Google App Engine and other tidbits
As anticipated, Java support on Google App Engine has been announced. To date, GAE has supported only the Python programming language. In keeping with the “phenomenal cosmic power, itty bitty living space” sandboxing that’s become common to cloud execution environments, GAE/Java has all the restrictions of GAE/Python. However, the already containerized nature of Java applications means that the restrictions probably won’t feel as significant to developers. Many Python libraries and frameworks are not “pure Python”; they include C extensions for speed. Java libraries and frameworks are, by contrast, usually pure Java; the biggest issues for porting Java into the GAE environment are likely to be the restrictions on system calls and the lack of threads. Generically, GAE/Java offers servlets. The other things that developers are likely to miss are support for JMS and JMX (Java’s messaging and monitoring, respectively).
Overall, the Java introduction is a definite plus for GAE, and is presumably also an important internal proof point for them — a demonstration that GAE can scale and work with other languages. Also, because there are lots of languages that now target the Java virtual machine (i.e., they’ve got compilers/interpreters that produce byte code for the Java VM) — Clojure and Scala, for instance — as well as ports of other languages, like JRuby, we’ll likely see additional languages available on GAE ahead of Google’s own support for those environments.
Google also followed through on an earlier announcement, adding support for scheduld tasks (“cron”). Basically, at a scheduled time, GAE cron will invoke a URL that you specify. This is useful, but probably not everything people were hoping it would be. It’s still subject to GAE’s normal restrictions; this doesn’t let you invoke a long-running background process. It requires a shift in thinking — for instance, instead of doing the once-daily data cleanup run at 4 am, you ought to be doing cleanup throughout the day, every couple of minutes, a bit of your data set at a time.
All of that is going to be chewed over thoroughly by the press and blogosphere, and I’ve contributed my two cents to a soon-to-be-published Gartner take on the announcement and GAE itself, so now I’ll point out something that I don’t think has been widely noticed: the unladen-swallow project plan.
unladen-swallow is apparently an initiative within Google’s compiler optimization team, with a goal of achieving a 5x speed-up in CPython (i.e., the normal, mainstream, implementation of Python), starting from the 2.6 base (the current version, which is a transition point between the 2.5 used by App Engine, and the much-different Python 3.0). The developers intend to achieve this speed-up in part by moving from the existing custom VM to one built on top of LLVM. (I’ve mentioned Google’s interest in LLVM in the past.) I think this particular approach answers some of the mystery surrounding Google and Python 3.0 — this seems to indicate longer-term commitment to the existing 2.x base, while still being transition-friendly. As is typical with Google’s work with open-source code, they plan to release these changes back to the community.
All of which goes back to a point of mine earlier this week: Although programming language communities strongly resemble fandoms, languages are increasingly fungible. We’re a long way from platform maturity, too.