Spark

Professional Spark addresses the challenges in moving from proof-of-concept or demo Spark applications to live Spark in production. It covers:
Cluster Managers Performance Tuning Security Lifecycle of Jobs Shared experience about what problems are encountered while running Spark in production. Real use cases where Spark fits best. Data warehouse with Spark SQL How to schedule resources on a production cluster between Spark applications. Tips and tricks. Spark with Tachyon. The benefits of storing the the RDDs of heap. Describe the available spark db connectors. Tips and tricks, and how to use them. What are the limitations and the advantages of using spark MLlib? Spark streaming in production. What are the limitations? The problems encountered? How were they fixed? most important for a production environment : security. How to ensure security on spark (Kerberos) Spark on Yarn Spark on Mesos Spark Hardware requirements / estimating cluster size