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Summer Industrial Training Big Data Hadoop Administrator | 6 Months / 6 Weeks Big Data Hadoop Administrator Training in Chandigarh

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    Big Data Hadoop Administrator


    Module 1 – Learning Objectives:

    By end of the module, the student will be able to understand the basics of big data, he/she will have the foundation of Hadoop daemons and Hadoop architecture.

      1. Understanding Big Data Basics
      2. Big Data Use Cases
      3. Introduction to Hadoop
      4. Understanding Hadoop Ecosystem
      5. Introduction to HDFS
        • Introduction to Namenode
        • Introduction to Datanode
        • Introduction to Secondary Namenode
      6. Introduction to MapReduce
        • Introduction to JobTracker
        • Introduction to TaskTracker
      7. Summarizing Hadoop Architecture
      8. Roles and Responsibilities of a Hadoop Administrator

    Module 2 – Learning Objectives:

    By end of the module, the student will be able to create a multi node Hadoop cluster. For preparing the students to create Hadoop cluster, this module gives the deep understanding of how linux works, how to setup the virtual machines, how to setup the passwordless ssh.

      • Linux internals
        • Commands that are required
        • Linux basics
      • Hadoop Cluster Installation Pre-requisites
        • Pre-requisites of Hadoop Installation
          • Softwares Download
          • Preparing yo;ur VM
          • Enabling VM with VMware
          • Understanding mandatory changes in the operating system
      • Installation and Configuration
        • Understanding Hadoop cluster installation modes
        • Understanding Hadoop version 1 installation and configuration
        • Passwordless SSH setup
      • Hands-On Practice for creating a Hadoop cluster
        • Helping individually in practicing Hadoop cluster installation

    Module 3 – Learning Objectives:

    By end of the module, the student will be able to understand how to plan a production cluster of Hadoop. Students will understand the hardware and software requirements of Hadoop cluster, performance tuning after cluster creation and benchmarking.

    Module 4 – Learning Objectives:

    By end of the module, the student will be able to administrate the Hadoop cluster. Students will understand how to copy the data from one Hadoop cluster to another Hadoop cluster, different Hadoop schedulers to run the jobs, backup and recovery of metadata, data, configurations, and applications data and recover the cluster data.

    Module 5 – Learning Objectives:

    By end of the module, the student will be able to understand how the next version of Hadoop and YARN works. New features of Hadoop version 2, yarn framework, deploying a Hadoop 2 cluster in pseudo distributed and multi distributed mode.

    • Hadoop 2.0 new features
    • YARN
      • Understanding Resource Manager
      • Understanding Application Master
      • Understanding Node Manager
      • Understanding Hadoop 2 Job Execution Framework
    • Hadoop 2 Multi-node cluster creation
      • Pre-requisites of Hadoop Installation
      • Softwares Download
      • Preparing your VM
      • Enabling VM with VMware
      • Understanding mandatory changes in the operating system
      • Installation and Configuration
      • Understanding Hadoop version 2 installation and configuration
      • Passwordless SSH setup

    Module 6 – Learning Objectives:

    By end of the module, the student will be able to learn how to achieve high availability, how to enable federation in namenode and what the various improvements in Hadoop 2 are.

      • Practice Hadoop 2 multi-node Cluster Creation
        • Helping individuals in practicing Hadoop 2 cluster installation
      • Sample Yarn Job execution
      • Understanding Issues of Hadoop 1
      • Understanding improvements in Hadoop 2
      • Namenode Federation
        • Enable segregation of HDFS using multiple namenodes
      • Namenode – High Availability
        • Achieving Namenode High-Availability using Quorum Journal Manager
        • Achieving Namenode High-Availability using Network File System
      • Implementation of NN High Availability
        • Helping individuals achieving Namenode High Availability

    Module 7 – Learning Objectives:

    By end of the module, the student will be able to administrate the basics of Hadoop ecosystem components like Hive, Hbase, Sqoop, Flume and Pig.

    • Hadoop Ecosystem Introduction
      • Understanding the integration of Hadoop ecosystem
    • Touchbase with Hive
      • What is Hive
      • Architecture of Hive
      • Understanding Hive metastore concepts
    • HBase
      • Understading HBase Basics
      • Understanding HBase storage Model
      • Understanding HBase Architecture
      • Cluster Installation and Configuration
    • Pig
      • What is Pig?
      • How Pig integrates with Hadoop cluster?
      • Demo of Pig Jobs using MapReduce
    • Sqoop
      • What is Sqoop?
      • How to import and export the data from Sqoop to RDBMS?
      • Example of Sqoop jobs using MySQL
    • Flume
      • What is F
      • Sample Flume jobs

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