HADOOP BIG DATA Training from ZaranTech

HADOOP Professional Competency Development Program
We focus on delivering Role-Specific training rather than Product based Training

HADOOP Professional Role Based Training
Course Duration: 30-35 hours + Live Case
Studies
Prereq

Timings: Weekdays & Weekends (after work hrs)
Mode of Training: Online

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How Are We Different?
 We just don’t teach HADOOP Concepts but we share our real-time implementation experiences
to get the audiences ready to face customers and Implement Solutions.
 We don’t make HADOOP Developer but we make them Complete & Full-fledged HADOOP
Consultants by training them on Development, Administration & Application Design with Project
based real-time scenarios and several Case Studies for practice
 Our faculties are not just technical developers or trainers; they are industry experts and
consultants for fortune 500 companies who are highly capable of understanding the business and
know how technology can be closely connected with people and business.
 Our Role-Specific training differs from any other training company in the world

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Benefits:
Training Highlights:
 Quality Course Material & E-books
 Focus on Hands on training
 24 x 7 Online access to trainers
 35 hrs. + 30 Assignments, 2Live Case Studies
for Doubts Clarification,
Course  Video Recordings of sessions provided
Title: Business Analyst Competency Development Program
 Project based training with hands on exp.
Course  Demonstration ofTraining using tools like
Duration: 45 hours Concepts
Training Materials: All attendees would receive
 Resume Preparation Guidance
Eclipse, Tomcat Server and MySQL
 Mock Interviews from Professional
 One Problem Statement discussed across the
 Training presentation of each session,
Core Java, Servlets, JSP, EJB, Struts, Hibernate
Consultants,
 Source Code for examples covered.
 HADOOP Certification Guidance
 Marketing one-on-one with a Recruiter
 Resume prep, Interview Questions provided
Training Format: This course is delivered as a highly interactive session, with extensive live examples. This
 Real-time Project Documents
 SOA Fundamentals and Products covered
course is delivered in Online using Web and Audio Conferencing.
 Onsite Job assistance for 1 month
What will you learn?
 Cloud Computing for JAVA developers
 Special Project training programs for
 Introduction to HADOOP and BIG DATA
trained F1 students on OPT or CPT.

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The J2EE/JEE Training uses best practices and guidelines from Java Community Process (JCP®). The trainincontent

ZaranTech LLC. , http://www.zarantech.com, info@zarantech.com , (515) 309-7846, Page - 1
5550 Wild Rose Lane, Suite 400, West Des Moines IA 50266


In this training, attendees learn:
BASIC HADOOP
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Introduction and Overview of Hadoop
Hadoop Distributed FileSystem (HDFS)
HBase – The Hadoop Database
Map/Reduce 2.0/YARN
MapReduce Workflows
Pig
Hive
Putting it all together

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ADVANCED HADOOP
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Integrating Hadoop Into The Workflow
Delving Deeper Into The Hadoop API
Common Map Reduce Algorithms
Using Hive and Pig
Practical Development Tips and Techniques
More Advanced Map Reduce Programming
Joining Data Sets in Map Reduce
Graph Manipulation in Hadoop
Creating Workflows With Oozie
HANDS ON EXCERCISE

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Attendees also learn:
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2.

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Resume Preparation Guidelines and Tips
Mock Interviews and Interview Preparation Tips attend?

Audience

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This course is designed for anyone who is
1. Wanting to architect a project using Hadoop and its Eco System components.
2. Wanting to develop Map Reduce programs
3. A Business Analyst or Data Warehousing person looking at alternative approach to data analysis and
storage.



Pre-Requisites
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The participants should have at least basic knowledge of Java.
Any experience of Linux environment will be very helpful.

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HADOOP Role Based Training Program
Enhancements

HADOOP ROLE BASED TRAINING
PROGRAM ROADMAP
What is Big Data &
Why Hadoop?

