Well actually….no. The second Development Milestone Release of MySQL Cluster 7.2 introduces support for what we call “Multi-Site Clustering”. In this post, I’ll provide an overview of this new capability, and considerations you need to make when considering it as a deployment option to scale geographically dispersed database services.<?xml:namespace prefix = o />

You can read more about MySQL Cluster 7.2.1 in the article posted on the MySQL Developer Zone. 

MySQL Cluster has long offered Geographic Replication, distributing clusters to remote data centers to reduce the affects of geographic latency by pushing data closer to the user, as well as providing a capability for disaster recovery.

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Well actually….no. The second Development Milestone Release of MySQL Cluster 7.2 introduces support for what we call “Multi-Site Clustering”. In this post, I’ll provide an overview of this new capability, and considerations you need to make when considering it as a deployment option to scale geographically dispersed database services.<?xml:namespace prefix = o />

You can read more about MySQL Cluster 7.2.1 in the article posted on the MySQL Developer Zone. 

MySQL Cluster has long offered Geographic Replication, distributing clusters to remote data centers to reduce the affects of geographic latency by pushing data closer to the user, as well as providing a capability for disaster recovery.

…

Clustered computing brings with it many benefits: high performance, high availability, scalable infrastructure, etc. But it also brings with it more complexity.

Why?

Well, by its very nature, there are more “moving parts” to monitor and manage (from physical, virtual and logical hosts) to clustering software to redundant networking components – the list goes on. And a cluster that isn’t effectively provisioned and managed will cause more downtime than the standalone systems it is designed to improve upon.

When it comes to the database industry, analysts already estimate that 50% of a typical database’s Total Cost of Ownership is attributable to staffing and downtime costs. These costs will only increase if a database cluster is not effectively monitored and managed.

Monitoring and management has been a major focus in the development of the …

Dear Kettle friends,

on occasion we need to support environments where not only a lot of data needs to be processed but also in frequent batches.  For example, a new data file with hundreds of thousands of rows arrives in a folder every few seconds.

In this setting we want to use clustering to use “commodity” computing resources in parallel.  In this blog post I’ll detail how the general architecture would look like and how to tune memory usage in this environment.

Clustering was first created around the end of 2006.  Back then it looked like this.

The master

This is the most important part of our cluster.  It takes care of administrating network configuration and topology.  It also keeps track of the state of dynamically added slave servers.

The master …

InnoDB uses an index-organized data storage technique, wherein the primary key acts as the clustered index and this clustered index holds the data. Its for this reason that understanding the basics of InnoDB primary key is very important, and hence the need for these notes.

If you haven't done that, thinking that you would spare your energies for more juicy matters, I have news for you. What I explained in the previous part is exactly what you need to do to set up parallel replication. With just a tiny additional detail.
For the sake of the diligent readers who have followed the instructions with the first lessons, I won't repeat them, but I'll invite you to set the environment as explained in the first part.
Once you have a cluster up and …

Some people don't probably know, but there is a difference between how indexes work in MyISAM and how they work in InnoDB, particularly when talking from the point of view of performance enhancement. Now since, InnoDB is starting to be widely used, it is important we understand how indexing works in InnoDB. Hence, the reason for this post!

If you haven’t seen it, Josh Berkus has a very concise way to look at the confusing mess that is database “clustering” from the point of view of three distinct types of users: transactional, analytic, and online. I think that using this kind of distinction could help keep discussions clear — I’ve seen a lot of conversations around clustering run off the rails due to disagreements about what clustering means. MySQL Cluster, for example, is a huge red herring for a lot of people, but it seems to be a difficult process to learn it well enough to decide. If we called it a clustering solution for transactional users, but not for analytic or online users, it might help a lot.

Related posts:

1. …

Mike Hogan, CEO of ScaleDB spoke at the Boston MySQL User Group in September 2009:

ScaleDB is a storage engine for MySQL that delivers shared-disk clustering. It has been described as the Oracle RAC of MySQL. Using ScaleDB, you can scale your cluster by simply adding nodes, without partitioning your data. Each node has full read/write capability, eliminating the need for slaves, while delivering cluster-level load balancing. ScaleDB is looking for additional beta testers, there is a sign up at http://www.scaledb.com.

Slides are online (and downloadable) at http://www.slideshare.net/Sheeri/scale-db-preso-for-boston-my-sql-meetup-92009

Watch the video online at …