Hadoop Online Training

Best Hadoop Online Training

Hadoop Online Training

QTEC provides real-time and placement oriented  Hadoop Training online training, online training. Our Hadoop Training course includes basic to advanced level and our Hadoop Training course is designed to get the placement in major MNC companies in online training as soon as you complete the Hadoop Training in online training from our institute.

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QTEC provides real-time Hadoop Online Training. We Provide 100% Placement Assistance and ensures that each and every student gets all kind of support from us.

Hadoop Online Training Course Content

Hadoop Training in Marathahalli

Course Content for Hadoop Developer

This Course Covers 100% Developer and 40% Administration Syllabus.

Introduction to BigData, Hadoop:-

 Big Data Introduction

 Hadoop Introduction

 What is Hadoop? Why Hadoop?

 Hadoop History?

 Different types of Components in Hadoop?

 HDFS, MapReduce, PIG, Hive, SQOOP, HBASE, OOZIE, Flume, Zookeeper and so on…

 What is the scope of Hadoop?

Deep Drive in HDFS (for Storing the Data):-

 Introduction of HDFS

 HDFS Design

 HDFS role in Hadoop

 Features of HDFS

 Daemons of Hadoop and its functionality

o Name Node

o Secondary Name Node

o Job Tracker

o Data Node

o Task Tracker

 Anatomy of File Wright

 Anatomy of File Read

 Network Topology

o Nodes

o Racks

o Data Center

 Parallel Copying using DistCp

 Basic Configuration for HDFS

 Data Organization

o Blocks and

o Replication

 Rack Awareness

 Heartbeat Signal

 How to Store the Data into HDFS

 How to Read the Data from HDFS

 Accessing HDFS (Introduction of Basic UNIX commands)

 CLI commands

MapReduce using Java (Processing the Data):-

 The introduction of MapReduce.

 MapReduce Architecture

 Data flow in MapReduce

o Splits

o Mapper

o Portioning

o Sort and shuffle

o Combiner

o Reducer

 Understand Difference Between Block and InputSplit

 Role of RecordReader

 Basic Configuration of MapReduce

 MapReduce life cycle

o Driver Code

o Mapper

o and Reducer

 How MapReduce Works

 Writing and Executing the Basic MapReduce Program using Java

 Submission & Initialization of MapReduce Job.

 File Input/Output Formats in MapReduce Jobs

o Text Input Format

o Key Value Input Format

o Sequence File Input Format

o NLine Input Format

 Joins

o Map-side Joins

o Reducer-side Joins

 Word Count Example

 Partition MapReduce Program

 Side Data Distribution

o Distributed Cache (with Program)

 Counters (with Program)

o Types of Counters

o Task Counters

o Job Counters

o User Defined Counters

o Propagation of Counters

 Job Scheduling


 Introduction to Apache PIG

 Introduction to PIG Data Flow Engine

 MapReduce vs. PIG in detail

 When should PIG use?

 Data Types in PIG

 Basic PIG programming

 Modes of Execution in PIG

o Local Mode and

o MapReduce Mode

 Execution Mechanisms

o Grunt Shell

o Script

o Embedded

 Operators/Transformations in PIG

 PIG UDF’s with Program

 Word Count Example in PIG

 The difference between the MapReduce and PIG


 Introduction to SQOOP

 Use of SQOOP

 Connect to mySql database

 SQOOP commands

o Import

o Export

o Eval

o Codegen etc…

 Joins in SQOOP

 Export to MySQL

 Export to HBase


 Introduction to HIVE

 HIVE Meta Store

 HIVE Architecture

 Tables in HIVE

o Managed Tables

o External Tables

 Hive Data Types

o Primitive Types

o Complex Types

 Partition

 Joins in HIVE

 HIVE UDF’s and UADF’s with Programs

 Word Count Example


 Introduction to HBASE

 Basic Configurations of HBASE

 Fundamentals of HBase

 What is NoSQL?

 HBase Data Model

o Table and Row

o Column Family and Column Qualifier

o Cell and its Versioning

 Categories of NoSQL Data Bases

o Key-Value Database

o Document Database

o Column Family Database

 HBASE Architecture

o HMaster

o Region Servers

o Regions

o MemStore

o Store


 How HBASE is differed from RDBMS

 HDFS vs. HBase

 Client-side buffering or bulk uploads

 HBase Designing Tables

 HBase Operations

o Get

o Scan

o Put

o Delete



 What is MongoDB?

 Where to Use?

 Configuration On Windows

 Inserting the data into MongoDB?

 Reading the MongoDB data.

Cluster Setup:–

 Downloading and installing the Ubuntu12.x

 Installing Java

 Installing Hadoop

 Creating Cluster

 Increasing Decreasing the Cluster size

 Monitoring the Cluster Health

 Starting and Stopping the Nodes


 Introduction Zookeeper

 Data Modal

 Operations


 Introduction to OOZIE

 Use of OOZIE

 Where to use?


 Introduction to Flume

 Uses of Flume

 Flume Architecture

o Flume Master

o Flume Collectors

o Flume Agents

Project Explanation with Architecture



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