September 17, 2014

One more InnoDB gap lock to avoid

While troubleshooting deadlocks for a customer, I came around an interesting situation involving InnoDB gap locks. For a non-INSERT write operation where the WHERE clause does not match any row, I expected there should’ve been no locks to be held by the transaction, but I was wrong. Let’s take a look at this table and […]

Want to archive tables? Use Percona Toolkit’s pt-archiver

Percona Toolkit’s pt-archiver is one of the best utilities to archive the records from large tables to another tables or files. One interesting thing is that pt-archiver is a read-write tool. It deletes data from the source by default, so after archiving you don’t need to delete it separately. As it is done by default, you […]

Knowing what pt-online-schema-change will do

pt-online-schema-change is simple to use, but internally it is complex.  Baron’s webinar about pt-online-schema-change hinted at several of the tool’s complexities.  Consequently, users often want to know before making changes what pt-online-schema-change will do when it runs.  The tool has two options to help answer this question: –dry-run and –print. When ran with –dry-run and –print, pt-online-schema-change changes nothing […]

Recovering from a bad UPDATE statement

Did you just run an UPDATE against your 10 million row users table without a WHERE clause?  Did you know that in MySQL 5.5 that sometimes you can recover from a bad UPDATE statement?  This is possible if you are running in binlog_format=ROW ! Imagine this scenario:

We run an accidental UPDATE statement that […]

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 […]

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 […]

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: […]

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 […]

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 […]

EXPLAIN EXTENDED can tell you all kinds of interesting things

While many people are familiar with the MySQL EXPLAIN command, fewer people are familiar with “extended explain” which was added in MySQL 4.1 EXPLAIN EXTENDED can show you what the MySQL optimizer does to your query. You might not know this, but MySQL can dramatically change your query before it actually executes it. This process […]