The release of MySQL 5.5 has brought several enhancements. While most of the coverage went, understandably, to the semi-synchronous replication, the enhancements of partitioning were neglected, and sometimes there was some degree of misunderstanding on their true meaning. With this article, we want to explain these cool enhancements, especially the parts that were not fully understood.

What's new, in a nutshell: http://dev.mysql.com/doc/refman/5.1/en/mysql-nutshell.html Release notes: http://dev.mysql.com/doc/refman/5.1/en/news-5-1-x.html (In the video, it's the page entitled "Changes in release 5.1.x"). And yes, very early on (at about 2 minutes in) I talk about my take on Monty's controversial post at http://monty-says.blogspot.com/2008/11/oops-we-did-it-again-mysql-51-released.html The slides can be downloaded as a PDF at http://technocation.org/files/doc/2008_12_New51.pdf or in Open Office presentation format at http://technocation.org/files/doc/2008_12_New51.odp

In the words of Sheeri: "At the January 2009 Boston User Group I presented a session on the new partitioning feature in MySQL 5.1. I go through how to define partitions, how partitioning makes queries faster, the different types of partitioning and when to use each type, and the restrictions and limitations of partitioning. The slides are available at http://www.technocation.org/files/doc/2009_01_Partitioning.pdf Notes: The partitioning part of the MySQL Manual is at: http://dev.mysql.com/doc/refman/5.1/en/partitioning-overview.html. The functions that are not allowed in partitioning expressions are listed at: http://dev.mysql.com/doc/refman/5.1/en/partitioning-limitations.html We also had an interesting development — according to the manual, an INSERT to a partitioned table that includes values that do not have a partition should insert all values up to the failure point. The example I used (and  []

Why sharding is not always good

This article explains how to test the performance of a large database with MySQL 5.1, showing the advantages of using partitions. The test database uses data published by the US Bureau of Transportation Statistics. Currently, the data consists of ~ 113 million records (7.5 GB data + 5.2 GB index).

Everybody needs sharding, and the Spider storage engine offers a nice solution, transparent to the final user, to implement sharding without losing track of usability.

Databases grow every day more. It is not uncommon to accumulate 100 GB of historical data with an increasing performance problem. MySQL 5.1 with partitions can solve your problems quickly and painlessly in many cases. Using partitions, you can deal with several simple data warehousing cases in a transparent way.

Insights from the developers behind MySQL Partitioning. How is partitioning implemented, how does it work in the server and with the storage engines? What solutions can it be a part of and what problems does it introduce? We present a new partitioning type: Column list, range partitioning on any column type. And give the status of the current development.

The Spider Storage Engine creates table-links from local databases to remote databases. To supports XA transaction and table partitioning itself, the Spider also created for the database shardings. Spider Storage Engine is being offered to the public by GPL. http://spiderformysql.com

Based on a real-world case study from a comprehensive market intelligence product - developed for Boats.com/YachtWorld.com by Breadboard BI, Inc - this 45 minute presentation describes a multi-source, enterprise data warehouse developed on a 100% open source stack - MySQL 5.1 (with partitioning), Pentaho Business Intelligence Suite, Linux OS.