This is the third post in a series about developing the MepSQL build system. In the previous posts we chose BuildBot running in the Amazon EC2 cloud. In this post we actually get a closer look at how the packages are being built (to be followed by even closer looks in later posts :-)

One of the things missing when you fork MySQL is the build system. (The other main missing component being the manual.) It is possible for anyone to compile MySQL from source, but the actual build system (scripts, testing, etc) used by MySQL itself is not public. The same is true for the automated testing. MariaDB uses the open source tool called BuildBot for both of these tasks - in this post we are mainly concerned about the building of packages. Actually, we are mainly concerned with BuildBot itself and the details about building packages is saved for a later post. I will document both the MariaDB system and the MepSQL system which was derived from that.

This is the second part in a series of posts about how the MepSQL packages were built. In part 1 I evaluated OpenSuse Build System and Launchpad PPA and ended up concluding that running your own BuildBot system is the best choice, as those public services didn't provide any facility to test their packages.

This brings us to the next topic: As I don't possess any servers, should I buy one (or more) or should I try out the cloud services? If yes, should I use Amazon EC2 or something else?

This is the first part of many posts in a series of blog posts where I want to document how the MepSQL packages were built. By doing that, I will also end up covering the MariaDB build system (which this is based on), some of BuildBot, Amazon EC2 cloud and packaging DEBs and RPMs just in general, so it could be interesting from many perspectives. In this first part I'll simply scribble some notes about reviewing the OpenSuse Build System, Launchpad PPA service vs using your own servers and automating the builds with BuildBot.

Originally I just wanted to work on some new ideas on the automated build and QA system used by MariaDB. But since leaving Monty Program I didn't have access to any of those servers anymore, so as a first step I had to look into what alternatives there are for building binary packages for many operating systems and hardware platforms. In fact, this was another thing I had wanted to learn more about for a while. For instance Michal Hrušecký uses OpenSuse Build Service to build both MySQL and MariaDB packages for all RPM based distributions in the blink of an eye - I was interested to find out what's behind that magic.

After another week of hacking on MepSQL the DEB files for Ubuntu are now available.(MepSQL is my new "just a hobby" MySQL fork project.)

The Download page has instructions on how to install the packages with a simple apt-get install command. Debian packages will appear soon as they are now easy to add - I mostly just need to add new Amazon images for each.

Some time ago Stephen O'Grady and Brian Aker had an interesting Blogo-dialogue about what they call the "Cambrian Explosion" of open source development. The Cambrian Explosion means that we increasingly see forks of projects being developed in different directions, where traditionally we are used to open source development happening in relatively hierarchical and easy to follow upstream and downstream relationships. This is exactly what happens in the MySQL community currently, where in total there is more progress than ever before, but that progress is divided among several competing forks, none of which is strictly in an upstream-downstream hierarchy with each other.

I used to be a bit frustrated about this state of affairs, believing that if at least most of the forks could co-operate on a common tree, we would see even faster progress. But when I left MariaDB some months ago, I realized that the situation is what it is and since all existing MySQL variants are associated with a commercial vendor, there wasn't an obvious choice for me to continue contributing, which I still want to do. So I thought I might as well embrace this Cambrian Explosion thing and just publish my own fork as a contribution to the community.

And this is where I today announce the new MepSQL project and the immediate availability of MepSQL 5.1.52-alpha1.

A primary motivation for writing the Open Life book, as well as this blog, was not only to write about open source software, but to encourage applications of open source outside the world of software. Part four of the book covers such topics from Wikipedia and Project Gutenberg to a mining company releasing it's mining data to the public. Some of the chapters also propose some ideas that had not been done yet at the time of writing. One was open source movies.

In November a Mark Schonewille posted a blog on when you can't and cannot use the GPL version of MySQL together with your closed source application. The post was a result of actually talking to an Oracle lawyer which makes it valuable information. Unfortunately Mark's blog is now offline (it seems he didn't renew his domain registration?)

This is just a repost of the disappeared blog post. (The small print allows me to copy it verbatim.) There is no commentary from myself, except that what Mark wrote is the same I also heard Oracle say a year ago. That Oracle is being consistent on this point is very welcome and deserves to be kept available online.

Update 2011-06-23: Mark comments that his blog is still online, but at a new address: https://qery.us/tl

I often wonder what's behind the increased trend behind Hadoop and other NoSQL technologies. I realize if you're Yahoo that such technology makes sense. I don't get why everyone else wants to use it.

Reading Stephen O'Grady's self-review of his predictions for 2010 for the first time gave me some insights into how such people think:

Democratization of Big Data

Consider that RedMonk, a four person analyst shop, has the technical wherewithal to attack datasets ranging from gigabytes to terabytes in size. Unless you’re making institutional money, budgets historically have not permitted this. The tools of Big Data have never been more accessible than they are today.