September 2, 2014

InnoDB Full-text Search in MySQL 5.6: Part 3, Performance

This is part 3 of a 3 part series covering the new InnoDB full-text search features in MySQL 5.6. To catch up on the previous parts, see part 1 or part 2 Some of you may recall a few months ago that I promised a third part in my InnoDB full-text search (FTS) series, in […]

Webinar: Building a highly scaleable distributed row, document or column store with MySQL and Shard-Query

On Friday, February 15, 2013 10:00am Pacific Standard Time, I will be delivering a webinar entitled “Building a highly scaleable distributed row, document or column store with MySQL and Shard-Query” The first part of this webinar will focus on why distributed databases are needed, and on the techniques employed by Shard-Query to implement a distributed […]

Sphinx search performance optimization: attribute-based filters

One of the most common causes of a poor Sphinx search performance I find our customers face is misuse of search filters. In this article I will cover how Sphinx attributes (which are normally used for filtering) work, when they are a good idea to use and what to do when they are not, but […]

Impact of memory allocators on MySQL performance

MySQL server intensively uses dynamic memory allocation so a good choice of memory allocator is quite important for the proper utilization of CPU/RAM resources. Efficient memory allocator should help to improve scalability, increase throughput and keep memory footprint under the control. In this post I’m going to check impact of several memory allocators on the […]

Index Condition Pushdown in MySQL 5.6 and MariaDB 5.5 and its performance impact

I have been working with Peter in preparation for the talk comparing the optimizer enhancements in MySQL 5.6 and MariaDB 5.5. We are taking a look at and benchmarking optimizer enhancements one by one. So in the same way this blog post is aimed at a new optimizer enhancement Index Condition Pushdown (ICP). Its available […]

Distributed set processing performance analysis with ICE 3.5.2pl1 at 20 nodes.

Demonstrating distributed set processing performance Shard-Query + ICE scales very well up to at least 20 nodes This post is a detailed performance analysis of what I’ve coined “distributed set processing”. Please also read this post’s “sister post” which describes the distributed set processing technique. Also, remember that Percona can help you get up and […]

The four fundamental performance metrics

There are many ways to slice and aggregate metrics of activity on a system such as MySQL. In the best case, we want to know everything about the system’s activity: we want to know how many things happened, how big they were, and how long they took. We want to know precisely when they happened. […]

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 […]

Death match! EBS versus SSD price, performance, and QoS

Is it a good idea to deploy your database into the cloud? It depends. I have seen it work well many times, and cause trouble at other times. In this blog post I want to examine cloud-based I/O. I/O matters a lot when a) the database’s working set is bigger than the server’s memory, or […]

Testing MySQL column stores

Recently I had the opportunity to do some testing on a large data set against two MySQL column-store storage engines. I’d like to note that this effort was sponsored by Infobright, but this analysis reflects my independent testing from an objective viewpoint. I performed two different types of testing. The first focused on core functionality […]