Hadoop course Content online training â?? 30 hrs

Understanding Big Data

Introduction

Understanding Big Data

3V (Volume-Variety-Velocity) Characteristics

Structured and Unstructured Data

Application and use cases of Big Data

Limitations of Traditional Large Scale Systems

How a distributed way of computing is superior (cost and scale)

Installation/ setup/ configuration

Download and setting the VMware for running the Linux Cent OS or Ubunto

Download Install and configuration of Hadoop 1.0.4

Download Install and configuration of Hive 0.10 stable version

Download Install and configuration of sqoop 1.4.2

Download Install and configuration of oozie

Will share the configurations for setting up the Hadoop cluster

HDFS (Hadoop Distributed FileSystem)

HDFS Overview and Architecture

Data Replication

Safe Mode

Name Node

Checkpoint Node

Backup Node

Configuration Files

HDFS Data Flows

Read

Write

HDFS Commands

File System

Administrative

Advanced HDFS Features

HDFS Federation

HDFS High Availability

MapReduce Overview 

Functional Programming Paradigms

Input and Output Formats

Hadoop Data Types

Input Splits

Shuffling

Sorting

Hadoop Streaming 

Combiners

Partitioning

Configuration Files

Compression (Creating a sequence file and compressing the sequence file)

Distributed Cache

JVM Reuse

Standalone Mode

MR Algorithm and Data Flow

WordCount

MapReduce Architecture

Legacy MR

Next Generation MapReduce (aka YARN/MRV2)

Difference between Legacy MR and MR2 by programming

MR Best Practice and Debugging

Fundamental MR Algorithms (Non-Graph)

Max Temperature

Higher Level Abstractions for MapReduce â?? 1

Pig Introduction

Pig Latin Language Constructs

Pig User Defined Functions

Pig Use Cases

Pig  scripts for data analysis

Higher Level Abstractions for MapReduce â?? 2

Hive - Introduction

Hive QL

Hive User Defined Functions

Hive Use Cases

NOSQL Databases 

NoSQL Concepts

Review of RDBMS

Need for NOSQL

Brewers CAP Theorem

ACID vs BASE

Different Types of NoSQL Databases

Key Value

Columnar

Document

Graph

Columnar Databases

Hadoop Ecosystem

HBase â?? No SQL Database -

SQOOP

OOZIE

• At the end of each session material for the day will be shared and along with few links and other resources for the topics will be shared with the candidates.
• Exercises on the topic will be given for practice next day will discuss the solution for the same and will move to the next topic.
• Where ever possible Interview questions and scenario based problems will be shared to the candidates to get the insight of the real time environment.

• At the completion of the course a real time POC (Proof Of Concept) requirement will be given to the candidates for practicing the end to end Hadoop contents.

Optional:

For the candidate who do not have prior Java (Core Java)  knowledge Five sessions on Java concepts required for writing MapReduce programs will be taken