“The least expensive query is the query you never run.” Data access is expensive for your application. It often requires CPU, network and disk access, all of which can take a lot of time. Using less computing resources, particularly in the cloud, results in decreased overall operational costs, so caches provide real value by avoiding [...]
Flexviews – part 3 – improving query performance using materialized views
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 [...]
Using Flexviews – part two, change data capture
In my previous post I introduced materialized view concepts. This post begins with an introduction to change data capture technology and describes some of the ways in which it can be leveraged for your benefit. This is followed by a description of FlexCDC, the change data capture tool included with Flexviews. It continues with an [...]
Using Flexviews – part one, introduction to materialized views
If you know me, then you probably have heard of Flexviews. If not, then it might not be familiar to you. I’m giving a talk on it at the MySQL 2011 CE, and I figured I should blog about it before then. For those unfamiliar, Flexviews enables you to create and maintain incrementally refreshable materialized [...]
Modeling MySQL Capacity by Measuring Resource Consumptions
There are many angles you can look at the system to predict in performance, the model baron has published for example is good for measuring scalability of the system as concurrency growths. In many cases however we’re facing a need to answer a question how much load a given system can handle when load is [...]
Logging MySQL queries from the client instead of the server
The “slow query log” is the single most valuable way to examine query execution on your MySQL server. Queries are logged with timing information, and in the case of Percona Server, a great deal of additional performance and other diagnostic information. But the execution time recorded in the log is the time the query took [...]
Data Corruption, DRBD and story of bug
Working with customer, I faced pretty nasty bug, which is actually not rare situation , but in this particular there are some lessons I would like to share. The case is pretty much described in bug 55981, or in pastebin. Everything below is related to InnoDB-plugin/XtraDB, but not to regular InnoDB ( i.e in MySQL [...]
Estimating Replication Capacity
It is easy for MySQL replication to become bottleneck when Master server is not seriously loaded and the more cores and hard drives the get the larger the difference becomes, as long as replication remains single thread process. At the same time it is a lot easier to optimize your system when your replication runs [...]
Data mart or data warehouse?
This is part two in my six part series on business intelligence, with a focus on OLAP analysis. Part 1 – Intro to OLAP Identifying the differences between a data warehouse and a data mart. (this post) Introduction to MDX and the kind of SQL which a ROLAP tool must generate to answer those queries. [...]
Extending Index for Innodb tables can hurt performance in a surprising way
One schema optimization we often do is extending index when there are queries which can use more key part. Typically this is safe operation, unless index length increases dramatically queries which can use index can also use prefix of the new index are they ? It turns there are special cases when this is not [...]

