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BIGDATA HADOOP Course Details
 

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Batch Date: Mar 16th @9:00PM

Faculty: Mr. Ali (10+ Yrs of Exp,.. & Real Time Expert)

Duration : 30 Days

Venue :
DURGA SOFTWARE SOLUTIONS,
Flat No : 202, 2nd Floor,
HUDA Maitrivanam,
Ameerpet, Hyderabad - 500038

Ph.No: +91 - 9246212143, 80 96 96 96 96

Syllabus:

BIGDATA HADOOP


1. Setting up VM and Hadoop

  • Set up Cloudera VM
  • Install JDK
  • Installation Step of Hadoop Single Node Cluster
  • Install VM ware / Virtual Box

2. Introduction to Bigdata

  • Bigdata landscape
  • Course Content
  • Session details and Feedback process

3. Hadoop Architecture, Networking and Cluster
(HDFS & MapReduce)

  • Name Node
  • Data Node
  • Secondary Name Node
  • Rack Awareness
  • Replication & Re-replication
  • HDFS Read & Write

4. Linux & HDFS Commands

  • Basic Linux Commands
  • HDFS Commands

5. Working Session: Local FileSystem & HDFS Commands

6. MapReduce-1 (MR V1)

  • Understanding Map Reduce
  • Job Tracker and Task Tracker
  • Architecture of Map Reduce
  • Data Flow of Map Reduce
  • Hadoop Writable, Comparable & comparison with Java data types
  • Creation of local files and directories with Hadoop API
  • Creation of HDFS files and directories with Hadoop API
  • Map Function & Reduce Function
  • How Map Reduce Works
  • Anatomy of Map Reduce Job
  • Submission & Initialization of Map Reduce Job
  • Monitoring & Progress of Map Reduce Job
  • Understand Difference Between Block and Input Split
  • Role of Record Reader, Shuffler and Sorter
  • File Input Formats
  • How To check the Logs of all the Nodes (NN, DN, TT, JT, SNN)
  • Setting up Eclipse Development Environment
  • Creating Map Reduce Projects
  • Configuring Hadoop API on Eclipse IDE
  • Differences between the Hadoop Old and New APIs
  • Life cycle of the Job
  • Identity of Reducer

7. Working Session: Program

  • Map Reduce program flow with word count
  • Cricket Match Avg Score Program

8. Assessment

  • Hadoop MCQ

9. Apache Sqoop

  • Installation of Sqoop
  • Introduction to SQOOP & Architecture
  • Import data from RDBMS to HDFS
  • Handling incremental loads using sqoop
  • Hands on exercise

10. Working Session: Sqoop Commands

11. Sqoop Assignment

12. Apache Hive

  • Apache Hive Introduction & History
  • End-to-End workflow (Hive Architecture)
  • Data Types in Hive
  • Apache Hive table
  • Types of Tables in Hive (External & Internal)
  • Partitions (Static & Dynamic)
  • Types of Insertion (Single & Multi Table)
  • CTAS & CVAS Concept
  • Bucketing
  • File Input Formats (RCFILE, TEXTFILE, ORCFILE, SQUENCEFILE)

13. Working Session: Hive Practice

14. Hive Assignment

15. Apache PIG

  • PIG Introduction
  • Architecture
  • Commands

16. Working Session: Apache Pig Practice

17. Yarn (MapReduce V2)-Hadoop 2.x

  • Introduction of Yarn
  • Architecture of Yarn

18. ZooKeeper

  • Role of ZooKeeper
  • Journal Node
  • Use of ZoopKeeper

19. Apache Hbase

  • Hbase Introduction
  • Hbase commands
  • How To View Table data
  • How to Insert,Update and delete the data

20. Apache Oozie

  • Oozie Introduction
  • Components
  • How to Schedule Job
  • What is Workflow
  • What is Cordinator
  • What is Bundle

21. Hue

  • Introduction of Hue
  • How to run ETL process in Hue (Sqoop, Hive, Pig, Oozie)

22. Course closure : Mock Interview

  • Ending the course
  • Mock Interview on the concepts covered