May 18, 2013

InnoDB’s gap locks

One of the most important features of InnoDB is the row level locking. This feature provides better concurrency under heavy write load but needs additional precautions to avoid phantom reads and to get a consistent Statement based replication. To accomplish that, row level locking databases also acquire gap locks. What is a Phantom Read A [...]

How FLUSH TABLES WITH READ LOCK works with Innodb Tables

Many backup tools including Percona Xtrabackup, MyLVMBackup and others use FLUSH TABLES WITH READ LOCK to temporary make MySQL read only. In many cases the period for which server has to be made read only is very short, just few seconds, yet the impact of FLUSH TABLES WITH READ LOCK can be quite large because [...]

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 [...]

A recovery trivia or how to recover from a lost ibdata1 file

A few day ago, a customer came to Percona needing to recover data. Basically, while doing a transfer from one SAN to another, something went wrong and they lost the ibdata1 file, where all the table meta-data is stored. Fortunately, they were running with innodb_file_per_table so the data itself was available. What they could provide [...]

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: [...]

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 [...]

Using Flexviews – part two, change data capture

In my previous post I introduced materialized view concepts. This post begins with an introduction to change data capture technology and describes some of the ways in which it can be leveraged for your benefit. This is followed by a description of FlexCDC, the change data capture tool included with Flexviews. It continues with an [...]

Moving Subtrees in Closure Table Hierarchies

Many software developers find they need to store hierarchical data, such as threaded comments, personnel org charts, or nested bill-of-materials. Sometimes it’s tricky to do this in SQL and still run efficient queries against the data. I’ll be presenting a webinar for Percona on February 28 at 9am PST. I’ll describe several solutions for storing [...]

Replication of MEMORY (HEAP) Tables

Some Applications need to store some transient data which is frequently regenerated and MEMORY table look like a very good match for this sort of tasks. Unfortunately this will bite when you will be looking to add Replication to your environment as MEMORY tables do not play well with replication.