HADOOP BIG DATA Training from ZaranTech

HADOOP Professional Competency Development Program

We focus on delivering Role-Specific training rather than Product based Training

ZaranTech LLC. , http://www.zarantech.com, [email protected] , (515) 309-7846, Page - 1

5550 Wild Rose Lane, Suite 400, West Des Moines IA 50266

Course Title: Business Analyst Competency Development Program Course Duration: 45 hours Training Training Materials: All attendees would receive

Training presentation of each session,

Source Code for examples covered.

Training Format: This course is delivered as a highly interactive session, with extensive live examples. This course is delivered in Online using Web and Audio Conferencing.

What will you learn?

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

HADOOP Professional Role Based Training

Course Duration: 30-35 hours + Live Case

Studies

Prereq

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

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

Benefits:

Quality Course Material & E-books

24 x 7 Online access to trainers

for Doubts Clarification,

Project based training with hands on exp.

Resume Preparation Guidance

Mock Interviews from Professional

Consultants,

Marketing one-on-one with a Recruiter

Real-time Project Documents

Onsite Job assistance for 1 month

Special Project training programs for

trained F1 students on OPT or CPT.

Training Highlights:

Focus on Hands on training

35 hrs. + 30 Assignments, 2Live Case Studies

Video Recordings of sessions provided

Demonstration of Concepts using tools like

Eclipse, Tomcat Server and MySQL

One Problem Statement discussed across the Core Java, Servlets, JSP, EJB, Struts, Hibernate

HADOOP Certification Guidance

Resume prep, Interview Questions provided

SOA Fundamentals and Products covered

Cloud Computing for JAVA developers

Introduction to HADOOP and BIG DATA

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http://www.zarantech.com/

mailto:[email protected]





In this training, attendees learn: BASIC HADOOP

1. Introduction and Overview of Hadoop 2. Hadoop Distributed FileSystem (HDFS) 3. HBase – The Hadoop Database 4. Map/Reduce 2.0/YARN 5. MapReduce Workflows 6. Pig 7. Hive 8. Putting it all together

ADVANCED HADOOP

1. Integrating Hadoop Into The Workflow 2. Delving Deeper Into The Hadoop API 3. Common Map Reduce Algorithms 4. Using Hive and Pig 5. Practical Development Tips and Techniques 6. More Advanced Map Reduce Programming 7. Joining Data Sets in Map Reduce 8. Graph Manipulation in Hadoop 9. Creating Workflows With Oozie 10. HANDS ON EXCERCISE

Attendees also learn:

1. Resume Preparation Guidelines and Tips 2. Mock Interviews and Interview Preparation Tips attend?

Audience

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.

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Pre-Requisites

1. The participants should have at least basic knowledge of Java. 2. Any experience of Linux environment will be very helpful.

Advanced Map Reduce

Algorithms

Developing Map

Reduce Programs

Map Reduce Anatomy

Advanced Tips &

Techniques

Monitoring & Management of Hadoop

Using Hive & Pig

Hadoop Best Practices

and Use Cases

Deploying Hadoop on

Cloud

Sqoop

40 plus Assignments Case Studies

Certification Guidance

Resumes / Interview Guidance Mock Interviews (project & technical)

Hadoop Overview & its

Ecosystem

What is Big Data & Why Hadoop?

HDFS – Hadoop Distributed File System

HBase

HADOOP ROLE BASED TRAINING PROGRAM ROADMAP

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Topics covered:

BASIC HADOOP

Introduction and Overview of Hadoop 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) HDFS Overview and Architecture HDFS Installation HDFS Use Cases Hadoop File System Shell File System Java API Hadoop Configuration

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

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

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

Hive

Hive Overview Installation Hive QL

Putting it all together

Distributed installations Best Practices

ADVANCED HADOOP

Integrating Hadoop Into The Workflow

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

Delving Deeper Into The Hadoop API 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 Sorting and Searching Indexing Machine Learning With Mahout Term Frequency – Inverse Document Frequency Word Co-Occurrence Hands-On Exercise

Using Hive and Pig

Hive Basics Pig Basics Hands-on exercise

Practical Development Tips and Techniques 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

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

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

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

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

Interview Preparation 1. Mock Interviews 2. Interview Preparation Tips 3. Sample Interview Questions 4. How to clear an Interview

Take Away from the Course 1. Understanding of What and Why of Hadoop with its Eco-System Components. 2. Ability to write Map Reduce programs in a given scenario 3. Ability to correctly architect and implement the Best Practices in Hadoop Development 4. Ability to Manage and Monitor Hadoop 5. Ability to manage the different Hadoop Components when talking to each other.

About the trainer

1. 14 years of experience in consulting / training and mentoring participants on the design, infrastructure, integration aspects in the training.

2. 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.

3. 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].

4. 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.

5. 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.

6. 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.

7. 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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Healthcare System Application:

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.

CASE STUDY # 1 – “Healthcare System”

Tasks:

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 Zaran

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OTHER CASE STUDIES: Social Networking, Cruise Management System, Collegiate Sporting system

CASE STUDY # 2 – “Asset Management System”

Asset Management Application:

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.

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.

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.

The persistent storage is realized using an MySQL database. The business logic is realized using the J2EE/JEE

runtime system.

a storage subsystem managing persistent data a session subsystem controlling authentication, check out, and check in a notification subsystem sending past due notices an administration subsystem realizing administration requests a user interface subsystem translating HTTP requests into requests to other subsystems and translating

results into HTML pages.

Tasks:

Identify Features - Login Page, Customer Information, Asset Information etc.

Develop Prototype – HTML, JavaScript, CSS

Implement Functionality – Core Java, Servlets, JSP, Struts, Hibernate

Deploy and Test Application – Tomcat Server, Eclipse Zaran

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Education

HADOOP BIG DATA Training from ZaranTech