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Big data /Hadoop at Mytectra Institute

IWWA Building NO (10)P 2nd Floor, 7th Main Road BTM 2nd Stage, ,
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About The Course:-

This course will cover concept such as HDFS, MapReduce, hive, hbase, pig, etc.,.

Who Should Take this?

This course is designed for professionals aspiring to make a career in Big Data Analytics using Hadoop Framework. Software Professionals, Analytics Professionals, ETL developers, Project Managers, Testing Professionals are the key beneficiaries of this course. Other professionals who are looking forward to acquire a solid foundation of Hadoop Architecture can also opt for this course.


Some of the prerequisites for learning Hadoop include hands-on experience in Core Java and good analytical skills to grasp and apply the concepts in Hadoop.

We provide a complimentary course “Java Essentials for Hadoop” to all the participants who enroll for the Hadoop Training. This course helps you brush up your Java skills needed to write Map Reduce programs.

Course Objectives:-

After completion of the course you should be able to :

    • Understanding Big Data and Hadoop
    • Hadoop Architecture and HDFS
    • Hadoop MapReduce Framework – I
    • Hadoop MapReduce Framework – II
    • Advance MapReduce
    • Pig
    • Hive
    • Advance Hive and HBase
    • Advance HBase
    • Oozie and Hadoop Project Explanation with Architecture

Module 1: Hadoop Architecture

Topics covered on introduction
  • What is Big Data
    Hadoop Architecture
    Hadoop ecosystem components
    Hadoop Storage: HDFS
    Hadoop Processing: MapReduce Framework
    Hadoop Server Roles: NameNode
    Secondary NameNode and DataNode
    Anatomy of File Write and Read

Module 2: Hadoop Cluster Configuration And Data Loading

Topics covered on HDFS
  • Hadoop Cluster Architecture
    Hadoop Cluster Configuration files
    Hadoop Cluster Modes
    Multi-Node Hadoop Cluster2.4
    A Typical Production Hadoop Cluster
    MapReduce Job execution
    Common Hadoop Shell commands
    Data Loading Techniques: FLUME, SQOOP, Hadoop Copy Commands
    Hadoop Project: Data Loading.

Module 3: Hadoop MapReduce Framework

Topic 1: Understanding MapReduce
    • Hadoop Data Types
      Hadoop MapReduceparadigm
      Map and Reduce tasks
      MapReduce Execution Framework
      Partitioners and Combiners
      Input Formats (Input Splits and Records, Text Input, Binary Input, Multiple Inputs) Output Formats (TextOutput, BinaryOutPut, Multiple Output)
      Hadoop Project: MapReduceProgramming.
Topic 2: MapReduce Programs

Module 5:Hive And HiveQL

Topic 1: HIVE Introduction, Installation and Configuration
    • Hive Architecture and Installation
      Comparison with Traditional Database
      HiveQL: Data Types
      Operators and Functions
      Hive Tables(Managed Tables and External Tables, Partitions and Buckets, Storage Formats, Importing Data, Altering Tables, Dropping Tables)
      Querying Data (Sorting And Aggregating, Map Reduce Scripts, Joins & Subqueries, Views, Map and Reduce side Joins to optimize Query)

Module 7:Querying Data using Pig

Topic 3: Grunt
Topic 4: PIG Data Model
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Start-End Dates: 17 Jun 16 - 16 Jul 16
Course Duration: 30 days
Instructional Level: Appropriate for All
Live Projects
Doubt Clearing Sessions
Reading Material
EMI Option
Online Support
Post completion course access
Practice Exams
Placement assistance
Refund Policy
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