The vmware config used for this example. This is a quick tour of LVM and a demonstration how it is superior to static partitions. Basically, LVM provides you with a way to create dynamic partitions - you will be able to grow and shrink partitions on demand, move them between disks and snapshot them for backup, all while the filesystem and database on top of it are active and busy.

The LVM tour in this blog post has been created on a vmware instance with a Suse 10.0 Professional installation which I am using to show a combination of RAID and LVM configuration examples. The vmware has a bit of memory, a network card, a boot disk with a text only Suse 10 installation and 8 small simulated SCSI disks besides the boot disk to demonstrate stuff.

Here is the configuration for the basic system.


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Today I helped one of our lead Cluster developers, Martin Skold, finish up the editing on a article you should see posted on the MySQL Developers Zone page next week. The article is titled, "MySQL Cluster 5.0 ALTER TABLE In-Depth".

The article covers the MySQL ALTER TABLE syntax with code examples, how it works behind the scenes, and using the ndb_show_tables utility to verify results. He also gives us a preview into some of the improvements made to the ALTER TABLE functionality in 5.1.

ALTER TABLE enthusiasts should definitely check this article out. I'll add a link to the article on this blog post once the Web guys make it available.

- Jimmy

Please feel free to forward to interested parties.

Who: Jim Starkey at the Boston MySQL Meetup Group
What: Falcon, the new MySQL storage engine
When:
Monday, July 10, 2006 at 7:00 PM
Where:
MIT Building E51, Room 372
Wadsworth and Amherst Streets
Cambridge, MA 02117
Steps from the Red line, plenty of free parking.

The July Boston MySQL Meetup’s topic is Falcon, the new storage engine for MySQL. Creator Jim Starkey will speak. Jim Starkey has been writing database software for 20 years. He created BLOBs, multi-versioning concurrency for relational databases, cascading update triggers, event alerters, and more. Read more about him at http://tinyurl.com/lno4p and http://tinyurl.com/mym7d.

We will be meeting on MIT campus, close to the Kendall stop on the Red Line (subway). There is also plenty of free parking — you can park in ANY MIT lot after 3 pm, even if it says …

YAMQ (yet another MySQL question) came up at work this past week. Some of our old data warehousing libraries work under the assumption that MySQL can only handle 16 indexes (built during the early 3.23.x days). So the question is how many indexes can a single table have these days?

This is similar to last week's questions on how many joins MySQL can handle. I don't see much in the way of official documentation, but dug around the forums and found good information in this thread.

Creating an index requires creating a key, and there's a limit placed on the number of keys allowed for a table. Thus the limit on indexes is governed by the number of keys you are allowed to create. The error message when you've created one too many keys looks like:

PHP is different. Unlike Java for example, there is no formal community, and no formal community process. PHP does not see itself as controlled by a company, or even large corporate players. PHP is not developed, it kind of grows. People using other languages see this as a weakness, but I actually think of it as a strength of the language, the platform and the community.

PHP is used differently than for example Java. Successful PHP projects use different strategies. If you have listened to what Rasmus has been telling you in his speeches during the last two years, you might get an idea of how PHP is different, and why. If you are comparing the approach MySQL has been using in the Dell DVD webshop benchmark uncontest with the other PHP approaches, you can see some of these principles applied.

Unfortunately, for many of these principles and methodologies no fancy names exist. So in my untalk on the PHP unconference at …

Back in April MySQL had its yearly user's conference. Each year there are more users and more people to talk to, which means I get fewer chances to listen to any of the talks being presented. I did though take time out to listen to the talk on Second Life. I've been playing with BBS'es, Talkers, and other assorted digital online communities ever since I got my first modem. What fascinated me about Second Life was the prospect of it taking a shot at being the first "metaverse". I am a big fan of "Snow Crash" and would love to see that sort of environment spring to life. I work daily with friends and colleagues using IM and IRC, and any depth that can be added to those conversations is great as far as I am concerned.

I have also been fascinated with learning about how they are scaling with MySQL. Their design is fairly classic with replication, but what is interesting is to look and see how this is applied to a virtual …

At the developers conference this year, held in Sorrento, Italy, I was fortunate enough to meet and have dinner with some Italian MySQL users?some of whom had travelled from Rome to be with us that evening at a lovely traditional Italian restaurant just off one of the main squares.

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I?ve recently written about techniques for archiving, purging, and re-indexing huge database tables. These techniques exploit both data structure and usage patterns. In this article I?ll develop that theme further, and explain how to write more efficient non-backtracking maintenance jobs when the update and insertion patterns permit.

part of my focus for the next couple of weeks will be on rolling out some improvements to the mysql bugs system. the first step in doing that was to upgrade from mysql 4.1 to the latest mysql 5.1 beta, which turned out to be entirely painless.

the next step is going to be some database normalization and code refactoring. but because there are some other people who have written ad-hoc tools against the existing schema, i?ll be hiding the schema changes behind some views.

the first big schema change will be moving the categories from a bunch of hard-coded strings in the source code (and a varchar(32) field) to a table organized using the nested set model. that?s something i?ve been …