Sometimes we need to restore only some tables from a full backup maybe because your data loss affect a small number of your tables. In this particular scenario is faster to recover single tables than a full backup. This is easy with MyISAM but if your tables are InnoDB the process is a little bit [...]
Identifying the load with the help of pt-query-digest and Percona Server
Overview Profiling, analyzing and then fixing queries is likely the most oft-repeated part of a job of a DBA and one that keeps evolving, as new features are added to the application new queries pop up that need to be analyzed and fixed. And there are not too many tools out there that can make [...]
Fishing with dynamite, brought to you by the randgen and dbqp
I tend to speak highly of the random query generator as a testing tool and thought I would share a story that shows how it can really shine. At our recent dev team meeting, we spent approximately 30 minutes of hack time to produce test cases for 3 rather hard to duplicate bugs. Of course, [...]
Improved InnoDB fast index creation
One of the serious limitations in the fast index creation feature introduced in the InnoDB plugin is that it only works when indexes are explicitly created using ALTER TABLE or CREATE INDEX. Peter has already blogged about it before, here I’ll just briefly reiterate other cases that might benefit from that feature: when ALTER TABLE [...]
Emulating global transaction ID with pt-heartbeat
Global transaction IDs are being considered for a future version of MySQL. A global transaction ID lets you determine a server’s replication position reliably, among other benefits. This is great when you need to switch a replica to another master, or any number of other needs. Sometimes you can’t wait for the real thing, but [...]
Distributed Set Processing with Shard-Query
Can Shard-Query scale to 20 nodes? Peter asked this question in comments to to my previous Shard-Query benchmark. Actually he asked if it could scale to 50, but testing 20 was all I could due to to EC2 and time limits. I think the results at 20 nodes are very useful to understand the performance: [...]
Connecting orphaned .ibd files
There are two ways InnoDB can organize tablespaces. First is when all data, indexes and system buffers are stored in a single tablespace. This is typicaly one or several ibdata files. A well known innodb_file_per_table option brings the second one. Tables and system areas are split into different files. Usually system tablespace is located in [...]
Shard-Query EC2 images available
Infobright and InnoDB AMI images are now available There are now demonstration AMI images for Shard-Query. Each image comes pre-loaded with the data used in the previous Shard-Query blog post. The data in the each image is split into 20 “shards”. This blog post will refer to an EC2 instances as a node from here [...]
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 [...]

