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Spark: the Definitive Guide by Bill Chambers

Spark: the Definitive Guide

Big Data Processing Made Simple

Bill Chambers, Matei Zaharia

O'Reilly Media · Print & ebook · April 3, 2018

Learn how to use, deploy, and maintain Apache Spark with this comprehensive guide, written by the creators of the open-source cluster-computing framework.

Machine LearningData MiningCloud Computing
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Who it’s for
A practical guide to Spark’s APIs, cluster operations, streaming, and machine learning.
Themes
Big data processing, Stream processing, Machine learning
Genres
Data Mining, Machine Learning, Cloud Computing

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About this book

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. Youâ??ll explore the basic operations and common functions of Sparkâ??

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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, Sparkâ??s scalable machine-learning library. - Get a gentle overview of big data and Spark - Learn about DataFrames, SQL, and Datasetsâ??Sparkâ??s core APIsâ??through worked examples - Dive into Sparkâ??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, Sparkâ??s stream-processing engine - Learn how you can apply MLlib to a variety of problems, including classification or recommendation

Spark, Under the Hood

A practical guide to Spark’s APIs, cluster operations, streaming, and machine learning.

Come here for

  • Work through DataFrames, SQL, Datasets, and RDDs with examples
  • Connect application code to the realities of running a cluster

Expect

  • A broad path from Spark fundamentals to monitoring, tuning, and debugging
  • Technical guidance for developers and system administrators

Where it sits

Machine Learning65%
Cloud Computing40%
Data Mining26%

Percentages are BookFrontier’s reading of the book.

Publisher categories

  • Data Science
  • Data Mining
  • Java Programming
  • Python Programming
Show all 6 publisher categories
  • Computer Engineering
  • Data Modeling
Authors
Bill Chambers, Matei Zaharia
Publisher
O'Reilly Media
Published
April 3, 2018
Format
Print & ebook
Theme
Big data processing · Stream processing · Machine learning
Reading lane
Data Science