Summer Finance Tech Coding – Neo4j, Clojure/Om and Spark
I’m playing with a number of different technologies at the moment. Mostly extensions of ideas I’ve previously blogged about.
- Timelines and Neo4j
- Specifically I’m interested in modelling the trade lifecycle in Neo4j (as discussed here) and also Skill Cloud (here) and avoiding the “current” view graphs that most applications/samples use. Primarily leveraging ES6 code with Seraph as I’m not concerned about performance for this prototype.
- There are a few interesting references documents that are worth a read:
Each relationship has a from property with a long millisecond value representing 1 January 2014, and a to property with a very large long value (End-Of-Time, or EOT, which is a magic number – in this case Long.MAX_VALUE) that effectively means there is no current upper bound to the period associated with the relationship.
- Kenny Bastani offers a number of interesting articles on graph analytics. Specifically relevant given the avoid ideas.
- Zeppelin – The video offers a good overview. Very cool web based interactive data analytics.
- Working through Advanced Analytics with Spark. Chapter 9 is of interest for obvious reasons.
- Om Next – David Nolen presentation has rekindled my interested in ClojureScript. Push Technologies offer a simple but FX bias demo of ClojureScript streaming prices – although not overly complex the demo does offer food for though with regards to Clojure in the electronic trading space. “Brandon Bloom – Building CircleCI’s Front end With Om” provide some insight into the challenges of an Om project. Deployment to production is offered by lein-ring, IDE of choice is Cursive. Clojure compiling to the JVM should avoid a degree of issues in the corporate space.