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Index
Cover
Contents
Chapter 1: Big Data and the Hadoop Ecosystem
Big Data Meets Hadoop
The Hadoop Ecosystem
Hadoop Core Components
Hadoop Distributions
Developing Enterprise Applications with Hadoop
Summary
Chapter 2: Storing Data in Hadoop
HDFS
HBase
Combining HDFS and HBase for Effective Data Storage
Using Apache Avro
Managing Metadata with HCatalog
Choosing an Appropriate Hadoop Data Organization for Your Applications
Summary
Chapter 3: Processing Your Data with MapReduce
Getting to Know MapReduce
Your First MapReduce Application
Designing MapReduce Implementations
Summary
Chapter 4: Customizing MapReduce Execution
Controlling MapReduce Execution with InputFormat
Reading Data Your Way with Custom RecordReaders
Organizing Output Data with Custom Output Formats
Writing Data Your Way with Custom RecordWriters
Optimizing Your MapReduce Execution with a Combiner
Controlling Reducer Execution with Partitioners
Using Non-Java Code with Hadoop
Summary
Chapter 5: Building Reliable MapReduce Apps
Unit Testing MapReduce Applications
Local Application Testing with Eclipse
Using Logging for Hadoop Testing
Reporting Metrics with Job Counters
Defensive Programming in MapReduce
Summary
Chapter 6: Automating Data Processing with Oozie
Getting to Know Oozie
Oozie Workflow
Oozie Coordinator
Oozie Bundle
Oozie Parameterization with Expression Language
Oozie Job Execution Model
Accessing Oozie
Oozie SLA
Summary
Chapter 7: Using Oozie
Validating Information about Places Using Probes
Designing Place Validation Based on Probes
Designing Oozie Workflows
Implementing Oozie Workflow Applications
Implementing Workflow Activities
Implementing Oozie Coordinator Applications
Implementing Oozie Bundle Applications
Deploying, Testing, and Executing Oozie Applications
Using the Oozie Console to Get Information about Oozie Applications
Summary
Chapter 8: Advanced Oozie Features
Building Custom Oozie Workflow Actions
Adding Dynamic Execution to Oozie Workflows
Using the Oozie Java API
Using Uber Jars with Oozie Applications
Data Ingestion Conveyer
Summary
Chapter 9: Real-Time Hadoop
Real-Time Applications in the Real World
Using HBase for Implementing Real-Time Applications
Using Specialized Real-Time Hadoop Query Systems
Using Hadoop-Based Event-Processing Systems
Summary
Chapter 10: Hadoop Security
A Brief History: Understanding Hadoop Security Challenges
Authentication
Authorization
Oozie Authentication and Authorization
Network Encryption
Security Enhancements with Project Rhino
Putting it All Together — Best Practices for Securing Hadoop
Summary
Chapter 11: Running Hadoop Applications on AWS
Getting to Know AWS
Options for Running Hadoop on AWS
Understanding the EMR-Hadoop Relationship
Using AWS S3
Automating EMR Job Flow Creation and Job Execution
Orchestrating Job Execution in EMR
Summary
Chapter 12: Building Enterprise Security Solutions for Hadoop Implementations
Security Concerns for Enterprise Applications
What Hadoop Security Doesn’t Natively Provide for Enterprise Applications
Approaches for Securing Enterprise Applications Using Hadoop
Summary
Chapter 13: Hadoop’s Future
Simplifying MapReduce Programming with DSLs
Faster, More Scalable Processing
Security Enhancements
Emerging Trends
Summary
Appendix: Useful Reading
Introduction
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