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Hadoop Framework Training

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Hadoop Framework Training

Hadoop Framework

Our Hadoop Framework Online Training course lets you master the concepts of the Hadoop Framework. Our Hadoop Framework training offers from basic level to advanced level. We provide Hadoop Framework certification after the completion of the course. This Training will help you get better opportunities and high pay professional opportunities.

Course Overview

Our Hadoop Framework helps you get a deeper knowledge of various Hadoop Framework Tools, Hadoop Framework Architecture, and Hadoop Framework Components. Our professionals will give you real-world knowledge and real-world examples which are best in their respective fields.

Key Features:

  • Job Assistance will be provided
  • Real-life industry-based projects will be given as assignments to improve your skills
  • Mock interview sessions will be taken to build confidence among the students
  • 24/7 support will be given to the students

Who Should Learn Hadoop Framework ?

Programming Developers, System Administrators, Project Managers, Mainframe Professionals, Architects, Testing Professionals, Business Intelligence, Analytical Professionals, and freshly graduated students who wanted to start their career as Hadoop Framework Developer can take this course.

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Course curriculum / Syllabus

Introduction , The Motivation for Hadoop
  • Problems with traditional large-scale systems
  • Requirements for a new approach
Hadoop Basic Concepts
  • An Overview of Hadoop
  • The Hadoop Distributed File System
  • Hands on Exercise
  • How MapReduce Works
  • Hands on Exercises
  • Anatomy of a Hadoop Cluster
  • Other Hadoop Ecosystem Components
Writing a MapReduce Program
  • Examining a Sample MapReduce Program
  • With several examples
  • Basic API Concepts
  • The Driver Code
  • What is The Mapper?
  • What is The Reducer?
  • Hadoop’s Streaming API
Delving Deeper Into The Hadoop API
  • More About ToolRunner
  • Testing with MRUnit
  • Reducing Intermediate Data With Combiners
  • Configuring and closing methods for Map/Reduce Setup and Teardown
  • Writing Partitioners for Better Load Balancing
  • Hands-On Exercise
  • Directly Accessing HDFS
  • Using the Distributed Cache
  • Hands-On Exercise
Performing several hadoop
  • The configure and close Methods
  • What are Sequence Files?
  • What is Record Reader?
  • What is Record Writer?
  • What is Role of Reporter?
  • What is Output Collector?
  • Processing video files and audio files
  • Processing image files
  • Processing XML files
  • Usage of Counters
  • Directly Accessing HDFS
  • Working of ToolRunner
  • Using The Distributed Cache
Common MapReduce Algorithms
  • Sorting and Searching
  • What is Indexing?
  • Classification/Machine Learning
  • Term Frequency – Inverse Document Frequency
  • Word Co-Occurrence
  • Hands-On Exercise: Creating an Inverted Index
  • Identity Mapper in MapReduce Algorithms
  • Identity Reducer in MapReduce Algorithms
  • Exploring well known problems using MapReduce applications
Using Hbase
  • What is HBase?
  • Features and usage of HBase API
  • Managing large data sets with HBase
  • Using HBase in Hadoop applications
  • Hands-on Exercise
Using Hive and Pig
  • Hive Basics
  • Pig Basics
  • Hands on Exercise
Practical Development Tips and Techniques
  • Debugging MapReduce Code
  • Using LocalJobRunner Mode for Easier Debugging
  • Retrieving Job Information with Counters
  • What is Logging development of programs?
  • Splittable File Formats
  • Determining the Optimal Number of Reducers
  • Map-Only MapReduce Jobs
  • Hands on Exercise
Debugging MapReduce Programs
  • Testing with MRUnit
  • What is Logging in debugging programs
  • Classification/Machine Learning
  • Advanced MapReduce Programming
  • A Recap of the MapReduce Flow
  • The Secondary Sort
  • Customized InputFormats and OutputFormats
  • Pipelining Jobs With Oozie
  • Map-Side Joins
  • Reduce-Side Joins
Joining Data Sets in MapReduce
  • Map-Side Joins
  • The Secondary Sort
  • Reduce-Side Joins
Monitoring and debugging on a Production Cluster
  • Counters
  • Skipping Bad Records
  • Rerunning failed tasks with Isolation Runner
Tuning for Performance in MapReduce
  • Reducing network traffic with combiner
  • Partitioners
  • Reducing the amount of input data
  • Using Compression
  • Reusing the JVM
  • Running with speculative execution
  • How to refactor a code and rewrite algorithms Parameters affecting Performance
  • Other Performance Aspects

Hadoop Framework Training FAQ’s:

1.What will you learn through Big Data Hadoop Framework?

In this course you will learn the concepts of big data analysis. Besides the course, dummy projects will also be provided to you so that you can understand the core concepts easily.

2.How will the certification affect my career?

Big data is being used in various industries and there is a huge demand of certified big data professionals in the market. The course will make you eligible for the jobs in many industries.

3.Which prerequisites are required for the course?

A basic knowledge of Java and LINUX is necessary to learn Hadoop.

4.How much time will it take to learn Hadoop?

A few days is taken to learn the course provided that you have basic knowledge of Java and LINUX.

5.For how much time will instructors be available?

Instructors will be available 24/7.

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Mock projects

Real world project samples for practical sessions