Overview of Course

Our MapReduce Training course is designed to help you master the concepts of MapReduce and its implementation using Hadoop. The course provides hands-on experience in developing MapReduce programs, deploying them on Hadoop clusters, and working with big data. You will learn how to write efficient MapReduce programs in Java, and how to use Hadoop to manage large-scale data processing. 

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Course Highlights

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Comprehensive coverage of MapReduce and Hadoop

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Hands-on experience in developing MapReduce programs

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Practical implementation of MapReduce on Hadoop clusters

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    Real-world Projects

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Skills You’ll Learn


MapReduce programming model


Developing MapReduce programs in Java


Managing large-scale data processing using Hadoop


MapReduce design patterns


Optimization techniques for MapReduce programs


Debugging MapReduce programs


Working with big data

Training Options

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1-on-1 Training

On Request
  • Option Item Access to live online classes
  • Option Item Flexible schedule including weekends
  • Option Item Hands-on exercises with virtual labs
  • Option Item Session recordings and learning courseware included
  • Option Item 24X7 learner support and assistance
  • Option Item Book a free demo before you commit!
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Corporate Training

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  • Option Item Everything in 1-on-1 Training plus
  • Option Item Custom Curriculum
  • Option Item Extended access to virtual labs
  • Option Item Detailed reporting of every candidate
  • Option Item Projects and assessments
  • Option Item Consulting Support
  • Option Item Training aligned to business outcomes
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Course Reviews


  • Object
  • Class
  • Attributes
  • Inheritance
  • Aspects of Java

  • Java-Eclipse.
  • How to Create New Java project
  • How to create New Java Class
  • Hello World program
  • How to run this program
  • Types of integer
  • Class creation & name given
  • Create object
  • Creation of package

  • Sub-class & super Class
  • Map-Reducing in Inheritance

  • What is the method of overloading
  • overloading modify
  • Difference between overloading & overriding
  • Method of overriding

  • Basic concept of abstract
  • Abstract class demo
  • Class extends
  • Difference between Abstract & concrete class
  • Implementation of abstract class in Java
  • Difference between JRE & JBM

  • Word count example
  • Exception
  • Tool runner
  • Mapper
  • Map method
  • Sum reducer

  • Introduction and characteristics of big data
  • Introduction of Hadoop and its work
  • What is HDFS and its explanation with example
  • Introduction to Map Reduce?
  • What is Map Phase?
  • What is Reduce Phase?

  • Introduction to Hadoop ecosystem
  • How Hadoop solve problems of typical distributed system
  • What is Sqoop and its working
  • What is Qozie and its working
  • What is Pig and its working
  • What is Flume and its working
  • What is Hive and its working
  • HDFS Storage Mechanism
  • How files are Stored / Read / Written in HDFS
  • Understanding Demons

  • Hadoop installation
  • Introduction to Mapreduce and HDFS

  • MapReduce job Execution
  • MapReduce Combiner
  • MapreducePartitioner
  • Shuffle & Sort Phase
  • Map Reduce in detail
  • Comparison b/w YARN and MRV1
  • Cloudera Developer Certification Overview
  • Hands on Exercises on Map Reduce
  • Introduction to Mapper, Box classes and Reducer
  • Input Formats and Output Formats
  • How to filter File Inputs
  • How to work on amazon cluster
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Target Audience:

  • Developers who want to learn MapReduce and Hadoop
  • Data analysts and data scientists who want to work with big data
  • IT professionals who want to develop skills in big data processing
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  • Basic programming skills in Java
  • Familiarity with Linux command line interface
  • Understanding of basic data processing concepts

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Benefits of the course:

  • Develop skills in big data processing using MapReduce and Hadoop
  • Hands-on experience in developing MapReduce programs
  • Expert guidance and support from experienced instructors
  • Industry-recognized certification on successful completion of the course
  • Career advancement opportunities in the field of big data processing
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Exam details to pass the course:

  • The course does not have a separate exam.
  • Your progress in the course will be evaluated through quizzes, assignments, and a final project.
  • To successfully complete the course, you will need to achieve a minimum score in the quizzes and assignments, and submit a final project that meets the requirements of the course.
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Certification path:

  • To earn the certification for MapReduce Training, you need to complete the course and pass the final project evaluation.
  • The certification is issued by Skillzcafe and is recognized in the industry as proof of your expertise in MapReduce and Hadoop.
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Career options after doing the course:

  • After completing the MapReduce Training course, you will have the skills and knowledge required to work with big data and develop MapReduce programs using Hadoop.
  • You can pursue a career as a big data engineer, Hadoop developer, data analyst, or data scientist.
  • The demand for professionals with skills in big data processing and Hadoop is high, and you can expect to find job opportunities in various industries.


Why should you take this course from Skillzcafe:

Why should you take this course from Skillzcafe:
  • Bullet Icon Skillzcafe is a leading provider of online courses in technology and business.
  • Bullet Icon Our courses are designed by industry experts and delivered by experienced instructors who provide expert guidance and support throughout the course.
  • Bullet Icon The MapReduce Training course is designed to provide hands-on experience in developing MapReduce programs and working with big data using Hadoop.
  • Bullet Icon You will benefit from our interactive learning environment, real-world case studies, and expert guidance to develop skills in big data processing.


Yes, the course is suitable for beginners who have basic programming skills in Java and familiarity with Linux command line interface.

No, you do not need to have prior experience in Hadoop to take this course. The course covers the fundamentals of Hadoop and MapReduce and provides hands-on experience in developing MapReduce programs.

The course duration is 70 hours.

To earn the certification, you need to complete the course and pass the final project evaluation. The certification is issued by Skillzcafe and is recognized in the industry.

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