Learning Spark Lightning-Fast Big Data Analytics by Holden Karau, Andy Konwinski, Patrick Wendell, Matei Zaharia; O'Reilly Media

Apache Spark started as a research project at UC Berkeley in the AMPLab, which focuses on big data analytics. Spark is an open source cluster computing platform designed to be fast and general-purpose for data analytics - It's both fast to run and write. Spark provides primitives for in-memory cluster computing: your job can load data into memory and query it repeatedly much quicker than with disk-based systems like Hadoop MapReduce. Users can write applications quickly in Java, Scala or Python. In additional, it's easy to run standalone or on EC2 or Mesos. It can read data from HDFS, HBase, Cassandra, and any Hadoop data source.
If you would like a book about Spark - Learning Spark Lightning-Fast Big Data Analytics by Holden Karau, Andy Konwinski, Patrick Wendell, Matei Zaharia. It's a great book for who is interested in Spark development and starting with it. Readers will learn how to express MapReduce jobs with just a few simple lines of Spark code and more...

• Quickly dive into Spark capabilities such as collect, count, reduce, and save
• Use one programming paradigm instead of mixing and matching tools such as Hive, Hadoop, Mahout, and S4/Storm
• Learn how to run interactive, iterative, and incremental analyses
• Integrate with Scala to manipulate distributed datasets like local collections
• Tackle partitioning issues, data locality, default hash partitioning, user-defined partitioners, and custom serialization
• Use other languages by means of pipe() to achieve the equivalent of Hadoop streaming

With Early Release - 7 chapters. Explained Apache Spark overview, downloading and commands that should know, programming with RDDS (+ more advance) as well as working with Key-Value Pairs, etc. Easy to read and Good examples in a book. For people who want to learn Apache Spark or use Spark for Data Analytic. It's a book, that should keep in shelf.

Book: Learning Spark Lightning-Fast Big Data Analytics
Authors: Holden Karau, Andy Konwinski, Patrick Wendell, Matei Zaharia