Introduction

Attracting over 2m subscribers in just 4 months and growing by 30,000 new users per day, Playful Play needed a database that was able to keep pace with the massive scalability and high availability demands of the wildly successful La Vecindad de El Chavo Facebook game.

Playful Play selected MySQL Cluster CGE running on a public cloud to power their gaming platform, providing:

• 45% improvement in performance;
• 99.999% uptime;
• 80% reduction in DBA overhead;
• Local language support, 24x7.

As a result, Playful Play has been able to maintain user growth rates and attract new advertisers to the platform, while enhancing agility and reducing cost. …

The MySQL Cluster engineering team recently ran a live webinar, available now on-demand demonstrating the ClusterJ and ClusterJPA NoSQL APIs for MySQL Cluster, and how these can be used in building real-time, high scale Java-based services that require continuous availability.

Attendees asked a number of great questions during the webinar, and I thought it would be useful to share those here, so others are also able to learn more about the Java NoSQL APIs.

First, a little bit about why we developed these APIs and why they are interesting to Java developers.

ClusterJ and Cluster JPA

ClusterJ is a Java interface to MySQL Cluster that provides either a static or dynamic domain object model, similar to the data model used by JDO, …

In a previous post I wrote ARM based servers. Since then, and thanks to all the comments and responses I got, I looked more into this ARM thing and it's absolutely fascinating...

Look at this beauty (taken from the site of Calxeda, the manufacturer):

What is it? A chip? A server? No, it's a cluster of 4 servers...

And this:

is HP Redstone Server, 288 chips, 1,152 cores (Calxeda quad-core SoC) in a 4U server “Dramatically reducing the cost and complexity of cabling and …

In my previous post I covered the shard-disk paradigm's pros and cons, but the conclusion that is that it cannot really qualify as a scale-out solution, when it comes to massive OLTP, big-data, big-sessions-count and mixture of reads and writes.

Read/Write splitting is achieved when numerous replicated database servers are used for reads. This way the system can scale to cope with increase in concurrent load. This solution qualifies as a scale-out solution as it allow expansion beyond the boundaries of one DB, DB machines are shared-nothing, can be added as a slave to the replication "group" when required.


And, as a fact, read/write …

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Yesterday I was asked by a customer for the reason why he had failed to achieve scale with a state-of-the-art "shared-storage" cluster. "It's a scale-out to 4 servers, but with a shared disk. And I got, after tons of work and efforts, 130% throughput, not even close to the expected 400%" he said.

Well, scale-out cannot be achieved with a shared storage and the word "shared" is the key. Scale-out is done with absolutely nothing shared or a "shared-nothing" architecture. This what makes it linear and unlimited. Any shared resource, creates a tremendous burden on each and every database server in the cluster.

In a previous post, I identified database engine activities such as buffer management, locking, thread locks/semaphores, and recovery tasks - as the main bottleneck in the OLTP …

Earlier this week, Andrew Morgan wrote a piece on running MySQL Cluster on Raspberry Pi. Since the term “Cluster” is hideously overloaded, I’ll note that we’re talking about the NDB cluster storage engine here, a very specific architecture originally acquired by MySQL AB from Ericsson (telco).

Raspberry Pi is a new single-board computer based on the ARM processor series (same stuff that powers most mobile phones these days), and it can run Linux without any fuss. Interfaces include Ethernet, USB, and HDMI video, and the cost is $25-50. I’m looking to use one for the front-end of a MythTV setup (digital video recorder and TV system), I can just strap the Raspberry Pi to the back of a TV or monitor to do its …

Back in 2006 we became aware of problems storing large numbers of rows in a single table in cluster. Johan Andersson and Yves Trudeau have each blogged about the problem and the common workaround here and here.  We've since then done some cleanup to provide a more proper "Table is full" error message when running into this problem.

As explained in the referenced blog posts, the problem is the result of a limitation on the size of the hash index of each partition. The hash index for each partition would allow at most ~49 million records. By default an ndbd or ndbmtd node have only 1 local query handler (LQH) block and thus 1 partition per node.  The ndbmtd nodes having MaxNoOfExecutionThreads = 4 or 8 cluster will have 2 or 4 LQH per node respectively. So, the …

Summary (aka TL/DR):

Support for Foreign Key constraints has been one of the most requested feature enhancements for MySQL Cluster. We are therefore extremely excited to announce that Foreign Keys are part of the first Labs Release of MySQL Cluster 7.3 – available for download, evaluation and feedback now! (Select the mysql-cluster-7.3-labs-June-2012 build)

In this blog, I will attempt to discuss the design rationale, implementation, configuration and steps to get started in evaluating the first MySQL Cluster 7.3 Labs Release.

Pace of Innovation

It was only a couple of months ago that we announced the General …

I had to install Percona XtraDB Cluster, I think for the first time since it was announced stable. I remembered many problems I faced with beta releases, which was understandable given they were only for a preview, but this time I hoped for significant improvements.

I have to say I am generally quite sensitive about simple problems that could/should be easily discovered and corrected. Well, it didn’t take five minutes to see a few of such problems. These minutes I spent installing the database binaries from Percona Yum repository. It turned out that was enough to see a lot of errors for no reason. Not a good thing.

[..]
  Installing : 1:Percona-XtraDB-Cluster-server-5.5.23-23.5.333.rhel6.x86_64         5/5
ls: cannot access /var/lib/mysql/*.err: No such file or directory
ls: cannot access /var/lib/mysql/*.err: No such file or directory
[Note] Flashcache bypass: disabled

Why does it matter that ls: cannot access …