In this Spark screencast, we create a standalone Apache Spark job in Scala. In the job, we create a spark context and read a file into an RDD of strings; then apply transformations and actions to the RDD and print out the results.

In this third Spark screencast, we demonstrate more advanced use of RDD actions and transformations, as well as caching RDDs in memory.

This is our 2nd Spark screencast. In it, we take a tour of the documentation available for Spark users online.

This screencast marks the beginning of a series of hands-on screencasts we will be publishing to help new users get up and running in minutes. In this screencast, we:

1. Download and build Spark on a local machine (running OS X, but should be a similar process for Linux or Unix).
2. Introduce the API using the Spark interactive shell to explore a file.