9781491912218-1491912219-Spark: The Definitive Guide: Big Data Processing Made Simple

Spark: The Definitive Guide: Big Data Processing Made Simple

ISBN-13: 9781491912218
ISBN-10: 1491912219
Edition: 1
Author: Matei Zaharia, Bill Chambers
Publication date: 2018
Publisher: O'Reilly Media
Format: Paperback 603 pages
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Book details

ISBN-13: 9781491912218
ISBN-10: 1491912219
Edition: 1
Author: Matei Zaharia, Bill Chambers
Publication date: 2018
Publisher: O'Reilly Media
Format: Paperback 603 pages

Summary

Spark: The Definitive Guide: Big Data Processing Made Simple (ISBN-13: 9781491912218 and ISBN-10: 1491912219), written by authors Matei Zaharia, Bill Chambers, was published by O'Reilly Media in 2018. With an overall rating of 4.0 stars, it's a notable title among other Computer Science (Data Modeling & Design, Databases & Big Data, Data Mining, Data Processing, Java, Programming Languages) books. You can easily purchase or rent Spark: The Definitive Guide: Big Data Processing Made Simple (Paperback, Used) from BooksRun, along with many other new and used Computer Science books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $17.25.

Description

Learn how to use, deploy, and maintain Apache Spark with this comprehensive guide, written by 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.

You’ll explore 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. Developers and system administrators will learn the fundamentals of monitoring, tuning, and debugging Spark, and explore machine learning techniques and scenarios for employing MLlib, Spark’s scalable machine-learning library.

  • 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
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