr, git etc for any website no matter how small.

It is well known that MySQL can use a lot of temporary files and that, using a ramdisk (tmpfs on Linux) can improve performance drastically as Matt has shown here. The problem with tmpfs is its limited size. You need just one query creating a huge temporary file that happens once per day to screw up the tmpfs scenario. I have done some fuse programming in my previous job and I think it is possible to use fuse to mix a tmpfs filesystem with a regular filesystem, the regular filesystem being used only when the tmpfs is full. Fuse has a lower performance level than a regular filesystem but I think the possibility to use tmpfs the vast majority of the queries needing a temporary file will overcome the performance limitation of fuse.

That is the explanation for the MiniWheatFS name, the frosted side is the tmpfs and the healthy side is the regular filesystem. There are many fuse …

So since last talking about a new benchmark I found a need for one.  Specifically the need to truly test IO bound workloads in mysql to flex fast storage subsystems.  Tackling a new benchmark is not as easy as I thought.  I am already on version 2 of my code and its still really a mess.  But it appears solid enough to try and give it a few test runs on some really fast disk subsystems.  So Armed with several really bad queries I put together a read-only workload that just hammers the disk and little else…  I am working a little under the gun as I only have access to the TMS Ramsan for 1 more night, and only have access to a Violin memory test box for a short while longer as well.  The problem I am running into with these systems is DBT2 and sysbench bottleneck the CPU before they really flex the disk.  I want to flex the disk damn it!

So how’s it going?  reasonably well. I am not happy with …