Processing Big Data With Pivotal HD (Hadoop)

Course details

This comprehensive four day course will provide competent Java developers with the skills necessary to exploit the extended capabilities of Pivotal HD “The world’s most powerful Apache Hadoop distribution”. The course commences with a grounding in the relevant core technologies:

• Big fast data, NoSQL and their role in modern business applications
• Introduction to Hadoop HDFS and Map Reduce
• Using Hadoop ecosystem tools such Pig, Hive and HBase
• Overview of the Pivotal HD distribution
• Using Pivotal HAWQ

At Course Completion
By the end of the course, you should be able to meet the following objectives:

• Understanding the Hadoop and architecture
• Getting started with MapReduce to analyze large data sets&
• Practical considerations using MapReduce and Designing for MapReduce
• Initial understanding of HDFS concepts
• Advanced and practical considerations with HDFS
• Introduction to streaming MapReduce and Pig
• Overview of Hive ï‚·
• Understanding the Pivotal HD architecture 
• Getting started with HAWQ; Pivotal’s fast SQL driven and HDFS based analysis interface ï‚·
• Advanced and pragmatic considerations when using HAWQ

As a result of attending the course, the developer will be able to confiently utilize Pivotal HD, realizing the benefits of this important Hadoop distribution to deliver powerful analysis functionality of massive data with:

• The implementation of Hadoop MapReduce jobs
• The development of real-time data analysis applications with HAWQ

Course Outline

• Module 1: Course Introduction
• Module 2: Introduction to Hadoop
• Module 3: Introduction to Pivotal HD
• Module 4: Hadoop Distributed File System
• Module 5: Getting Started with Map Reduce
• Module 6: In-Depth Map Reduce
• Module 7: NOSQL Overview
• Module 8: Streaming MapReduce and Pig
• Module 9: Introduction to Hive
• Module 10: Getting Started with HAWQ
• Module 11: Working with HAWQ
• Module 12: HAWQ External Tables
• Module 13: HAWQ Practical Considerations