MapReduce Online Training

MapReduce Online Training

hadoop map reduce online-training

About MapReduce Online Training

MapReduce is a programming model used in Hadoop to allow massive scalability across thousands of servers in a Hadoop cluster. MapReduce generates and processes Big data on a cluster of computers using a parallel, distributed algorithm, providing for fault tolerance. It is one of the Core components of Apache Hadoop framework. It works with two basic procedures: mapping and reducing. First it maps the data, filtering and sorting it, splitting into key/value pairs. Then, the Reduce operation takes place and combining the pairs into smaller ones to provide meaningful output. It helps how to manage jobs with the Hadoop CLI and monitor them with MCS.

Course Objectives

MapReduce Course Objectives

After completion of the MapReduce Course at Naresh I Technologies, you will be expertise and eligible for:

  • Complete knowledge of  MapReduce component in Hadoop
  • Able to work on MapReduce related Project independently
  • Setup/Install/Configure MapReduce in Dev/Support/Test environment
  • Understand architecture of MapReduce and various operations performed on it
  • Familiar with standard solutions

Who should go for this course

  • Any IT experienced Professional who is interested to work on IT job related to Data Science, Bigdata, Hadoop, etc.
  • Any B.E/ B.Tech/ BSC/ MCA/ M.Sc Computers/ M.Tech/ BCA/ BCom College Students in any stream.
  • Fresh Graduates.

Pre-requisites

The course can learn by any IT professional having basic knowledge of:

  • Unix/Linux Operating System
  • Core Java
  • Database concepts of SQL

Course Curriculum

  • Hadoop vs RDBMS
  • Core components of Hadoop
  • Hadoop Distributed File System
  • HDFS Architecture and MapReduce
  • MapReduce in Hadoop
  • History of MapReduce
  • MapReduce applications
  • Data Flow in MapReduce
  • Map and Reduce operations
  • Job submission flow of MapReduce
  • Data Flow in MapReduce
  • MapReduce example
  • MapReduce Daemons
  • Job tracker
  • Task Tracker
  • Other phases in Map Reduce
  • Data Flow in single, multiple and no reduce task
  • Hadoop 1.x architecture
  • Problem with Hadoop 1.x, Hadoop 2.x features,
  • YARN MR Application Execution Flow
  • YARN Workflow
  • Anatomy of MapReduce Program
  • Input Splits in MapReduce
  • Combiner
  • Partitioner
  • Demos on MapReduce
  • Counters
  • Distributed Cache
  • MRunit
  • Reduce Join
  • Custom Input Format
  • Sequence Input Format


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Training Features

Instructor-Led Training Sessions

We believe to provide our students the Best interactive experience as part of their learning

Expert Trainers

We Constantly evaluate our trainers and only the “Best” Provides the Training

Flexible Schedule

Do not hesitate to ask… because we will work according to your calendar

Industry Specific Scenarios

Students are provided with all the Real-Time and Relevant Scenarios

e-Learning Sessions

Online training sessions are held Live and we provide students with the Training Videos

24/7 Support

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