Hosting a shared MySQL instance for your internal or external clients (“multi-tenant”) was always a challenge. Multi-tenants approach or a “schema-per-customer” approach is pretty common nowadays to host multiple clients on the same MySQL sever. One of issues of this approach, however, is the lack of visibility: it is hard to tell how many resources (queries, disk, […]
In the very early days of Percona Vadim wrote very nice post about GROUP_CONCAT. But I want to show you a bit more about it. When is GROUP_CONCAT useful? Usually while working with Support customers I recommend it when you have aggregation of many-to-many info. It makes the view simpler and more beautiful and it […]
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 […]
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 […]
(There is an updated version of this post here) MySQL has useful extention to the GROUP BY operation: function GROUP_CONCAT: GROUP_CONCAT(expr) – This function returns a string result with the concatenated non-NULL values from a group. Where it can be useful?
Percona is glad to announce the release of Percona Server 5.1.73-14.12 on July 31st, 2014 (Downloads are available here and from the Percona Software Repositories). Based on MySQL 5.1.73, including all the bug fixes in it, Percona Server 5.1.73-14.12 is now the current stable release in the 5.1 series. All of Percona‘s software is open-source and free, all the details of the release […]
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 […]