Spring for Apache Hadoop - Reference Documentation

Authors

Costin Leau , Thomas Risberg , Janne Valkealahti

2.0.0.RC4-hdp21

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Table of Contents

Preface
I. Introduction
1. Requirements
2. Additional Resources
II. Spring and Hadoop
3. Hadoop Configuration, MapReduce, and Distributed Cache
3.1. Using the Spring for Apache Hadoop Namespace
3.2. Configuring Hadoop
3.3. Creating a Hadoop Job
3.3.1. Creating a Hadoop Streaming Job
3.4. Running a Hadoop Job
3.4.1. Using the Hadoop Job tasklet
3.5. Running a Hadoop Tool
3.5.1. Replacing Hadoop shell invocations with tool-runner
3.5.2. Using the Hadoop Tool tasklet
3.6. Running a Hadoop Jar
3.6.1. Using the Hadoop Jar tasklet
3.7. Configuring the Hadoop DistributedCache
3.8. Map Reduce Generic Options
4. Working with the Hadoop File System
4.1. Configuring the file-system
4.2. Using HDFS Resource Loader
4.3. Scripting the Hadoop API
4.3.1. Using scripts
4.4. Scripting implicit variables
4.4.1. Running scripts
4.4.2. Using the Scripting tasklet
4.5. File System Shell (FsShell)
4.5.1. DistCp API
5. Working with HBase
5.1. Data Access Object (DAO) Support
6. Hive integration
6.1. Starting a Hive Server
6.2. Using the Hive Thrift Client
6.3. Using the Hive JDBC Client
6.4. Running a Hive script or query
6.4.1. Using the Hive tasklet
6.5. Interacting with the Hive API
7. Pig support
7.1. Running a Pig script
7.1.1. Using the Pig tasklet
7.2. Interacting with the Pig API
8. Using the runner classes
9. Security Support
9.1. HDFS permissions
9.2. User impersonation (Kerberos)
10. Yarn Support
10.1. Using the Spring for Apache Yarn Namespace
10.2. Using the Spring for Apache Yarn JavaConfig
10.3. Configuring Yarn
10.4. Local Resources
10.5. Container Environment
10.6. Application Client
10.7. Application Master
10.8. Application Container
10.9. Application Master Services
10.9.1. Basic Concepts
10.9.2. Using JSON
10.9.3. Converters
10.10. Application Master Service
10.11. Application Master Service Client
10.12. Using Spring Batch
10.12.1. Batch Jobs
10.12.2. Partitioning
Configuring Master
Configuring Container
10.13. Using Spring Boot Application Model
10.13.1. Auto Configuration
10.13.2. Application Files
10.13.3. Application Classpath
Simple Executable Jar
Simple Zip Archive
10.13.4. Container Runners
Custom Runner
10.13.5. Resource Localizing
10.13.6. Container as POJO
10.13.7. Configuration Properties
10.13.8. Controlling Applications
Generic Usage
Using Configuration Properties
Using YarnPushApplication
Using YarnSubmitApplication
Using YarnInfoApplication
Using YarnKillApplication
11. Testing Support
11.1. Testing MapReduce
11.1.1. Mini Clusters for MapReduce
11.1.2. Configuration
11.1.3. Simplified Testing
11.1.4. Wordcount Example
11.2. Testing Yarn
11.2.1. Mini Clusters for Yarn
11.2.2. Configuration
11.2.3. Simplified Testing
11.2.4. Multi Context Example
11.3. Testing Boot Based Applications
III. Developing Spring for Apache Hadoop Applications
12. Guidance and Examples
12.1. Scheduling
12.2. Batch Job Listeners
IV. Spring for Apache Hadoop sample applications
V. Other Resources
13. Useful Links
VI. Appendices
A. Using Spring for Apache Hadoop with Amazon EMR
A.1. Start up the cluster
A.2. Open an SSH Tunnel as a SOCKS proxy
A.3. Configuring Hadoop to use a SOCKS proxy
A.4. Accessing the file-system
A.5. Shutting down the cluster
A.6. Example configuration
B. Using Spring for Apache Hadoop with EC2/Apache Whirr
B.1. Setting up the Hadoop cluster on EC2 with Apache Whirr
C. Spring for Apache Hadoop Schema