New Class Schedule Coming soon...

Bigdata and Hadoop Developement

The accessibility of substantial information sets displays new open doors and difficulties to associations of all sizes. This course clarifies Hadoop best practices and gives the Hadoop advancement preparing and programming aptitudes to create arrangements that keep running on the Apache Hadoop stage. Moreover, you figure out how to test and send Big Data arrangements on merchandise bunches. Both Big Data and Hadoop have been in much demand ever since their inception. These programs are mainly used to sort through multiple terabytes of data that are clustered and accommodated throughout the functioning of a business or website. These are important data and need to be sorted, stored, backed up, recovered and managed. These are the exact skills that an individual can lean with the help of the Big Data and Hadoop Development Training.

The Successful completion of this course awards candidates with a certificate that declares them as skilled and knowledgeable professionals with more than 60 hours of experience in Big Data and Hadoop Administrating.


Category
: Technical

Duration
: 30 Days

Timing
: Week Days: 1 - 2 hrs per day (OR) Weekends: 2 - 3 hrs per day

Method
: Online / Classroom Training Study

Material
: Softcopy

System Access
: 30 Days

Job Assurance
: 100% Placement Assistance

Extras
: Interview Questions & Answers will be covered along with course

Introduction to Hadoop and its Ecosystem, Map Reduce and HDFS cture

  • Big Data, Factors constituting Big Data
  • Hadoop and Hadoop Ecosystem
  • Map Reduce -Concepts of Map, Reduce, Ordering, Concurrency, Shuffle, Reducing, Concurrency
  • Hadoop Distributed File System (HDFS) Concepts and its Importance
  • Deep Dive in Map Reduce – Execution Framework, Partitioner, Combiner, Data Types, Key pairs
  • HDFS Deep Dive – Architecture, Data Replication, Name Node, Data Node, Data Flow
  • Parallel Copying with DISTCP, Hadoop Archives

Practice 

Hands on Exercises

  • Installing Hadoop in Pseudo Distributed Mode, Understanding Important configuration files, their Properties and Demon Threads
  • Accessing HDFS from Command Line
  • Map Reduce – Basic Exercises
  • Understanding Hadoop Eco-system
  • Introduction to Sqoop, use cases and Installation
  • Introduction to Hive, use cases and Installation
  • Introduction to Pig, use cases and Installation
  • Introduction to Oozie, use cases and Installation
  • Introduction to Flume, use cases and Installation
  • Introduction to Yarn

Practice - Importing Mysql Data using Sqoop and Querying it using Hive

Deep Dive in Map Reduce and Yarn

  • How to develop Map Reduce Application, writing unit test
  • Best Practices for developing and writing, Debugging Map Reduce applications
  • Joining Data sets in Map Reduce
  • Hadoop API’s
  • Introduction to Hadoop Yarn
  • Difference between Hadoop 1.0 and 2.0

Practice – end to end PoC using Yarn or Hadoop 2

Real World Transactions handling of Bank

  • Moving data using Sqoop to HDFS
  • Incremental update of data to HDFS
  • Running Map Reduce Program
  • Running Hive queries for data analytics

Practice – end to end PoC using Yarn or Hadoop 2.0

Running Map Reduce Code for Movie Rating and finding their fans and average rating

Deep Dive in Pig

1.Introduction to Pig

  • What Is Pig?
  • Pig’s Features
  • Pig Use CasesInteracting with Pig

2.Basic Data Analysis with Pig

  • Pig Latin Syntax
  • Loading Data
  • Simple Data Types
  • Field Definitions
  • Data Output
  • Viewing the Schema
  • Filtering and Sorting Data
  • Commonly-Used Functions
  • Hands-On Exercise: Using Pig for ETL Processing

3.Processing Complex Data with Pig

  • Complex/Nested Data Type
  • Grouping
  • Iterating Grouped Data
  • Hands-On Exercise: Analyzing Data with Pig

Practice 

Deep Dive in Hive

1.Introduction to Hive

  • What Is Hive?
  • Hive Schema and Data Storage
  • Comparing Hive to Traditional Databases
  • Hive vs. Pig
  • Hive Use Cases
  • Interacting with Hive

2.Relational Data Analysis with Hive

  • Hive Databases and Tables
  • Basic HiveQL Syntax
  • Data Types
  • Joining Data Sets
  • Common Built-in Functions

