My previous benchmark on Performance Schema was mainly in memory workload and against single tables. Now after adding multi-tables support to sysbench, it is interesting to see what statistic we can get from workload that produces some disk IO. So let’s run sysbench against 100 tables, each 5000000 rows (~1.2G ) and buffer pool 30G. [...]
MySQL caching methods and tips
“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 [...]
Ultimate MySQL variable and status reference list
I am constantly referring to the amazing MySQL manual, especially the option and variable reference table. But just as frequently, I want to look up blog posts on variables, or look for content in the Percona documentation or forums. So I present to you what is now my newest Firefox toolbar bookmark: an option and [...]
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 [...]
Shard-Query adds parallelism to queries
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 [...]
MySQL Limitations Part 3: Subqueries
This is the third in a series on what’s seriously limiting MySQL in certain circumstances (links: part 1, 2). This post is about subqueries, which in some cases execute outside-in instead of inside-out as users expect.
A workaround for the performance problems of TEMPTABLE views
MySQL supports two different algorithms for views: the MERGE algorithm and the TEMPTABLE algorithm. These two algorithms differ greatly. A view which uses the MERGE algorithm can merge filter conditions into the view query itself. This has significant performance advantages over TEMPTABLE views. A view which uses the TEMPTABLE algorithm will have to compute the [...]
Checking for a live database connection considered harmful
It is very common for me to look at a customer’s database and notice a lot of overhead from checking whether a database connection is active before sending a query to it. This comes from the following design pattern, written in pseudo-code:
1 2 3 4 5 6 | function query_database(connection, sql) if !connection.is_alive() and !connection.reconnect() then throw exception end return connection.execute(sql) end |
Many of the popular development platforms do something similar to this. Two [...]
New OLAP Wikistat benchmark: Introduction and call for feedbacks
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 [...]

