Introduction to MapReduce training for beginners in Basel | Map Reduce Training for Beginners | Advanced MapReduce Training

Introduction to MapReduce training for beginners in Basel | Map Reduce Training for Beginners | Advanced MapReduce Training
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Wed 18 September 2019
Wednesday 18 September 2019
3:30 AM - 5:30 AM
Ended


In this course we will introduce you to distributed data processing, how to use MapReduce to process large amounts of data. This course is focused on providing practical hands-on exercises. Students will learn to write MapReduce programs. Advanced Features of MapReduce will be covered as well. 

Course Schedule

Prerequisite

Desired but not required - Exposure to, Working proficiency of Java, sql.

 

Course Features

  • 4 weeks, 8 sessions, 16 hours of total LIVE Instruction
  • Training material, instructor handouts and access to useful resources on the cloud provided
  • Practical Hands on Lab exercises on cloud workstations provided
  • Actual code and scripts provided
  • Real-life Scenarios

Course Outline

1. Introduction to MapReduce

  • MapReduce Overview
  • MapReduce in Hadoop
  • History of MapReduce
  • MapReduce applications
  • Data Flow in MapReduce
  • Map and Reduce operations
  • Job submission flow of MapReduce
  • Map Operation
  • Job Initialization
  • Task Assignment
  • Job Completion
  • Job Scheduling
  • Job Failures
  • Shuffle and sort
  • Word Count Problem, Flow and Solution
  • MapReduce Algorithms

2. Map Reduce Types and Formats

  • Data Types
  • File Formats
  • Input Formats
  • Output Formats
  • Explain the Driver, Mapper and Reducer code
  • Configuring development environment - Eclipse
  • Writing Unit Test
  • Running locally
  • Running on Cluster

3. Understanding MapReduce

  • Data Flow in MapReduce
  • MapReduce example
  • MapReduce Daemons
  • Job tracker
  • Task Tracker
  • Other phases in MapReduce
  • Data Flow in single, multiple and no reduce task

4. MapReduce with YARN

  • Hadoop Architecture
  • Problem with Hadoop 1.x, Hadoop 2.x features,
  • YARN MapReduce Application Execution Flow
  • YARN Workflow
  • Anatomy of MapReduce Program

5. Advanced MapReduce

  • Counters
  • Sorting
  • Input Splits in MapReduce
  • MapReduce Combiner
  • MapReduce Partitioner
  • MapReduce Distributed Cache
  • MRunit
  • Reduce Join
  • Joins - Map Side and Reduce Side
  • Custom Input Format
  • Sequence Input Format
  • Side Data Distribution

Refund Policy

  • There are no Refunds. All Sales is final.




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Entirety Technology
Basel, Switzerland

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