Learn Hadoop at your Leisure time

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Introduction :

Big Data and Hadoop training course is designed to provide knowledge and skills to become a successful Hadoop Developer. In-depth knowledge of concepts such as Hadoop Distributed File System, Hadoop Cluster, Map-Reduce, Hbase Zookeeper etc. will be covered in the course. Reason To Attend : After the completion of the Big Data and Hadoop Course at KPM, you should be able to:

• Master the concepts of Hadoop Distributed File System and MapReduce framework

• Setup a Hadoop Cluster • Understand Data Loading Techniques using Sqoop and Flume • Program in MapReduce (Both MRv1 and MRv2) • Learn to write Complex MapReduce programs • Program in YARN (MRv2) • Perform Data Analytics using Pig and Hive • Implement HBase, MapReduce Integration, Advanced Usage

and Advanced Indexing • Have a good understanding of ZooKeeper service • New features in Hadoop 2.0 -- YARN, HDFS Federation,

NameNode High Availability • Implement best Practices for Hadoop Development and

Debugging • Implement a Hadoop Project • Work on a Real Life Project on Big Data Analytics and gain

Hands on Project Experience

Who should attend : This course is designed for professionals aspiring to make a career in Big Data Analytics using Hadoop Framework. Software Professionals, Analytics Professionals, ETL developers, Project Managers, Testing Professionals are the key beneficiaries of this course. Other professionals who are looking forward to acquire a solid foundation of Hadoop Architecture can also opt for this course.


Course Content :

Big Data Economy …………………………………………………………… 1.5 Hrs.

• What is Big Data • Characteristics of Big Data • How did data become so Big • Why should you care about Big Data • Uses Cases of Big Data Analysis • What are possible options for analyzing big data • Traditional Distributed Systems • Problem with traditional Distributed systems

Hadoop Introduction………………………………………………………… 1.5 Hrs.

• What is Hadoop • History of Hadoop • How does Hadoop solve Big Data Problem • Components of Hadoop • Hadoop Flavours

Hadoop Distributed File System Part 1…...……………………………… 2 Hrs

• HDFS Architecture • HDFS Internals • HDFS Use Cases • HDFS Daemons • Files and Blocks • Namenode Memory Concerns • Secondary Namenode • HDFS Access Options


Installing Hadoop (Single Node)…......……..……….…………………… 1 Hrs

• Installation Overview • Hadoop Installation • Hadoop Daemons Stuff

Advanced Hadoop Distributed File System Concepts………….…… 2 Hrs.

• HDFS Workshops • HDFS API • How to use Configuration class • Using HDFS in MapReduce • Using HDFS Programmatically • HDFS Permission and Security • Additional HDFS Tasks • Rebalancing Blocks • Copying Large Sets of Files • Decommissioning Nodes • Verifying File System Health • Rack Awareness • HDFS Web Interface

Map-Reduce Workshops………...…..……………………………………....… 5 Hrs


Introduction to MapReduce ……….…………………………………..…… 3 Hrs

• MapReduce Basics • Functional Programming Concepts • List Processing • Mapping Lists • Reducing Lists • Putting them Together in MapReduce • An Example Application: Word Count • Understanding the Driver • Understanding the Mapper • Understanding the Reducer • MapReduce Data Flow • A Closer look • Additional MapReduce Functionality • Fault Tolerance

Advanced MapReduce Concepts…..……………………………………..…. 2 Hrs

• Understanding Combiners • Understanding Partitioners • Understanding input formats • Understanding output formats • Distributed Cache • Understanding Counters • More Tips • Chaining Jobs • Listing and Killing Jobs


Cloud Computing Overview………..…………………………...…….....…… 1 Hrs

• Cloud Computing Introduction • SaaS/PaaS/IaaS • Characteristics

Installing Hadoop (Multi Node)………..………………………..............…… 1 Hrs

• Cluster Configurations • Configuring Masters • Configuring Slaves • Cluster Stuff

Hadoop Ecosystem Pig ….………………………………………………………. 1 Hrs

• Pig Programs structure and Execution Process • Joins • Filtering • Group and Co-Group • Schema merging and redefining schema • Pig functions

Hadoop Ecosystem Hive…………………………………………………………. 2 Hrs

• Motivation and Understanding Hive • Using Hive Command line interface • Data types and File Formats • Basic DDL operations • Schema Design • An Example of Pig and Hive


Hadoop Ecosystem HBase and Zookeeper………….………………………. 1 Hrs

• HBase Overview • HBase Architecture • HBase Installation • HBase Admin : Test • HBase Client: Client Loading Overview • Fully Distributed HBase Configuration • Loading HBase • HBase Data Access

Hadoop Ecosystem Sqoop …………………………………………………. 1 Hrs

• Sqoop Overview • Sqoop Installation • Importing Data • Exporting Data

Hadoop Ecosystem Oozie………………………………………………..…. 1 Hrs

• Oozie overview • Oozie Features • Bundle • Scalability • Usability • Oozie challenges

Hadoop Ecosystem Apache Flume……………….…………………..……. 1 Hrs

• Apache Flume Overview • How it Works • Flume Connection with HDFS


Hadoop Version 2 Concepts …………………….………………………….. 2 Hrs

• Yarn • Hadoop Federation • Authentication in Hadoop • High Availability

Administration Refresher……………………………………………………… 1 Hrs

• Setting up Hadoop Cluster – Considerations • Most Important Configurations • Installation Options • Scheduling in Hadoop • FIFO Scheduler • FAIR Scheduler

Building a Web Log Analysis POC using MapReduce..…….……….…... 2 Hrs

• Designing Structures for POC • With MapReduce develop code • Push data using Flume into HDFS • Run MapReduce Code • Analyse the Output

Real Life Project and POC…………………………………….……….....……….... 6 Hrs


Training Methodlogy :

- 80% training is practical - The duration of course is 36 - 40 Hrs - Individual attention is provided to all candidates - Training involves multiple workshops to explain the practical concepts - Regular assignments will be given to the candidates - Study material, PPTs, Project and POC codes, etc. will be given to the candidates - Course involves 3 Proof Of Concepts - Course involves a Real Life Project - Trainer will assist you for interview preparation

About The Organizer :

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Our aim is to upgrade and set those key skills that are result oriented and bring organizational excellence by all means.

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Learn Hadoop at your Leisure time