Spark

Learn how to use, deploy, and maintain Apache Spark with this comprehensive guide, written the creators of the open-source cluster-computing framework. With an emphasis on improvements and new features in Spark 2.0, authors Bill Chambers and Matei Zaharia break down Spark topics into distinct sections, each with unique goals."-webkit-tap-highlight-color: transparent; color: rgb(64, 64, 64); font-family: guardian-text-oreilly, Helvetica, sans-serif; font-size: 14.4px; margin-top: 1.2rem; margin-bottom: 0px; padding: 0px; box-sizing: border-box; border-width: 0px; border-style: initial; vertical-align: baseline; line-height: 1.3rem; background-color: rgb(255, 255, 255);"Youll explore the basic operations and common functions of Sparks structured APIs, as well as Structured Streaming, a new high-level API for building end-to-end streaming applications. Developers and system administrators will learn the fundamentals of monitoring, tuning, and debugging Spark, and explore machine learning techniques and scenarios for employing MLlib, Sparks scalable machine-learning library.
Get a gentle overview of big data and Spark
Learn about DataFrames, SQL, and DatasetsSparks core APIsthrough worked examples
Dive into Sparks low-level APIs, RDDs, and execution of SQL and DataFrames
Understand how Spark runs on a cluster
Debug, monitor, and tune Spark clusters and applications
Learn the power of Structured Streaming, Sparks stream-processing engine
Learn how you can apply MLlib to a variety of problems, including classification or recommendation