Spark 101

Abstract: Spark has gained a lot of traction lately. It is an in-memory distributed computing framework that can be 10-100x faster than traditional MapReduce for certain applications. In this talk, we will focus on the core Spark concepts like RDDs, transformation against RDDs, and how RDDs are partitioned across multiple nodes. We will also talk about topics related to the Spark job life cycle like the job scheduler, job optimization, and failure handling.

Speaker: Danish Shrestha is a Sr. Big Data Software engineer at Windlogics. He has been working with big data-related technologies for a few years now. His work has been mainly focused around Hadoop, Spark, Cassandra, HBase and MongoDB. He has a masters in Computer Science from the University of Illinois, Urbana-Champaign.

Parking: Parking is free for the summer in the Anderson Parking Ramp.

Food: Pizza and drinks, first come first serve, starting at 6:30PM provided by Thomson Reuters.

Map: http://bit.ly/RCtaTI