Practice: Running Hive Queries on the Shell, Scripts, and Hue

3.Hive Data Management

  • Hive Data Formats
  • Creating Databases and Hive-Managed Tables
  • Loading Data into Hive
  • Altering Databases and Tables
  • Self-Managed Tables
  • Simplifying Queries with Views
  • Storing Query Results
  • Controlling Access to Data
  • Hands-On Exercise: Data Management with Hive

4.Hive Optimization

  • Understanding Query Performance
  • Partitioning
  • Bucketing
  • Indexing Data

Practice

Introduction to Hbase architecture

  • What is Hbase
  • Where does it fits
  • What is NOSQL

Practice 

Hadoop Cluster Setup and Running Map Reduce Jobs

  • Hadoop Multi Node Cluster Setup using Amazon ec2 – Creating 4 node cluster setup
  • Running Map Reduce Jobs on Cluster

Practice 

Advance Mapreduce

  • Delving Deeper Into The Hadoop API
  • More Advanced Map Reduce Programming, Joining Data Sets in Map Reduce
  • Graph Manipulation in Hadoop

Practice 

Job and certification support

Major Project, Hadoop Development, cloudera Certification Tips and Guidance and Mock Interview Preparation, Practical Development Tips and Techniques, certification preparation

This specific course has been designed by some of the leading industry professionals in the field of Hadoop development. 

This helps us to provide candidates with in-depth skills and knowledge of the topic so that they can continue on the way to become successful Hadoop Developers. 

The strategically designed curriculum is extensive and natures and makes it a point to cover all the different sectors of Hadoop Development. 

Some of the other core objectives of the course, includes-

Understanding and short listing different types of data into Hadoop that are compatible with the system.

Analysing different kinds of Data using HIVE and PIG.

Learning and becoming an expert on diverse concepts, related to Hadoop eco-system - Map Reduce and HDFS systems.

Setting Up Hadoop Cluster

Writing Complex Max Reduce Programs

Understanding and executing expert Zookeeper services, etc.

The KBS Training Institute is providing top class Big Data and Hadoop Development Training to individuals across the country for quite some time now. 

The course is designed to meet international standards as well as provide the students of this course with internationally bankable job opportunities.

The aim of the company is to cater to both skilled employee hungry employers as well as the genuine, hardworking job seeking individuals and this course helps deliver to this aim, fantastically. 

KBS is registered with the top institutes around the world, dealing in Hadoop and that brings us the right to despatch succession certificates to candidates who have completed the course successfully. 

Our certificate holds much value in the international job market, for the role of Hadoop Developer. 

Course Highlights:

There are a number of highlights of the Big Data and Hadoop Development Training designed by KBS. Candidates will not only learn to manage data on a much larger scale but will also learn to write codes on the Map Reduce system/framework.  Apart from this the hands on nature of the training, communicative sessions, 24x7 assistance from mentors, and co-operative projects, also make some of the highlights of this training. Some other advanced modules that candidates can learn with this course, are-

  • Yarn, 
  • Oozie, 
  • Zookeeper, 
  • Sqoop, 
  • Flume, 
  • Mongo, 
  • Neo4J,
  • Prophetess, and 
  • Spark.

What are the system requirements?

For Hadoop to be compatible with your system, you will require-

  • 4GB Ram, and a
  • 64 Bit operating system.

What should I opt for-class based training or online training?

Online training is for individuals who find it hard to take out time for regular classes out of their busy schedule or leave beyond the proximity of the classes. As far as the competency of both these options is concerned, both of them are equally fantastic.

What if I Miss a class?

Every class comes with a recording, which is handed over to students after the completion of the class. If you miss a class, you can use the recording to catch up on whatever is taught. 

When am I eligible to get my certificate?

A candidate is only eligible to receive a certificate, after completing all assignments and projects and securing a 65% in their exam.

How do I get my Certificate?

On successful completion of the Big Data and Hadoop Development Training exam and expert evaluation of assignments and projects, candidates are handed over their certificates through mail.

Prerequisite

Trainee must need to complete an under graduate course to better understand the course.

Having Knowledge in core Java will be an advantage, yet is not mandatory.

Having fair Knowledge with any database will be an advantage, yet is not mandatory.

Quick Enquiry Form