Course Description | Course Outline | Hadoop & Accumulo Training | IT Training

Course Outline

1. Introduction

• Overview of Hadoop
• MapReduce
• Hadoop Distributed File System
• What Is Pig?
• Why Use Pig?

2. Installing and Running Pig

• Downloading and Installing Pig
• Running Pig

3. Grunt

• Interpreting Pig Latin Scripts
• HDFS Commands
• Controlling Pig

4. The Pig Data Model

• Data Types
• Schemas

5. Basic Pig Latin

• Input and Output
• Relational Operations
• User Defined Functions

6. Advanced Pig Latin

• Advanced Relational Operations
• Using Pig with Legacy Code
• Integrating Pig and MapReduce
• Nonlinear Data Flows
• Controlling Execution
• Pig Latin Preprocessor

7. Developing and Testing Scripts

• Development Tools
• Testing Your Scripts with PigUnit

8. Tuning Pig

• Improving Script Performance
• Improving Performance with User Defined Functions
• Using Compression in Intermediate Results
• Data Layout Optimization
• Handling Bad Records

9. Embedding Pig Latin in Python

• Compile
• Bind
• Run
• Utility Methods

10. Writing Evaluation and Filter Functions

• Writing an Evaluation Function in Java
• Algebraic Interface
• Accumulator Interface
• Python UDFs
• Writing Filter Functions

11. Writing Load and Store Functions

• Load Functions
• Store Functions

12. Pig and and the Rest of the Hadoop Zoo

• Pig and Hive
• Cascading
• NoSQL Databases
• Metadata in Hadoop

13. Built-in User Defined Functions and Piggybank

• Built-in UDFs
• Piggybank