Even thought I am a Windows user, I am no where near a Microsoft lackey but recently I learned that Microsoft is giving away a ton of professional grade software to students. Through the Microsoft DreamSpark program, students can get access to Visual Studio 2008 Professional, Windows Server 2003 Standard Edition, Microsoft Expression Studio, XNA Studio, XNA Creators Club, SQL Server 2005, as well as other free software such as their express edition software. That is well over $1,500 of free software. I am typically not a Microsoft fanboy but I do have to give credit to Microsoft for making its development tools free of charge to students across the world. Now I wish Adobe would do the same.
Technorati Tags: microsft, dreamspark, xna, visual studio, windows, sql server, c#, adobe
Percona is looking to hire someone to develop Maatkit, among other things.
If I weren’t having so much fun being the consulting team lead, I’d be doing it myself. (In fact, I’m still hacking on it a lot. Got some pretty fun stuff done this weekend.) I don’t know what the rest of the world thinks, but I think Maatkit is a damn enjoyable project to work on. Hopefully someone else will have the same kind of mindset and want to get paid for it, unlike poor working-on-the-weekends me.
I’m not stepping away from the project. It’s just grown a lot, and there is room and money to grow it much more. This is actually the best compliment to the project: that it is worth hiring someone to keep improving it. Lots of people are using it, and there’s a lot of stealth-mode stuff I/we want to do with it too.
On a related note, who wants me to order another batch of Maatkit t-shirts? I’ve gotten quite a few questions about it.
No TagsMy post on what it’s like to write a technical book was a stream-of-consciousness look at the process of writing High Performance MySQL, Second Edition. I got a lot of responses from it and learned some neat things I wouldn’t have learned if I hadn’t written the post. I also got a lot of questions, and my editor wrote a response too. I want to follow up on these things.
I really intended to write the post as just “here’s what it’s like, just so you’re prepared.” But at some point I got really deep into it and lost my context. That’s when I started to write about the things that didn’t go so smoothly with the publisher, and some of these things had a little extra sting in them that I would have done well to edit out.
All of us are human and the process wasn’t that bad, all things considered — the book was just a massive project that put huge demands on all of us and stressed everything from the capabilities of our chosen tools to our patience. As the editor points out in his response to my blog post, this is precisely why nobody else has ever been able to pull this off. This book stands head and shoulders above the crowd. It’s just hard to write, and very few people in the world actually have the knowledge to do it, much less the time, inclination, and ability.
Everything I said was (I believe) factual and correct, although as the editor points out there are different stories behind them. I also want to mention that I’d shared all those concerns with my editor; I avoid criticizing people behind their backs. In hindsight, throwing all of my concerns onto a blog post without warning isn’t the kind of thing I like to do either.
So I believe I was honest, but unfair to the editor. I’ve apologized to him. And by the way, yes I would work with him again, and I fully expect that it would be easier because I have learned more about the process.
I ran this post by my editor before publishing it.
Several people asked me to say more about my heuristics for improving the quality of the writing. I’ve already explained many of them, but here’s more:
The tools I used to find sentences and phrases that score badly on some readability metric were pretty helpful to me as I tightened the writing up more and more. Nobody has reviewed the book yet, but I think when they do, they’ll be unlikely to mention “oh, and by the way the writing is wonderfully compact!” If we pulled this off right, you won’t notice that the writing is clear and compact. Writing is like a stereo system: you’re supposed to hear the music, not the speakers.
Anyway, my point is that we expanded the first edition’s actual coverage many times over, and ended up with only 658 pages of actual material. So the writing is much more compressed, and to do that you have to find and eliminate confusing writing. Confusing writing usually means that the concepts don’t flow clearly, and it takes more words to say the same thing because you’re kind of bumbling about, gesturing at your meaning from several angles instead of saying it clearly just once.
Here’s how I analyzed each chapter:
As I wrote in my previous post, the analyzer uses a combination of readability metrics and “other stuff” to measure the badness of each sentence and paragraph. It aggregates sentences and paragraphs by the metrics. I calculated the number of words, percent of complex words, syllables per word, number of sentences, words per sentence, and a bunch of other things, as well as the standard readability metrics. Each sentence and paragraph got scored on these. Then I printed overall metrics, and sorted the sentences and paragraphs worst-first and printed out a snippet of the offending text. Here’s a sample of chapter 3’s metrics (originally numbered chapter 4) at some intermediate stage in the writing process.
This was a lot of work. If I had been writing with Vim, I could have done better. I could have used the compiler integration and set my “make” program to the analysis program. If you use Vim and you don’t know about this, it’s a pity. My next book will be written in Vim, by the way.
Actually, I probably could have done better regardless, but this was good enough. I just searched for the snippets and then examined what was going on.
There were some false positives. For example, bullet-points often scored badly on the readability metrics, and so a five-word bullet point item would look like terrible writing just because it was short enough that it had a high percentage of complex words. It’s not an exact science. Maybe next time will be better.
If you’d like to see the source code, here’s the clean_text.pl and here’s the analyze_text.pl. Enjoy!
Perl, writing