Understand the value of big data and how Hadoop can
help manage it. Navigate the Hadoop 2 ecosystem and create clusters. Use
applications for data mining, problem-solving, analytics, and Moore
DETAIL
- Author: Dirk deRoos, Paul C. Zikopoulos, Roman B. Melnyk, PhD, Bruce Brown, and Rafael Coss·
- Language: English
- Published: 2014
- Page: 411
- Size: 4 MB
- Format: pdf
CONTENTS
Introduction
Part I: Getting Started with Hadoop
Chapter
1: Introducing Hadoop and Seeing What It’s Good For
Chapter
2: Common Use Cases for Big Data in Hadoop
Chapter
3: Setting Up Your Hadoop Environment
Part II: How Hadoop Works
Chapter
4: Storing Data in Hadoop: The Hadoop Distributed File System
Chapter
5: Reading and Writing Data
Chapter
6: MapReduce Programming
Chapter
7: Frameworks for Processing Data in Hadoop:
YARN and MapReduce
Chapter
8: Pig: Hadoop Programming Made Easier
Chapter
9: Statistical Analysis in Hadoop
Chapter
10: Developing and Scheduling Application Workflows with Oozie
Part III: Hadoop and Structured Data
Chapter
11: Hadoop and the Data Warehouse: Friends or Foes?
Chapter
12: Extremely Big Tables: Storing Data in HBase
Chapter
13: Applying Structure to Hadoop Data with Hive
Chapter
14: Integrating Hadoop with Relational Databases Using Sqoop
Chapter
15: The Holy Grail: Native SQL Access to Hadoop Data
Part IV: Administering and Configuring Hadoop
Chapter
16: Deploying Hadoop
Chapter
17: Administering Your Hadoop Cluster
Part V: The Part of Tens
Chapter
18: Ten Hadoop Resources Worthy of a Bookmark
Chapter
19: Ten Reasons to Adopt Hadoop
Index
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