Hadoop Framework Training Online| Hadoop Framework Certification

Course Overview

The Hadoop Framework training is designed to help in understanding the basic and advanced concepts of Hadoop. During the Hadoop certification training, you will learn about an overview of big data, and Hadoop, features of Hadoop, an introduction to YARN (Yet Another Resource Negotiator), a description of MapReduce, YARN architecture, Hadoop MapReduce framework, and many more. You will also get exposure to two real-time company-based projects that are based on the Hadoop framework which is beneficial in improving your technical skills and career growth. These projects can help in improving your professional resume and is advantageous in getting a job in a top company with exciting salaries. We also provide Hadoop tutorials that contain brief details of the Hadoop framework course and help in the preparation for the certification exam. After completing your online course, we will also offer Hadoop Framework Certification that is helpful for a better future.

Key Features Hadoop Framework Certification:

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 Course ?

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.

Top Hiring Company

Industry Trends

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

Siebel Sales scenario: Forecasting
Sales methodologies, TAS, Remote
Siebel Sales scenario: Opportunity Management
Smart Script, Email Response, Multi-Tenancy, and Hoteling

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.