Hadoop 2 Quick-Start Guide

Learn the Essentials of Big Data Computing in the Apache Hadoop 2 Ecosystem

Nonfiction, Computers, Database Management, Internet
Cover of the book Hadoop 2 Quick-Start Guide by Douglas Eadline, Pearson Education
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Author: Douglas Eadline ISBN: 9780134049991
Publisher: Pearson Education Publication: October 28, 2015
Imprint: Addison-Wesley Professional Language: English
Author: Douglas Eadline
ISBN: 9780134049991
Publisher: Pearson Education
Publication: October 28, 2015
Imprint: Addison-Wesley Professional
Language: English

Get Started Fast with Apache Hadoop® 2, YARN, and Today’s Hadoop Ecosystem

 

With Hadoop 2.x and YARN, Hadoop moves beyond MapReduce to become practical for virtually any type of data processing. Hadoop 2.x and the Data Lake concept represent a radical shift away from conventional approaches to data usage and storage. Hadoop 2.x installations offer unmatched scalability and breakthrough extensibility that supports new and existing Big Data analytics processing methods and models.

 

Hadoop® 2 Quick-Start Guide is the first easy, accessible guide to Apache Hadoop 2.x, YARN, and the modern Hadoop ecosystem. Building on his unsurpassed experience teaching Hadoop and Big Data, author Douglas Eadline covers all the basics you need to know to install and use Hadoop 2 on personal computers or servers, and to navigate the powerful technologies that complement it.

 

Eadline concisely introduces and explains every key Hadoop 2 concept, tool, and service, illustrating each with a simple “beginning-to-end” example and identifying trustworthy, up-to-date resources for learning more.

 

This guide is ideal if you want to learn about Hadoop 2 without getting mired in technical details. Douglas Eadline will bring you up to speed quickly, whether you’re a user, admin, devops specialist, programmer, architect, analyst, or data scientist.

 

Coverage Includes

  • Understanding what Hadoop 2 and YARN do, and how they improve on Hadoop 1 with MapReduce
  • Understanding Hadoop-based Data Lakes versus RDBMS Data Warehouses
  • Installing Hadoop 2 and core services on Linux machines, virtualized sandboxes, or clusters
  • Exploring the Hadoop Distributed File System (HDFS)
  • Understanding the essentials of MapReduce and YARN application programming
  • Simplifying programming and data movement with Apache Pig, Hive, Sqoop, Flume, Oozie, and HBase
  • Observing application progress, controlling jobs, and managing workflows
  • Managing Hadoop efficiently with Apache Ambari–including recipes for HDFS to NFSv3 gateway, HDFS snapshots, and YARN configuration
  • Learning basic Hadoop 2 troubleshooting, and installing Apache Hue and Apache Spark

 

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Get Started Fast with Apache Hadoop® 2, YARN, and Today’s Hadoop Ecosystem

 

With Hadoop 2.x and YARN, Hadoop moves beyond MapReduce to become practical for virtually any type of data processing. Hadoop 2.x and the Data Lake concept represent a radical shift away from conventional approaches to data usage and storage. Hadoop 2.x installations offer unmatched scalability and breakthrough extensibility that supports new and existing Big Data analytics processing methods and models.

 

Hadoop® 2 Quick-Start Guide is the first easy, accessible guide to Apache Hadoop 2.x, YARN, and the modern Hadoop ecosystem. Building on his unsurpassed experience teaching Hadoop and Big Data, author Douglas Eadline covers all the basics you need to know to install and use Hadoop 2 on personal computers or servers, and to navigate the powerful technologies that complement it.

 

Eadline concisely introduces and explains every key Hadoop 2 concept, tool, and service, illustrating each with a simple “beginning-to-end” example and identifying trustworthy, up-to-date resources for learning more.

 

This guide is ideal if you want to learn about Hadoop 2 without getting mired in technical details. Douglas Eadline will bring you up to speed quickly, whether you’re a user, admin, devops specialist, programmer, architect, analyst, or data scientist.

 

Coverage Includes

 

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