Percona's MySQL & InnoDB performance and scalability blog
Queries in MySQL, Sphinx and many other database or search engines are typically single-threaded. That is when you issue a single query on your brand new r910 with 32 CPU cores and 16 disks, the maximum that is going to be used to process this query at any given point is 1 CPU core and [...]
I did a Webinar about MySQL Upgrade – Best Practices Yesterday and there were some questions we could not answer during Webinar, following Jay’s Lead I decided to post them as a Blog Post. Q: Can you go directly MySQL 5.0 to 5.5 for MyISAM tables? MyISAM have not been getting any significant development since [...]
One of the most painful troubleshooting tasks with MySQL is troubleshooting memory usage. The problem usually starts like this – you have configured MySQL to use reasonable global buffers, such as innodb_buffer_size, key_buffer_size etc, you have reasonable amount of connections but yet MySQL takes much more memory than you would expect, causing swapping or other [...]
Upgrades are usually one of the biggest part of any database infrastructure maintenance. Even with enough planning something else can go bad after sending your production application to the version you’ve upgraded to. Let’s look at how one Percona Toolkit tool, pt-upgrade can help you identify what to expect and test your upgrades better which [...]
Overview Profiling, analyzing and then fixing queries is likely the most oft-repeated part of a job of a DBA and one that keeps evolving, as new features are added to the application new queries pop up that need to be analyzed and fixed. And there are not too many tools out there that can make [...]
One of the serious limitations in the fast index creation feature introduced in the InnoDB plugin is that it only works when indexes are explicitly created using ALTER TABLE or CREATE INDEX. Peter has already blogged about it before, here I’ll just briefly reiterate other cases that might benefit from that feature: when ALTER TABLE [...]
Often times, from a computing perspective, one must run a function on a large amount of input. Often times, the same function must be run on many pieces of input, and this is a very expensive process unless the work can be done in parallel. Shard-Query introduces set based processing, which on the surface appears [...]
Can Shard-Query scale to 20 nodes? Peter asked this question in comments to to my previous Shard-Query benchmark. Actually he asked if it could scale to 50, but testing 20 was all I could due to to EC2 and time limits. I think the results at 20 nodes are very useful to understand the performance: [...]
I don’t use many tools in my consulting practice but for the ones I do, I try to know them as best as I can. I’ve been using mk-query-digest for almost as long as it exists but it continues to surprise me in ways I couldn’t imagine it would. This time I’d like to share [...]
Combating “data drift” In my first post in this series, I described materialized views (MVs). An MV is essentially a cached result set at one point in time. The contents of the MV will become incorrect (out of sync) when the underlying data changes. This loss of synchronization is sometimes called drift. This is conceptually [...]
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