AWS Lambda, Clojure and ClojureScript


In case you’re not familiar with them, AWS Lambdas are a fascinating idea - they are server functions you can create and run without first provisioning servers: you write your code, upload it, and pay only for the time that is executed.

There’s only one (somewhat minor) catch: given that there is no provisioned server capacity at all, the first time that you execute a lambda it has to be warmed up. The code stays live for a period of time after the first execution, but given Clojure’s start up time cost, I was wondering what effect that would have on a Clojure lambda.

ClojureScript performance revisited


At the recent Thingmonk conference in London, I got to chatting about Clojure and ClojureScript. It’s an IoT event, so it was to be expected that the topic of performance on devices like the Tessel or Raspberry Pi would come up.

That got me thinking about the piece I wrote back in January about ClojureScript performance for Processing sketches. How much has ClojureScript performance improved since?

Let’s find out.

Tropology performance: PostgreSQL vs Neo4j

Or, apples vs. papaya salad.

Short version: I’ve moved Tropology to PostgreSQL for performance reasons, and because after some evaluation, Neo4j wasn’t as good a fit as it seemed at first blush.

You may want to start by catching up with the other Tropology articles.

All done?

Visualizing TVTropes - Part 4: Merges

Episode IV: A new approach

We got better performance with the last changes I made to the import process, at the cost of parallelization and a significantly less clean Clojure codebase.

As I was going about wrapping them up, I got a recommendation from Michael Hunger. Summarized:

  • Don’t use the batch REST API
  • The Cypher query endpoint is outdated
  • Try merges

Well then. So much for that feature branch.

Visualizing TVTropes - Part 3: Proper batching

The story so far

Yesterday we were discussing our (admittedly) somewhat ghetto, not-quite-batched Neo4j implementation.

The long and short of it is that I was initially attacking the import process as one would on a JDBC client for a relational database. Query for these values here, create those if some don’t exist, insert relationships here, etc.

That seems to be woefully inefficient in Neo4j.

Visualizing TVTropes - Part 2: Neo4j optimizations

Welcome. You may want to first catch up on Part 1 of this little experiment.

All done? OK then.

ClojureScript vs. CoffeeScript for Processing sketches

DECEMBER 2015 UPDATE: I’ve run some tests with the latest ClojureScript and made some minor changes to the code, which significantly improved performance. Read this post for updated numbers. Keeping this post around for archival reasons.

The set up

This whole thing started not as a performance test, but as me experimenting with ClojureScript and Quil while reading Matt Pearson’s Generative Art. As such, it is not the most scientific of comparisons, and instead born out of my notes when exploring how to do sketches with ClojureScript for the web.

Consider the following example: