April Presentation Night

Thank you to Thomson Reuters for sponsoring food and drink for this event!

Confirmed Feature Talks:

1. Intro to Recommendation Engines + Learning Analytics

Aaron Merlob from Silicon Valley-based learning analytics company Junyo will be talking about recommendation engines.

His talk will:

1. Give a top level overview of the various types of recommendation engines (what problems they solve, strengths/weaknesses, what type of data they require),

2. Briefly shine a light on the underlying mathematics (although no formulas will be presented to save time for code samples)

3. Bring in an example from learning analytics, demonstrating the flexibility and power of recommendation engines, and finally

4. Discuss implementation in Spark with code examples.

2. Spark meets Spring | Mark Fisher, Pivotal

Spring XD provides a unified platform for stream and batch processing with a modular and extensible architecture. It also supports a range of deployment options from single node to a standalone cluster to the cloud. While on the surface it appears that Spring XD overlaps with Spark, this presentation will emphasize how they can complement each other:

• For stream processing, developers can focus on Spark's DStream operations in those parts of a pipeline where they can benefit from the distributed processing capabilities of Spark, but then use Spring XD's DSL to connect that processing logic to a wide variety of data sources and sinks.

• For batch processing, developers likewise focus on the RDD operations, but the job itself can be orchestrated by Spring XD, and even triggered by events on streams.

This presentation will provide a quick high-level overview of Spring XD but then dive into live demos of its integration with Spark and Spark Streaming.