Pythian Group

OpenSQLCamp was a huge success! Not many folks have blogged about what they learned there….if you missed it, all is not lost. We did take videos of most of the sessions (we only had 3 video cameras, and 4 rooms, and 2 sessions were not recorded).

All the videos have been processed, and I am working on uploading them to YouTube and filling in details for the video descriptions. Not all the videos are up right now….right now all the lightning talks are up.

• All the lightning talks belowin one continuous video (just over 54 minutes total)
• The Graph Engine (Antony Curtis)
• Cluster/J, a new set of Java APIs to MySQL Cluster 5.1 (John David Duncan)
• Sphinx, the fulltext storage engine (Peter Zaitsev)
• iiBench, the Indexed Insertion Benchmark (Bradley Kuszmaul of Tokutek)
• JJtree in Coco
• Integrating OSS with Windows (Tom Hanrahan of Microsoft)
• Trainwreck, an agent for MySQL replication (Domas Mituzas)
• Column Stores (David Lutz of Infobright)
• I Play With Data, about doing real statistical calculations of data, when SQL gets in the way (Joseph di Paolantonio)
• Your Guide to NoSQL (Brian Aker)
• PL/Parrot The call for PL/Parrot in Postgres is put out there (Jonathan “Duke” Leto)

Read the rest of this entry . . .

If you have a 12-server MySQL Cluster with:

1 Management Node
3 SQL Nodes
2 Data Node Groups, 4 Data Nodes per group

And each machine is configured to allocate 1G of memory for its function, how much data (data + indexes) can you store in total in your cluster?

You can guess, but you get bonus points if you explain why and the explanation is correct.

Someone asked me what applications were good/bad for MySQL Cluster. As I’ve now actually had experience with a Cluster setup and a real-life application of it, and dug through the manual, I present a few characteristics of applications that will work with Cluster, and why they are so (so that if you have an application that meets some of the characteristics but not all of them, you can decide whether it’s worth it to use Cluster or not).

Firstly, I’ll state this — there’s actually a very limited application to MySQL cluster. I haven’t assessed the disk-based cluster, only the memory-based one, so I don’t know what really changes with disk-based. But after you see this list, you certainly will want to re-think your use of disk-based cluster if a lot of the inner workings don’t change.

The factors are listed below, but the “ruler” I keep in my mind is the fact that MySQL Cluster was developed for telecom applications. The basic characteristic is a lot of writes, small data in amounts that can fit into memory, and the data being transient in nature. Something like a “session” table is a great application.

So here are the characteristics of a good application for MySQL Cluster, with explanations of why: Read the rest of this entry . . .