
Programming Elastic MapReduce
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Content
- Intro
- Copyright
- Table of Contents
- Preface
- What Is AWS?
- What's in This Book?
- Sign Up for AWS
- Code Samples in This Book
- Conventions Used in This Book
- Using Code Examples
- Safari® Books Online
- How to Contact Us
- Acknowledgments
- Chapter 1. Introduction to Amazon Elastic MapReduce
- Amazon Web Services Used in This Book
- Amazon Elastic MapReduce
- Amazon EMR and the Hadoop Ecosystem
- Amazon Elastic MapReduce Versus Traditional Hadoop Installs
- Data Locality
- Hardware
- Complexity
- Application Building Blocks
- Chapter 2. Data Collection and Data Analysis with AWS
- Log Analysis Application
- Log Messages as a Data Set for Analytics
- Understanding MapReduce
- Collection Stage
- Simulating Syslog Data
- Generating Logs with Bash
- Moving Data to S3 Storage
- All Roads Lead to S3
- Developing a MapReduce Application
- Custom JAR MapReduce Job
- Running an Amazon EMR Cluster
- Viewing Our Results
- Debugging a Job Flow
- Running Our Job Flow with Debugging
- Reviewing Job Flow Log Structure
- Debug Through the Amazon EMR Console
- Our Application and Real-World Uses
- Chapter 3. Data Filtering Design Patterns and Scheduling Work
- Extending the Application Example
- Understanding Web Server Logs
- Finding Errors in the Web Logs Using Data Filtering
- Mapper Code
- Reducer Code
- Driver Code
- Running the MapReduce Filter Job
- Analyzing the Results
- Building Summary Counts in Data Sets
- Mapper Code
- Reducer Code
- Analyzing the Filtered Counts Job
- Job Flow Scheduling
- Scheduling with the CLI
- Scheduling with AWS Data Pipeline
- Creating a Pipeline
- Adding Data Nodes
- Adding Activities
- Scheduling Pipelines
- Reviewing Pipeline Status
- AWS Pipeline Costs
- Real-World Uses
- Chapter 4. Data Analysis with Hive and Pig in Amazon EMR
- Amazon Job Flow Technologies
- What Is Pig?
- Utilizing Pig in Amazon EMR
- Connecting to the Master Node
- Pig Latin Primer
- Exploring Data with Pig Latin
- Running Pig Scripts in Amazon EMR
- What Is Hive?
- Utilizing Hive in Amazon EMR
- Hive Primer
- Exploring Data with Hive
- Running Hive Scripts in Amazon EMR
- Finding the Top 10 with Hive
- Our Application with Hive and Pig
- Chapter 5. Machine Learning Using EMR
- A Quick Tour of Machine Learning
- Python and EMR
- Why Python?
- The Input Data
- The Mapper
- The Reducer
- Putting It All Together
- What About Java?
- What's Next?
- Chapter 6. Planning AWS Projects and Managing Costs
- Developing a Project Cost Model
- Software Licensing
- AWS and Cloud Licensing
- Private Data Center and AWS Cost Comparisons
- Cost Calculations on an Example Application
- Optimizing AWS Resources to Reduce Project Costs
- Amazon Regions
- Amazon Availability Zones
- EC2 and EMR Costs with On Demand, Reserve, and Spot Instances
- Reserve Instances
- Spot Instances
- Reducing AWS Project Costs
- Amazon Tools for Estimating Your Project Costs
- Appendix A. Amazon Web Services Resources and Tools
- Amazon AWS Online Resources
- Amazon AWS Cost Estimation Tools
- AWS Best Practices and Architecture
- Amazon EMR Distributions
- Appendix B. Cloud Computing, Amazon Web Services, and Their Impacts
- AWS Service Delivery Models
- Platform as a Service
- Infrastructure as a Service
- Storage as a Service
- Performance
- Elasticity and Growth
- Fixed Capacity
- Variable Capacity
- Security
- Security Is a Shared Responsibility
- Data Security in Elastic MapReduce
- Uptime and Availability
- Appendix C. Installation and Setup
- Prerequisites
- Installing Hadoop
- Building MapReduce Applications
- Running MapReduce Applications Locally
- Installing Pig
- Installing Hive
- Index
- About the Authors
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