Hadoop Training in Harrisburg

Enroll in or hire us to teach our Hadoop class in Harrisburg, Pennsylvania by calling us @303.377.6176. Like all HSG classes, Hadoop may be offered either onsite or via instructor led virtual training. Consider looking at our public training schedule to see if it is scheduled: Public Training Classes
Provided there are enough attendees, Hadoop may be taught at one of our local training facilities.

Answers to Popular Questions:

 
Yes, this class can be tailored to meet your specific training needs.
Yes, we provide consulting services.
Yes, group discounts are provided.

Course Description

 
Implement Hadoop Solutions throughout the enterprise If you're ready to make the most out of massively scalable analytics, you need to know how to take advantage of Hadoop technologies. With this class, you'll learn how! It focuses on the architecture and approaches for building advanced, Hadoop-based enterprise applications, taking a deeper, code-level dive into delivering real-world solutions. It also walks you through the data design and how it impacts implementation. It explains how MapReduce works, and shows you how to reformulate specific business problems in MapReduce. Throughout the chapters, you'll find in-depth Java code examples that you can use, derived from applications that have been successfully built and deployed.
Course Length: 3 Days
Course Tuition: $1590 (US)

Prerequisites

Knowledge of database systems, SQL programming and a software development language is needed. Previous experience with the Java software language is required.

Course Outline

 

Chapter 1: Big Data and the Hadoop Ecosystem

Chapter 2: Storing Data in Hadoop

Chapter 3: Processing Your Data with MapReduce

Chapter 4: Customizing MapReduce Execution

Chapter 5: Building Reliable MapReduce Apps

Chapter 6: Automating Data Processing with Oozie

Chapter 7: Using Oozie

Chapter 8: Advanced Oozie FEATURES

Chapter 9: Real-Time Hadoop

Chapter 10: Hadoop Security 331A Brief History: Understanding Hadoop Security Challenges

Chapter 11: Running Hadoop Applications on AWS

Chapter 12: Building Enterprise Security Solutions for Hadoop Implementations

Chapter 13: Hadoop's Future

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