Percona's MySQL & InnoDB performance and scalability blog
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 [...]
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 [...]
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 [...]
Preamble: On performance, workload and scalability: MySQL has always been focused on OLTP workloads. In fact, both Percona Server and MySQL 5.5.7rc have numerous performance improvements which benefit workloads that have high concurrency. Typical OLTP workloads feature numerous clients (perhaps hundreds or thousands) each reading and writing small chunks of data. The recent improvements to [...]
Dear Community, Starting with this release, we introduce a new release model for Percona Server. From now on, we will have both Stable and Release Candidate releases. Release Candidates will introduce new features not yet available in Stable releases. Along with new features, our new 5.1.49-12.0 RC contains a couple of patches from the Facebook-MySQL [...]
A few weeks ago, we had a query optimization request from one of our customer. The query was very simple like:
1 | SELECT * FROM `table` WHERE (col1='A'||col1='B') ORDER BY id DESC LIMIT 20 OFFSET 0 |
This column in the table is looks like this:
1 | `col1` enum('A','B','C','CD','DE','F','G','HI') default NULL |
The table have 549252 rows and of course, there is an index on the col1. MySQL estimated the cardinality of that index as [...]
I’ve seen my posts on Ontime Air traffic and Star Schema Benchmark got a lot of interest (links: http://www.mysqlperformanceblog.com/2010/01/07/star-schema-bechmark-infobright-infinidb-and-luciddb/ http://www.mysqlperformanceblog.com/2009/10/02/analyzing-air-traffic-performance-with-infobright-and-monetdb/ http://www.mysqlperformanceblog.com/2009/10/26/air-traffic-queries-in-luciddb/ http://www.mysqlperformanceblog.com/2009/11/02/air-traffic-queries-in-infinidb-early-alpha/ ). However benchmarks by itself did not cover all cases I would want, so I was thinking about better scenario. The biggest problem is to get real big enough dataset, and I thank [...]
Couple of months ago there was a post by FreshBooks on getting great performance improvements by lowering table_cache variable. So I decided to investigate what is really happening here. The “common sense” approach to tuning caches is to get them as large as you can if you have enough resources (such as memory). With MySQL [...]
This is next post in series Analyzing air traffic performance with InfoBright and MonetDB Air traffic queries in LucidDB Air traffic queries in InfiniDB: early alpha Let me explain the reason of choosing these engines. After initial three posts I am often asked “What is baseline ? Can we compare results with standard MySQL engines [...]
As Calpont announced availability of InfiniDB I surely couldn’t miss a chance to compare it with previously tested databases in the same environment. See my previous posts on this topic: Analyzing air traffic performance with InfoBright and MonetDB Air traffic queries in LucidDB I could not run all queries against InfiniDB and I met some [...]
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