The creators of the Apache Spark cluster computing framework have written this book showing how to use, deploy, and maintain Apache Spark. 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. Topics covered start from the basic operations and common functions of Spark’s structured APIs, as well as Structured Streaming, a new high-level API for building end-to-end streaming applications.

<ASIN:1491912219>

The book also covers the fundamentals of monitoring, tuning, and debugging Spark, as well as machine learning techniques and scenarios for employing MLlib, Spark’s scalable machine-learning library.

Author: Bill Chambers and Matei Zaharia
Publisher: O'Reilly
Date: March 2018
Pages: 608
ISBN: 978-491912218
Print: 1491912219
Kindle: B079P71JHY
Audience: developers wanting to use Spark
Level: intermediate
Category: Data Science 

• Get a gentle overview of big data and Spark
• Learn about DataFrames, SQL, and Datasets—Spark’s core APIs—through worked examples
• Dive into Spark’s 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, Spark’s stream-processing engine
• Learn how you can apply MLlib to a variety of problems, including classification or recommendation

For recommendations of Big Data books see Reading Your Way Into Big Data in our Programmer's Bookshelf section.

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