Hadoop Overview & its
Ecosystem

Map Reduce Anatomy

Developing Map
Reduce Programs

Advanced Tips &
Techniques

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Monitoring &
Management of Hadoop

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Sqoop

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Deploying Hadoop on
Cloud

HDFS – Hadoop
Distributed File System

Advanced Map Reduce
Algorithms

Using Hive & Pig

Hadoop Best Practices
and Use Cases

HBase

40 plus Assignments
Case Studies
Certification Guidance
Resumes / Interview Guidance
Mock Interviews (project & technical)



Topics covered:
BASIC HADOOP

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Introduction and Overview of Hadoop
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What is Hadoop?
History of Hadoop.
Building Blocks - Hadoop Eco-System.
Who is behind Hadoop?
What Hadoop is good for and what it is not?

Hadoop Distributed File System (HDFS)
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HDFS Overview and Architecture
HDFS Installation
HDFS Use Cases
Hadoop File System Shell
File System Java API
Hadoop Configuration

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HBase - The Hadoop Database
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HBase Overview and Architecture
HBase Installation
HBase Shell
Java Client API
Java Administrative API
Filters
Scan Caching and Batching
Key Design
Table Design

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Map/Reduce 2.0/YARN
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Decomposing Problems into MapReduce Workflow
Using JobControl
Oozie Introduction and Architecture
Oozie Installation
Developing, deploying, and Executing Oozie Workflows



Pig
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Pig Overview
Installation
Pig Latin
Developing Pig Scripts
Processing Big Data with Pig
Joining data-sets with Pig

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Hive
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Hive Overview
Installation
Hive QL

Putting it all together
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Integrating Hadoop Into The Workflow
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ADVANCED HADOOP
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Distributed installations
Best Practices

Relational Database Management Systems
Storage Systems
Importing Data from RDBMSs With Sqoop
Hands-on exercise
Importing Real-Time Data with Flume
Accessing HDFS Using FuseDFS and Hoop

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Delving Deeper Into The Hadoop API
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More about ToolRunner
Testing with MRUnit
Reducing Intermediate Data With Combiners
The configure and close methods for Map/Reduce Setup and Teardown
Writing Partitioners for Better Load Balancing
Hands-On Exercise
Directly Accessing HDFS
Using the Distributed Cache
Hands-On Exercise

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Common MapReduce Algorithms
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Sorting and Searching
Indexing
Machine Learning With Mahout
Term Frequency – Inverse Document Frequency
Word Co-Occurrence
Hands-On Exercise

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Using Hive and Pig
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Hive Basics
Pig Basics
Hands-on exercise

Practical Development Tips and Techniques
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Debugging MapReduce Code
Using LocalJobRunner Mode For Easier Debugging
Retrieving Job Information with Counters
Logging
Splittable File Formats
Determining the Optimal Number of Reducers
Map-Only MapReduce Jobs
Hands-On-Exercise

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Custom Writables and WritableComparables
Saving Binary Data using SequenceFiles and Avro Files
Creating InputFormats and OutputFormats
Hands-On Exercise

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Joining Data Sets in MapReduce
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More Advanced MapReduce Programming
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Map-Side Joins
The Secondary Sort
Reduce-Side Joins

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Graph Manipulation in Hadoop
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Introduction to graph techniques
Representing graphs in Hadoop
Implementing a sample algorithm: Single Source Shortest Path



Creating Workflows With Oozie
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The Motivation for Oozie
Oozie’s Workflow Definition Format
HANDS ON EXERCISE

Interview Preparation

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Mock Interviews
Interview Preparation Tips
Sample Interview Questions
4. How to clear an Interview

Take Away from the Course
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Understanding of What and Why of Hadoop with its Eco-System Components.
Ability to write Map Reduce programs in a given scenario
Ability to correctly architect and implement the Best Practices in Hadoop Development
Ability to Manage and Monitor Hadoop
Ability to manage the different Hadoop Components when talking to each other.

