Learning Spark

Lightning-Fast Big Data Analysis

Nonfiction, Computers, Database Management, Data Processing, Internet, Web Development, Java, Application Software, Business Software
Cover of the book Learning Spark by Holden Karau, Andy Konwinski, Patrick  Wendell, Matei Zaharia, O'Reilly Media
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Author: Holden Karau, Andy Konwinski, Patrick Wendell, Matei Zaharia ISBN: 9781449359058
Publisher: O'Reilly Media Publication: January 28, 2015
Imprint: O'Reilly Media Language: English
Author: Holden Karau, Andy Konwinski, Patrick Wendell, Matei Zaharia
ISBN: 9781449359058
Publisher: O'Reilly Media
Publication: January 28, 2015
Imprint: O'Reilly Media
Language: English

Data in all domains is getting bigger. How can you work with it efficiently? Recently updated for Spark 1.3, this book introduces Apache Spark, the open source cluster computing system that makes data analytics fast to write and fast to run. With Spark, you can tackle big datasets quickly through simple APIs in Python, Java, and Scala. This edition includes new information on Spark SQL, Spark Streaming, setup, and Maven coordinates.

Written by the developers of Spark, this book will have data scientists and engineers up and running in no time. You’ll learn how to express parallel jobs with just a few lines of code, and cover applications from simple batch jobs to stream processing and machine learning.

  • Quickly dive into Spark capabilities such as distributed datasets, in-memory caching, and the interactive shell
  • Leverage Spark’s powerful built-in libraries, including Spark SQL, Spark Streaming, and MLlib
  • Use one programming paradigm instead of mixing and matching tools like Hive, Hadoop, Mahout, and Storm
  • Learn how to deploy interactive, batch, and streaming applications
  • Connect to data sources including HDFS, Hive, JSON, and S3
  • Master advanced topics like data partitioning and shared variables
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Data in all domains is getting bigger. How can you work with it efficiently? Recently updated for Spark 1.3, this book introduces Apache Spark, the open source cluster computing system that makes data analytics fast to write and fast to run. With Spark, you can tackle big datasets quickly through simple APIs in Python, Java, and Scala. This edition includes new information on Spark SQL, Spark Streaming, setup, and Maven coordinates.

Written by the developers of Spark, this book will have data scientists and engineers up and running in no time. You’ll learn how to express parallel jobs with just a few lines of code, and cover applications from simple batch jobs to stream processing and machine learning.

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