May 21, 2013

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 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 [...]

Percona Server 5.5.8 Beta Release

It’s finally here! Percona Server Percona Server 5.5.8-20.0 is now available for download. This is a beta release of Percona’s enhancements to the MySQL 5.5.8 server. Here are some highlights: Performance and scalability improvements throughout the server and storage engine Optimizations for flash storage such as SSD, Virident, and FusionIO Optimizations for cloud computing The [...]

Spreading .ibd files across multiple disks; the optimization that isn’t

Inspired by Baron’s earlier post, here is one I hear quite frequently – “If you enable innodb_file_per_table, each table is it’s own .ibd file.  You can then relocate the heavy hit tables to a different location and create symlinks to the original location.” There are a few things wrong with this advice:

MySQL Partitioning – can save you or kill you

I wanted for a while to write about using MySQL Partitioning for Performance Optimization and I just got a relevant customer case to illustrate it. First you need to understand how partitions work internally. Partitions are on the low level are separate table. This means when you’re doing lookup by partitioned key you will look [...]

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 [...]

Tuning InnoDB Concurrency Tickets

InnoDB has an oft-unused parameter innodb_concurrency_tickets that seems widely misunderstood. From the docs: “The number of threads that can enter InnoDB concurrently is determined by the innodb_thread_concurrency variable. A thread is placed in a queue when it tries to enter InnoDB if the number of threads has already reached the concurrency limit. When a thread [...]

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 [...]

How innodb_open_files affects performance

Recently I looked at table_cache sizing which showed larger table cache does not always provides the best performance. So I decided to look at yet another similar variable – innodb_open_files which defines how many files Innodb will keep open while working in innodb_file_per_table mode. Unlike MyISAM Innodb does not have to keep open file descriptor [...]

Air traffic queries in LucidDB

After my first post Analyzing air traffic performance with InfoBright and MonetDB where I was not able to finish task with LucidDB, John Sichi contacted me with help to setup. You can see instruction how to load data on LucidDB Wiki page You can find the description of benchmark in original post, there I will [...]