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Apache Spark in 24 Hours, Sams Teach Yourself

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Apache Spark in 24 Hours, Sams Teach Yourself

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  • About eBook Formats
  • This eBook includes the following formats, accessible from your Account page after purchase:

    ePub EPUB The open industry format known for its reflowable content and usability on supported mobile devices.

    MOBI MOBI The eBook format compatible with the Amazon Kindle and Amazon Kindle applications.

    Adobe Reader PDF The popular standard, used most often with the free Adobe® Reader® software.

    This eBook requires no passwords or activation to read. We customize your eBook by discreetly watermarking it with your name, making it uniquely yours.

About

Features

  • 24 one-hour lessons that take students from the absolute basics to advanced development for data manipulation and analysis
  • Covers all aspects of Spark, including basic programming, SparkSQL, SparkR, Spark Streaming, and new initiatives such as Sparkling Water
  • Shows how to build Spark applications step by step, with all sample apps available for download
  • Teaches through practical instructions, realistic examples, hands-on workshops, Q-and-As, quizzes, exercises, tips, and more

Description

  • Copyright 2017
  • Dimensions: 7" x 9-1/8"
  • Pages: 592
  • Edition: 1st
  • Book
  • ISBN-10: 0-672-33851-3
  • ISBN-13: 978-0-672-33851-9

Apache Spark is a fast, scalable, and flexible open source distributed processing engine for big data systems and is one of the most active open source big data projects to date. In just 24 lessons of one hour or less, Sams Teach Yourself Apache Spark in 24 Hours helps you build practical Big Data solutions that leverage Spark’s amazing speed, scalability, simplicity, and versatility.

This book’s straightforward, step-by-step approach shows you how to deploy, program, optimize, manage, integrate, and extend Spark–now, and for years to come. You’ll discover how to create powerful solutions encompassing cloud computing, real-time stream processing, machine learning, and more. Every lesson builds on what you’ve already learned, giving you a rock-solid foundation for real-world success.

Whether you are a data analyst, data engineer, data scientist, or data steward, learning Spark will help you to advance your career or embark on a new career in the booming area of Big Data.

Learn how to
• Discover what Apache Spark does and how it fits into the Big Data landscape
• Deploy and run Spark locally or in the cloud
• Interact with Spark from the shell
• Make the most of the Spark Cluster Architecture
• Develop Spark applications with Scala and functional Python
• Program with the Spark API, including transformations and actions
• Apply practical data engineering/analysis approaches designed for Spark
• Use Resilient Distributed Datasets (RDDs) for caching, persistence, and output
• Optimize Spark solution performance
• Use Spark with SQL (via Spark SQL) and with NoSQL (via Cassandra)
• Leverage cutting-edge functional programming techniques
• Extend Spark with streaming, R, and Sparkling Water
• Start building Spark-based machine learning and graph-processing applications
• Explore advanced messaging technologies, including Kafka
• Preview and prepare for Spark’s next generation of innovations

Instructions walk you through common questions, issues, and tasks; Q-and-As, Quizzes, and Exercises build and test your knowledge; "Did You Know?" tips offer insider advice and shortcuts; and "Watch Out!" alerts help you avoid pitfalls. By the time you're finished, you'll be comfortable using Apache Spark to solve a wide spectrum of Big Data problems.

Downloads

Downloads

Please visit the author's site for sample files and exercise data for the book.

Sample Content

Online Sample Chapter

Installing Spark

Sample Pages

Download the sample pages (includes Hour 3 and the Index.)

Table of Contents

  • PART I:  GETTING STARTED WITH APACHE SPARK
  • Hour 1:  Introducing Apache Spark    
  • Hour 2:  Understanding Hadoop    
  • Hour 3:  Installing Spark    
  • Hour 4:  Understanding the Spark Application Architecture    
  • Hour 5:  Deploying Spark in the Cloud    
  • PART II:  PROGRAMMING WITH APACHE SPARK
  • Hour 6:  Learning the Basics of Spark Programming with RDDs    
  • Hour 7:  Understanding MapReduce Concepts    
  • Hour 8:  Getting Started with Scala    
  • Hour 9:  Functional Programming with Python    
  • Hour 10:  Working with the Spark API (Transformations and Actions)    
  • Hour 11:  Using RDDs: Caching, Persistence, and Output    
  • Hour 12:  Advanced Spark Programming    
  • PART III:  EXTENSIONS TO SPARK
  • Hour 13:  Using SQL with Spark    
  • Hour 14:  Stream Processing with Spark    
  • Hour 15:  Getting Started with Spark and R    
  • Hour 16:  Machine Learning with Spark
  • Hour 17:  Introducing Sparkling Water (H20 and Spark)    
  • Hour 18:  Graph Processing with Spark    
  • Hour 19:  Using Spark with NoSQL Systems    
  • Hour 20:  Using Spark with Messaging Systems    
  • PART IV:  MANAGING SPARK
  • Hour 21:  Administering Spark    
  • Hour 22:  Monitoring Spark    
  • Hour 23:  Extending and Securing Spark    
  • Hour 24:  Improving Spark Performance    
  • Index    

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