I had a customer recently who needed to reduce their database size on disk quickly without a lot of messy schema redesign and application recoding. They didn’t want to drop any actual data, and their index usage was fairly high, so we decided to look for unused indexes that could be removed. Collecting data It’s […]
I had a lot of questions on my MySQL Indexing: Best Practices Webinar (both recording and slides are available now) We had lots of questions. I did not have time to answer some and others are better answered in writing anyway. Q: One developer on our team wants to replace longish (25-30) indexed varchars with […]
I presented a webinar today about SQL Injection, to try to clear up some of the misconceptions that many other blogs and articles have about this security risk. You can register for the webinar even now that I’ve presented it, and you’ll be emailed a link to the recording, which will be available soon. During […]
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 […]
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: […]
Shard-Query is an open source tool kit which helps improve the performance of queries against a MySQL database by distributing the work over multiple machines and/or multiple cores. This is similar to the divide and conquer approach that Hive takes in combination with Hadoop. Shard-Query applies a clever approach to parallelism which allows it to […]
I often see people confuse different ways MySQL can use indexing, getting wrong ideas on what query performance they should expect. There are 3 main ways how MySQL can use the indexes for query execution, which are not mutually exclusive, in fact some queries will use indexes for all 3 purposes listed here.
I vaguely recall a couple of blog posts recently asking something like “what’s the formula to compute mysqld’s worst-case maximum memory usage?” Various formulas are in wide use, but none of them is fully correct. Here’s why: you can’t write an equation for it.
JOINs are expensive and it most typical the fewer tables (for the same database) you join the better performance you will get. As for any rules there are however exceptions The one I’m speaking about comes from the issue with MySQL optimizer stopping using further index key parts as soon as there is a range […]
This is pretty simple approach I often use called to optimize web application performance if problem happens with few pages. If we have “everything is slow” problem looking at slow query logs may be better start. So what could you do ? Look at the information shown on the page which comes from database. This […]