Hadoop Online Training course - Hyderabad

Hadoop Online Training
Introduction
Hadoop DW course structure is a blend of administration and writing code using
Hadoop ecosystem components to show working with Big data. Topics covered in
this course, include- Hive, Pig, Zoo Keeper, Sqoop and multi node setup of Hadoop
Cluster on Amazon ec2 in CDH4. Hadoop developer course focuses on training
participants on setting up Hadoop infrastructure, writing Map Reduce Programs, Hive
and Pig Scripts, working with HDFS, Zoo keeper and Sqoop, Flume, Oozie.
Who should attend?
Java Developers / Architects, Data warehouse developers /SAAS
Professionals/Architects, Big data Professionals
Pre requisites for attending Training
Basic knowledge of unix , sql scripting
OBJECTIVE of the Training
 Understanding Distributed , parallel , cloud computing , No sql concepts
 Setting up Hadoop infrastructure with single and multi node cluster on amazon
ec2(CDH4)  Understanding of concepts of Map and Reduce and functional Programming
 Writing Map and Reduce Programs , Working with HDFS
 Writing Hive and Pig Scripts and working with Zoo Keeper and Sqoop
 Ability to design and develop applications involving large data using Hadoop eco
system
Course Outline
Introduction to Hadoop
 Distributed computing
 Parallel computing
 Concurrency
 Cloud Computing
 Data Past, Present and Future
 Computing Past, Present and Future
 Hadoop
 NoSQL
 Hadoop Streaming
 Distributing Debug Scripts
 Getting Started With Eclipse
Hadoop Stack
 CAP Theorem
 Databases: Key Value, Document, Graph
 Hive and Pig
 HDFSLab 1: Hadoop Hands-on
 Installing Hadoop Single Node cluster(CDH4)  Understanding Hadoop configuration files
HDFS Introduction
 Architecture
 File System
 Data replication
 Name Node
 Data Node
Hive introduction
Installation and Configuration
 Running Hive
 Configuration management overview
 Runtime configuration
 Hive, Map-Reduce and Local-Mode
DDL Operations
 Metadata Store
DML Operations
SQL Operations
 queries
 selects and filters
 group by
 join
 multitable insert  streaming
Exercise
 MovieLens
 Apache log
Hive Archiecture
 Data Store
 Metastore
 Architecture
 Interface
 HQL
 Compiler  OptimizerPig Introduction
 Pig and Dataflow
 Pig Philosophy
 Pig and Hadoop
 Pig vs Hive
 Why Pig
Installing and Configuring Pig
 Download and Install from Apache
 Running Pig
 Local  Cluster  Cloud
 Command Line Options
Grunt  Understanding Grunt  Entering PigLatin script in Grunt  HDFS Commands in Grunt  Controlling Pig from Grunt
Pig Data Model  Problem Statement and Data Model  Input and Output  Load
 Store
 Dump
 Relational Operators
 Foreach
 Filter  Group
 OrderBy
 Distinct  Join
 Limit  Sample
 Parallel  User Defined Functions
 Registering UDF
 Defining UDF
 Calling Static Java Functions
Flume
 What is Flume?
 How it works ?
 An example
 What is Sqoop?
 How it works ? An example
 What is Oozie?
 How it works?
 An example
Sqoop
Oozie
Load and Store Functions
Overview of Built-in Functions
Introduction to Zoo Keeper
Cluster Planning and Cloud Manager Set-up
Hadoop Multi node Cluster Setup
 Installation and Configuration
 Running MapReduce Jobs on Multi Node cluster
Working with Large data sets
 Steps involved in analyzing large data
 Lab walk through
POC for Hadoop Connectivity with ETL Tool
High Availability Fedration, Yarn and Security
If you require any further information please do not hesitate to contact us
please feel free to mail us for demo session or call @ 9989754807
contact: trainings@keentechnologies.com
website url: httpwww.keentechnologies.com