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Learning Spark .pdf 2015出版 高清
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Learning Spark by Holden Karau, Andy Konwinski, Patrick Wendell, and Matei Zaharia Copyright © 2015 Databricks. All rights reserved
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PROGRAMMING LANGUAGES/SPARK
Learning Spark
ISBN: 978-1-449-35862-4
US $39.99 CAN $ 45.99
“
Learning Spark is at the
top of my list for anyone
needing a gentle guide
to the most popular
framework for building
big data applications.
”
—Ben Lorica
Chief Data Scientist, O’Reilly Media
Twitter: @oreillymedia
facebook.com/oreilly
Data in all domains is getting bigger. How can you work with it efficiently?
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.
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
Holden Karau, a software development engineer at Databricks, is active in open
source and the author of Fast Data Processing with Spark (Packt Publishing).
Andy Konwinski, co-founder of Databricks, is a committer on Apache Spark and
co-creator of the Apache Mesos project.
Patrick Wendell is a co-founder of Databricks and a committer on Apache Spark.
He also maintains several subsystems of Spark’s core engine.
Matei Zaharia, CTO at Databricks, is the creator of Apache Spark and serves as
its Vice President at Apache.
Learning Spark
Karau, Konwinski,
Wendell & Zaharia
Holden Karau, Andy Konwinski,
Patrick Wendell & Matei Zaharia
L e a r n i n g
Spark
LIGHTNING-FAST DATA ANALYSIS
PROGRAMMING LANGUAGES/SPARK
Learning Spark
ISBN: 978-1-449-35862-4
US $39.99 CAN $45.99
“
Learning Spark is at the
top of my list for anyone
needing a gentle guide
to the most popular
framework for building
big data applications.
”
—Ben Lorica
Chief Data Scientist, O’Reilly Media
Twitter: @oreillymedia
facebook.com/oreilly
Data in all domains is getting bigger. How can you work with it efficiently?
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.
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
Holden Karau, a software development engineer at Databricks, is active in open
source and the author of Fast Data Processing with Spark (Packt Publishing).
Andy Konwinski, co-founder of Databricks, is a committer on Apache Spark and
co-creator of the Apache Mesos project.
Patrick Wendell is a co-founder of Databricks and a committer on Apache Spark.
He also maintains several subsystems of Spark’s core engine.
Matei Zaharia, CTO at Databricks, is the creator of Apache Spark and serves as
its Vice President at Apache.
Learning Spark
Karau, Konwinski,
Wendell & Zaharia
Holden Karau, Andy Konwinski,
Patrick Wendell & Matei Zaharia
L e a r n i n g
Spark
LIGHTNING-FAST DATA ANALYSIS
Holden Karau, Andy Konwinski, Patrick Wendell, and
Matei Zaharia
Learning Spark
978-1-449-35862-4
[LSI]
Learning Spark
by Holden Karau, Andy Konwinski, Patrick Wendell, and Matei Zaharia
Copyright © 2015 Databricks. All rights reserved.
Printed in the United States of America.
Published by O’Reilly Media, Inc., 1005 Gravenstein Highway North, Sebastopol, CA 95472.
O’Reilly books may be purchased for educational, business, or sales promotional use. Online editions are
also available for most titles (http://safaribooksonline.com). For more information, contact our corporate/
institutional sales department: 800-998-9938 or corporate@oreilly.com.
Editors: Ann Spencer and Marie Beaugureau
Production Editor: Kara Ebrahim
Copyeditor: Rachel Monaghan
Proofreader: Charles Roumeliotis
Indexer: Ellen Troutman
Interior Designer: David Futato
Cover Designer: Ellie Volckhausen
Illustrator: Rebecca Demarest
February 2015: First Edition
Revision History for the First Edition
2015-01-26: First Release
See http://oreilly.com/catalog/errata.csp?isbn=9781449358624 for release details.
The O’Reilly logo is a registered trademark of O’Reilly Media, Inc. Learning Spark, the cover image of a
small-spotted catshark, and related trade dress are trademarks of O’Reilly Media, Inc.
While the publisher and the authors have used good faith efforts to ensure that the information and
instructions contained in this work are accurate, the publisher and the authors disclaim all responsibility
for errors or omissions, including without limitation responsibility for damages resulting from the use of
or reliance on this work. Use of the information and instructions contained in this work is at your own
risk. If any code samples or other technology this work contains or describes is subject to open source
licenses or the intellectual property rights of others, it is your responsibility to ensure that your use
thereof complies with such licenses and/or rights.
Table of Contents
Foreword. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix
Preface. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xi
1. Introduction to Data Analysis with Spark. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
What Is Apache Spark? 1
A Unified Stack 2
Spark Core 3
Spark SQL 3
Spark Streaming 3
MLlib 4
GraphX 4
Cluster Managers 4
Who Uses Spark, and for What? 4
Data Science Tasks 5
Data Processing Applications 6
A Brief History of Spark 6
Spark Versions and Releases 7
Storage Layers for Spark 7
2. Downloading Spark and Getting Started. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
Downloading Spark 9
Introduction to Spark’s Python and Scala Shells 11
Introduction to Core Spark Concepts 14
Standalone Applications 17
Initializing a SparkContext 17
Building Standalone Applications 18
Conclusion 21
iii
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