At taboola we are getting a constant feed of data (many billions of user events a day) and are using Apache Spark together with Cassandra for both real time data stream processing as well as offline data processing. We'd like to share our experience with these cutting edge technologies.

Apache Spark is an open source project - Hadoop-compatible computing engine that makes big data analysis drastically faster, through in-memory computing, and simpler to write, through easy APIs in Java, Scala and Python. This project was born as part of a PHD work in UC Berkley's AMPLab (part of the BDAS - pronounced "Bad Ass") and turned into an incubating Apache project with more active contributors than Hadoop. Surprisingly, Yahoo! are one of the biggest contributors to the project and already have large production clusters of Spark on YARN.

Spark can run either standalone cluster, or using either Apache mesos and ZooKeeper or YARN and can run side by side with Hadoop/Hive on the same data.

One of the biggest benefits of Spark is that the API is very simple and the same analytics code can be used for both streaming data and offline data processing.

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