Apache Spark I: From Scala Collections to Fast Interactive Big Data with Spark by Evan Chan.
Description:
This session introduces you to Spark by starting with something basic: Scala collections and functional data transforms. We then look at how Spark expands the functional collection concept to enable massively distributed, fast computations. The second half of the talk is for those of you who want to know the secrets to make Spark really fly for querying tabular datasets. We will dive into row vs columnar datastores and the facilities that Spark has for enabling interactive data analysis, including Spark SQL and the in-memory columnar cache. Learn why Scala’s functional collections are the best foundation for working with data!
Apache Spark II: Streaming Big Data Analytics with Team Apache, Scala & Akka by Helena Edelson.
Description:
In this talk we will step into Spark over Cassandra with Spark Streaming and Kafka. Then put it in the context of an event-driven Akka application for real-time delivery of meaning at high velocity. We will do this by showing how to easily integrate Apache Spark and Spark Streaming with Apache Cassandra and Apache Kafka using the Spark Cassandra Connector. All within a common use case: working with time-series data, which Cassandra excells at for data locality and speed.
Back to back excellent presentations on Spark!
I need to replace my second monitor (died last week) so I can run the video at full screen with a REPL open!
Enjoy!