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About the trainer
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14 years of experience in consulting / training and mentoring participants on the design,
infrastructure, integration aspects in the training.
Have trained more than 5,000 participants in the areas of Java, J2EE, Android and BPM and always
looking forward to share his knowledge in the IT domain with anyone.
Have extensively travelled and mentioned participants in different organizations in countries like RBC
[Luxemburg], Motorola [Germany],PayPal [Dublin],GVT [Brazil], Virtusa [Sri Lanka], Damac [Dubai],
Rogers Telecom [Canada],D&B, HBO, Micron, EMC, e-Rewards, Maximus [USA].
Have assisted and providing consulting to ADP, Diebold, Level 3 Communications, e- Rewards, South
West Airlines and other Corporates on their Process Requirements in the areas of BPM.
Have been on the Code Review Panel for multiple organizations for their product development
efforts and have brain stormed multiple new ideas which have turned into reality.
Was a part of the Core Initial Team for exploring HD Insight [Hadoop on Windows] for Microsoft India
Development Center and have mentored multiple batches of Developers, Project Managers and
Development Testers.
Have mentored participants in J P Morgan, TCS, HCL, Accenture in H1adoop and its eco-system
components like Hike, Hbase, Pig and Sqoop. Have also been involved in assisting the organizations in
setting up their initial Hadoop team.

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CASE STUDY # 1 – “Healthcare System”
Healthcare System Application:

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As the Product Manager for Inner Expressions you are asked to provide one of your largest clients with
additional features in the EMR (Electronic Medical Records Management) System. The client has requested an
integrated Referral Management System that tracks patients from Primary care into the Specialist
departments. Appointments are created by either the Primary Care Physicians themselves or other clinical staff
like Nurse Practitioners or Clinical Assistants. Each appointment must go through the appropriate checks
including checking if the patient has an active insurance with the client, whether the insurance program covers
the condition of the patient, patient’s preference for location and timings and availability of the Specialist
doctor.
Some appointments may have to be reviewed by the Specialists themselves before they can be approved, the
administrator of the facility (hospital) must have the ability to choose by appointment type to either make it
directly bookable by the Primary Care Staff or as a type that requires review by the specialist. The system
should also allow the Primary Care Staff and specialists departments to exchange notes and comments about a
particular appointment. If the specialist department requests tests or reports as mandatory for the
appointment, the system must ensure that the patient has these available on the date of the appointment.
The Hospital sets about 300 appointments per day and must support about 50 users at the same time. The
existing EMR system is based on J2EE/JEE and a MySQL database system.

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Tasks:
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Identify Features - Login Page, Customer Information, Facility Information, Appointments etc.
Develop Prototype – HTML, JavaScript, CSS
Implement Functionality – Core Java, Servlets, JSP, Struts, Hibernate
Deploy and Test Application – Tomcat Server, Eclipse

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CASE STUDY # 2 – “Asset Management System”
Asset Management Application:

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The asset management system keeps track of a number of assets that can be borrowed, their ownership, their
availability, their current location, the current borrower and the asset history. Assets include books, software,
computers, and peripherals. Assets are entered in the database when acquired, deleted from the database
when disposed. The availability is updated whenever it is borrowed or returned. When a borrower fails to
return an asset on time, the asset management system sends a reminder to the borrower and informs the asset
owner.

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The administrator enters new assets in the database, deletes obsolete ones, and updates any information
related to assets. The borrower search for assets in the database to determine their availability and borrows
and returns assets. The asset owner loans assets to borrowers. Each system has exactly one administrator, one
or more asset owners, and one or more borrowers. When referring to any of the above actor, we use the term
"user". All users are known to the system by their name and their email address. The system may keep track of
other attributes such as the owner's telephone number, title, address, and position in the organization.

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The system should support at least 200 borrowers and 2000 assets. The system should be extensible to other
types of assets. The system should checkpoint the state of the database every day such that it can be recovered
in case of data loss. Owners and the administrator are authenticated using a user/password combination.
Actors interact with the system via a web browser capable of rendering HTML and HTTP without support for
JavaScript and Java.

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Tasks:

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The persistent storage is realized using an MySQL database. The business logic is realized using the J2EE/JEE
 Identify
runtime system. Features - Login Page, Customer Information, Asset Information etc.
 Develop Prototype – HTML, JavaScript, CSS
 aImplement Functionality – Core Java, Servlets, JSP, Struts, Hibernate
storage subsystem managing persistent data

a session subsystem controlling authentication, check out, and check in
 aDeploy and Test Application – Tomcat Server, Eclipse
notification subsystem sending past due notices

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
administration
OTHER anuser STUDIES: subsystem realizing Cruise Management System, Collegiatesubsystems and translating
CASE interface subsystem translatingadministration requests
Social Networking,
Sporting system

a
HTTP requests into requests to other
results into HTML pages.


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