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Introduction to HADOOP

Distributed computing , cloud computing
Big data Basics and Need for Parallel Processing
How Hadoop works ?
Introduction to HDFS and Map

Big Data Course


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For more details contact us at +91-720-720-9005 ( Whats app ) or


Introduction to HADOOP

  1. Distributed computing , cloud computing
  2. Big data Basics and Need for Parallel Processing
  3. How Hadoop works ?
  4. Introduction to HDFS and Map Reduce

 Hadoop Architecture Details

  1. Name Node
  2. Data Node
  3. Secondary Name Node
  4. Job Tracker
  5. Task Tracker
  6. Safe Mode , FS Image and Edit log details

HDFS ( Hadoop - Distributed File System)

  1. Hadoop Distributed file system , Background, GFS
  2. Data Replication
  3. Data Storage
  4. Data Retrieval
  5. Additional HDFS commands
  6. HDFS Upgrade steps
  7. NameNode Failure recovery steps and execution.
  8. HDFS - Java API for Interaction with FS.
  9. Node Decommissioning 

 MapReduce Programming

  1. MapReduce, Background
  2. Writing MapReduce Programs
  3. Writable and WritableComparable
  4. Input Format, Output Format
  5. Input Split and Block size
  6. Combiner
  7. Partitioner
  8. Number of Mappers and Reducers
  9. Counters


Map Reduce Algorithms and Exercises

  1. Sentiment Analysis using Facebook , Twitter and Youtube data
  2. Frequency Count example with variations of MR .
  3. Eclipse based development of end to end MR Job and Deployment.
  4. Sorting Data using Key value Data Type Lab
  5. Exercises- Martix , Partitioner, No Reduce, Distributed Cache Labs


Hadoop Streaming

  1. Introduction to Hadoop Streaming
  2. Streaming API details and use cases
  3. Python Based Example for Streaming API
  4. Exercise for Hadoop Streaming ( XML Files ) Based.
  5. Exercises on Ruby
  6. Exercise on C# using MS-Azure.

Apache Pig

  1. Installation and configuration
  2. Execution Types - Local , MR modes
  3. Grunt Shell - Configuration 
  4. Pig Latin - Examples and code
  5. Data Processing using Pig Latin
  6. Loading and Storing Pig Functions
  7. Data Filtering
  8. Grouping & Joining Operations
  9. Hands on Exercises


Apache HBase Installation and Details

  1. HBase and NOSQL Introduction
  2. HBase Installation and Configuration.
  3. HBase and Java Based integration
  4. Hbase basic exercises


 Apache Hive  Instalaltion and Details

  1.     Hive Installation on Single cluster Hadoop Node.
  2.     Hive Services
  3.     Hive Shell Deion
  4.     Meta store Details
  5.     Hive QL Basics
  6.     Working with Tables, Databases etc.
  7.     Hive JDBC programming
  8.     Hands on Exercises and Assignments

Introduction to Amazon Map Reduce (AWS-EMR)

  1. Hadoop using Amaozon Web Service
  2. AWS MapReduce and EC2 
  3. AWS - S3 Service Model.
  4. AWS-MR Architecture.
  5. Streaming Exercise using EMR JobFlow.


Hadoop Infrastructure Planning

  1. Basic Hadoop hardware and software req
  2. Small , Medium and Large cluster 
  3. Networking challenges in Hadoop Deployment
  4. Disaster Recovery ( DR ) in Hadoop .
  5. Performance Tuning a large cluster

 Hadoop Industry Solutions

  1. EMC GreenPlum Introduction
  2. IBM BigInsight Details


People planning to move from Mainframe, SAP , ERP ,.NET domain get specialized consultancy help to map there existing skillset and tune it as per Hadoop related job opportunities.
We go with a end to end , 3 phase approach to cater to your need for not only helping you with training but also with interview preparation and later job support.

  1. Complete Hadoop and Eco system Training 
  2. Live Interview Preparation with mock interviews
  3.  Job support with coding help

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