Developing Apache Hadoop 2.0 Solutions for Data Analysts

Course Overview

This 4-day hands-on training course teaches students how to develop applications and analyze Big Data stored in Apache™ Hadoop© 2.0 using Apache Pig and Apache Hive. Students will learn the details of Hadoop 2.0, YARN, the Hadoop Distributed File System (HDFS), an overview of MapReduce, and a deep dive into using Pig and Hive to perform data analytics on Big Data, including finding trends and detecting patterns.


Students should be familiar with SQL and have a minimal understanding of programming principles. No prior Hadoop knowledge is required.

Target Audience

Data Analysts, BI Analysts, BI Developers, SAS Developers and other types of analysts who need to answer questions and analyze Big Data stored in a Hadoop cluster.

Course Objectives

At the completion of the course students will be able to:

  • Explain Hadoop 2.0 and YARN
  • Explain how HDFS Federation works in Hadoop 2.0
  • Explain the various tools and frameworks in the Hadoop 2.0 ecosystem
  • Explain the architecture of the Hadoop Distributed File System (HDFS)
  • Use the Hadoop client to input data into HDFS
  • Explain the architecture of MapReduce
  • Run a MapReduce job on Hadoop
  • Use Sqoop to transfer data between Hadoop and a relational database
  • Write a Pig script to explore and transform data in HDFS
  • Define advanced Pig relations
  • Use Pig to apply structure to unstructured Big Data
  • Invoke a Pig User-Defined Function
  • Write a Hive query
  • Understand how Hive tables are defined and implemented
  • Use Hive to run SQL-like queries to perform data analysis
  • Perform a multi-table select in Hive
  • Design a proper schema for Hive
  • Explain the uses and purpose of HCatalog
  • Use HCatalog with Pig and Hive
  • Use Pig to organize and analyze Big Data
  • Define a workflow using Oozie


Day 1
  • Understanding Hadoop 2.0 and YARN
  • The Hadoop Distributed File System (HDFS)
  • Inputting Data into HDFS
  • The MapReduce Framework
Day 2
  • Introduction to Pig
  • Advanced Pig Programming
Day 3
  • Hive Programming
  • Using HCatalog
Day 4
  • Advanced Hive Programming
  • Data Analysis and Statistics
  • Defining Workflow with Oozie

Lab Content

Students will work through the following lab exercises using the Hortonworks Data Platform 2.0:

  • Using HDFS commands
  • Using Sqoop to transfer data between HDFS and a RDBMS
  • Running a MapReduce job
  • Monitoring a MapReduce job
  • Exploring data with Pig
  • Splitting a dataset with Pig
  • Joining datasets with Pig
  • Using Pig to prepare data for Hive
  • Understanding Hive tables
  • Analyzing Big Data with Hive
  • Understanding MapReduce in Hive
  • Joining datasets with Hive
  • A Multi-table select with Hive
  • Streaming data with Hive and Python
  • Using HCatalog with Pig
  • Computing Quantiles with Pig
  • Computing ngrams with Hive
  • Defining Workflow with Oozie


  • $2795
  • Students who complete a paid reservation at least two weeks prior to the start of the course will enjoy a 10% discount
  • Note that discounts cannot be combined
Please contact us for any questions on Apache Hadoop training courses or would like to discuss a custom, on-site training course.


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