Programming

Trading performance for asynchronicity

An unusual conversation came up at one of the discussion groups in the day job recently. One of the interesting things that the Javascript language specification provides is a very good description of asynchronous execution that is then embodied in execution environments like NodeJS. Asynchronicity on the JVM is  emulated by an event loop mechanism on top of the usual threaded execution environment. In general if you run JVM code in a single-thread environment bad things will happen I would prefer to do it on at least two cores.

So I made the argument that if you want asynchronous code you would be better off executing code on NodeJS rather than emulating via something like Akka.

Some of my colleagues shot back that execution on NodeJS would be inferior and I didn’t disagree. Just like Erlang sometimes you want to trade raw execution performance to get something more useful out of the execution environment.

However people felt that you would never really want to trade performance for a pure asynchronous environment, which I found very odd. Most of the apps we write in the Guardian are not that performant because they don’t really need to be. The majority of our volume is actually handled by caching and a lot of the internal workloads are handled by frameworks like Elasticsearch that we haven’t written.

In follow up discussion I realised that people hadn’t understood the fundamental advantage of asynchronous execution which is that it is easier to reason about than concurrent code. Asynchronous execution contexts on NodeJS provide a guarantee that only one scope is executing at a time so whenever you come to look at an individual function you know that scope is limited entirely the block you are looking at.

Not many programmers are good at parsing and understanding concurrent code. Having used things like Clojure I have come to the conclusion that I don’t want to do concurrency without excellent language support. In this context switching to asynchronous code can be massively helpful.

Another common situation is where you want to try and achieve data locality. With concurrent code it is really easy to actually end up with net poorly performing code due to contention on contexts. Performing a logical and cohesive unit of work is arguably a lot easier in asynchronous code blocks. It should be easier to establish a context, complete a set of operations and then throw away the whole context, knowing that you won’t need to reload that context again as the task will now be complete.

It is hard to make definite statements of what appropriate solutions are for in particular situations. I do know though that performance is a poor place to start in terms of solution design. Understanding the pros and cons of execution modes matters considerably more.

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