MySQL 5.7 comes with a new set of features and multi-source replication is one of them. In few words this means that one slave can replicate from different masters simultaneously. During the last couple of months I’ve been playing a lot with this trying to analyze its potential in a real case that I’ve been […]
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State Snapshot Transfer (SST) is used in Percona XtraDB Cluster (PXC) when a new node joins the cluster or to resync a failed node if Incremental State Transfer (IST) is no longer available. SST is triggered automatically but there is no magic: If it is not configured properly, it will not work and new nodes […]
People using OpenStack Trove instances can hit a common issue in the MySQL world: how to perform schema change operations while minimizing the impact on the database server? Let’s explore the options that can allow online schema changes. Summary With MySQL 5.5, pt-online-schema-change from Percona Toolkit is your best option for large tables while regular […]
A deadlock in MySQL happens when two or more transactions mutually hold and request for locks, creating a cycle of dependencies. In a transaction system, deadlocks are a fact of life and not completely avoidable. InnoDB automatically detects transaction deadlocks, rollbacks a transaction immediately and returns an error. It uses a metric to pick the […]
This blog post is part two of two. Like part one, published Wednesday, this is a cross-post from Groupon’s engineering blog. Thanks again to Kyle Oppenheim at Groupon. And one more reminder that I’ll be at the Percona Live MySQL Conference and Expo next week in Santa Clara, California so look for me there. You […]
While we do have many blog posts on replication on our blog, such as on replication being single-threaded, on semi-synchronous replication or on estimating replication capacity, I don’t think we have one that covers the very basics of how MySQL replication really works on the high level. Or it’s been so long ago I can’t […]
It is no secret that bugs related to multithreading–deadlocks, data races, starvations etc–have a big impact on application’s stability and are at the same time hard to find due to their nondeterministic nature. Any tool that makes finding such bugs easier, preferably before anybody is aware of their existence, is very welcome.
A while back Friendfeed posted a blog post explaining how they changed from storing data in MySQL columns to serializing data and just storing it inside TEXT/BLOB columns. It seems that since then, the technique has gotten more popular with Ruby gems now around to do this for you automatically.
One question which comes up very often is when one should use SAN with MySQL, which is especially popular among people got used to Oracle or other Enterprise database systems which are quite commonly deployed on SAN. My question in such case is always what exactly are you trying to get by using SAN ?
Recently I was tasked with investigating slippage between master and slave in a standard replication setup. The client was using Maatkit’s mk-table-checksum to check his slave data was indeed a fair copy of that of the master.