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ONLINE ADVANCE HADOOP TRAINING IN SINGAPORE

Companies around the world today find it increasingly difficult to organize and manage large volumes of data. Hadoop has emerged as the most efficient data platform for companies working with big data, and is an integral part of storing, handling and retrieving enormous amounts of data in a variety of applications. Hadoop helps to run deep analytics which cannot be effectively handled by a database engine.

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Hadoop Course Modules

INTRODUCTION

  • What is Hadoop?
  • Who is behind Hadoop?

 

  • History of Hadoop
  • What Hadoop is good for and why it is Good

 

  • Building Blocks - Hadoop Eco-System

 

HDFS

  • Configuring HDFS
  • Additional HDFS Tasks
  • Hadoop File System Shell
  • Interacting With HDFS
  • HDFS Overview and Architecture
  • File System Java API
  • HDFS Permissions and Security
  • HDFS Installation

MAPREDUCE

  • Map/Reduce Overview and Architecture
  • Input and Output Formats
  • Practicing Map Reduce Programs (atleast 10 Map Reduce Algorithms )
  • Installation
  • Job Configuration
  • Developing Map/Red Jobs
  • Job Submission

Getting Started With Eclipse IDE

  • Configuring Hadoop API on Eclipse IDE

 

  • Connecting Eclipse IDE to HDFS

Advanced MapReduce Features

  • Custom Data Types
  • Partitioning Data

 

  • Input Formats
  • Reporting Custom Metrics

 

  • Output Formats
  • Distributing Auxiliary Job Data

 

PIG

  • Pig Overview
  • Pig with HDFS
  • Installation
  • Pig Latin

Hive

  • Hive Overview
  • Hive Unstructured Data Analyzation
  • Installation
  • Hive Semistructured Data Analyzation
  • Hive QL

HBase

  • HBase Overview and Architecture
  • CRUD operations
  • HBase Key Design
  • HBase Installation
  • Scanning and Batching
  • HBase Shell
  • Filters

ZooKeeper

  • Zoo Keeper Overview
  • Installation
  • Server Mantainace

Sqoop

  • Sqoop Overview
  • Installation
  • Imports and Exports

CONFIGURATION

  • Basic Setup
  • Cluster Configurations
  • Large Clusters: Multiple Racks
  • Important Directories
  • Small Clusters: 2-10 Nodes
  • Selecting Machines
  • Medium Clusters: 10-40 Nodes

Putting it all together

  • Distributed installations
  • Best Practices
 
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