It’s been a while since I blogged anything, mainly because most of my work lately has either been mind-numbing corporate stuff, or so highly contextualized that it wouldn’t be productive to write about.
Something came up last week, though, that just blew me away.
For various reasons, I’ve engaged Relevance to do a project for me. (Actually, the first results were so good that I’ve now got at least three more projects lined up.) They decided—and by “they”, I mean Stuart Halloway—to write the engine at the heart of this application in Clojure. That makes it sound like I was reluctant to go along, but actually, I was interested to see if the result would be as expressive and compact as everyone says.
Let me make a brief aside here and comment that I’m finding it much harder to be the customer on an agile project than to be a developer. I think there are two main reasons. First, it’s hard for me to keep these guys supplied with enough cards to fill an iteration. They’re outrunning me all the time. Big organizations like my employer just take a long time to decide anything. Second, there’s nobody else I can defer to when the team needs a decision. It often takes two weeks just for me to get a meeting scheduled with all of the stakeholders inside my company. That’s an entire iteration gone, just waiting to get to the meeting to make a decision! So, I’m often in the position of making decisions that I’m not 100% sure will be agreeable to all parties. So far, they have mostly worked out, but it’s a definite source of anxiety.
Anyway, back to the main point I wanted to make.
My personal theme is making software production-ready. That means handling all the messy things that happen in the real world. In a lab, for example, only one batch file ever needs to be processed at once. You never have multiple files waiting for processing, and files are always fully present before you start working on them. In production, that only happens if you guarantee it.
Another example, from my system. We have a set of rules (which are themselves written in Clojure code) that can be changed by privileged users. After changing the configuration, you can tell the daemonized Clojure engine to “(reload-rules!)”. The “!” at the end of that function means it’s an imperative with major side effects, so the rules get reloaded right now.
I thought I was going to catch them up when I asked, oh so innocently, “So what happens when you say (reload-rules!) while there’s a file being processed on the other thread?” I just love catching people when they haven’t dealt with all that nasty production stuff.
After a brief sidebar, Stu and Glenn Vanderburg decided that, in fact, nothing bad would happen at all, despite reloading rules in one thread while another thread was in the middle of using the rules.
Clojure uses a flavor of transactional memory, along with persistent data structures. No, that doesn’t mean they go in a database. It means that changes to a data structure can only be made inside of a transaction. The new version of the data structure and the old version exist simultaneously, for as long as there are outstanding references to them. So, in my case, that meant that the daemon thread would “see” the old version of the rules, because it had dereferenced the collection prior to the “reload-rules!” Meanwhile, the reload-rules! function would modify the collection in its own transaction. The next time the daemon thread comes back around and uses the reference to the rules, it’ll just see the new version of the rules.
In other words, two threads can both use the same reference, with complete consistency, because they each see a point-in-time snapshot of the collection’s state. The team didn’t have to do anything special to make this happen… it’s just the way that Clojure’s references, persistent data structures, and transactional memory work.
Even though I didn’t get to catch Stu and Glenn out on a production readiness issue, I still had to admit that was pretty frickin’ cool.