Course Detail

Course Description

Hadoop

• What is big Data
• What is Hadoop
• Relation between Big data and Hadoop
• Need of going ahead with Hadoop
• Challenges with Big Data

• Storage
• Processing
• Comparison with other Technologies
• RDBMS
• DATA WAREHOUSE
• TERADATA

Components of Hadoop Echo System

• Storage Components
• Processing Components

HDFS (Hadoop Distributed file System)

• What is a cluster environment
• Cluster Vs Hadoop cluster
• Features of HDFS
• Storage aspects of HDFS

• • Block

Configuring the Block size

• • Why HDFS Block size is so large
  • Design Principles of Block size

HDFS Architecture – 5 Daemons of Hadoop

• Name Node
• Data Node
• Secondary Name Node
• Job Tracker
• Task Tracker

Replication in Hadoop – Fail over Mechanism

• Data Storage in Data Nodes
• Replication
• Custom Replication

MapReduce

• Why Map Reduce is essential in Hadoop

• Processing Daemons of Hadoop

• Job Tracker

  • Roles of Job Tracker
  • How to configure Job Tracker in Hadoop

  Task Tracker

  • Roles of Task Tracker
  • Drawbacks W.R.T failure in cluster

  Input Split

  • Need of Input Split
  • Input Split Size
  • Input split size Vs block size
  • Input Split Vs Mappers

  Map Reduce Programming Model

  • Different phases of Map Reduce Algorithm
  • Data Types in Map Reduce

  Basis Map Reduce program

  • Driver code

     

  • Mapper Code
  • Reducer Code

  Combiner in Map Reduce

  Practitioner in Map Reduce

  Joins in map Reduce

  • Map side join
  • Reduce side join
  • Performance trade off

  Map Reduce Streaming

  Apache PIG

  • Introduction to PIG
  • Map Reduce Vs PIG
  • SQL Vs PIG
  • Data Types in PIG
  • Execution Modes of Pig ( Local/Distributed)
  • Execution Mechanism { Grunt Shell, Script }
  • Writing Simple pig script
  • Bags, Tuples, and Fields in PIG
  • UDF’s in PIG

  HIVE

  • Need of Apache Hive
  • HIVE Architecture [ Driver, Compiler, Executer ]
  • HIVE Query language
  • SQL Vs HIVE QL
  • Collection Data types in Hive [ Array, Struct, Map ]
  • UDF’s in HIVE
  • UDAFs
  • UDTFs
  • SerDe [ Hive serializer / Deserializer ]

  SQOOP

  • Introduction
  • MySQL Initialization
  • Connecting RDBMS using SQOOP
  • Sqoop Commands

  HBASE

  • Introduction
  • HDFS Vs HBase
  • HBase Architecture
  • MapReduce over HBase

  • • • Pre Requisites: Core JAVA + Linux Commands

        Time Duration: 5 Weeks [30 Hrs + lab]