Hadoop & Big Data Administration

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Things keep changing, and when in IT, you should know that the rule of the game is to understand the new wave and ride it when its there.In our Hadoop Big Data training course, we have designed by industry experts considering current industry job requirements to provide in-depth learning on big data and Hadoop Modules.We have two different certification training courses, which will prepare you to clear Cloudera Hadoop big data certification.

  • Cloudera Certified Hadoop Developer
    Cloudera Certified Hadoop Administrator

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  • bullets9 Completely hands on and project driven training
  • bullets9 Labs are created on your machine – you do it yourself with our trainer’s guidance
  • bullets9 If your system is not capable enough to run lab, lab servers can be provided as separate arrangements
  • bullets9 All sessions are recorded and are given for you to download and watch repeatedly
  • bullets9 You get access to a learning management system which is prepopulated with huge library of study materials which include PPTs, previous class recordings, quizzes and practice exams to help you prepare for real certification exams and track your training progress.
  • bullets9 On successful completion of your training and passing the online exam from LMS at the end will award you with a certificate of completion.
  • bullets9 You can discuss your career questions directly with our experienced faculty, even before you join or register for the course
  • bullets9 Industry Experienced Trainer – Theory can be taught by anyone, but real training comes from knowing real experiences

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Hadoop Administration Course Syllabus

Introduction to Big Data & Hadoop and its Ecosystem

  1. What is Big Data.
  2. Where does Hadoop Fit in?

Introduction to Hadoop Ecosystem software


Hadoop Architecture and Cluster setup

  1. Hadoop server roles and their usage
  2. Installation and Configurations
  3. Deploy a single node cluster
  4. Deploy a multi node cluster

Hadoop Cluster Administration

  1. Understanding Secondary Namenode
  2. Decommissioning and Commissioning of nodes
  3. Understanding Map – Reduce
  4. Understanding Job Schedulers

Backup, Recovery and Maintenance


Key Admin Commands

    1. Balancer
    2. Trash
    3. Distcp
    4. Data Backup and recovery

Enabling Trash
Manual Failover


Hadoop Cluster Planning & Management

  1. Planning Hadoop Cluster
  2. Hardware, network, Disk Space and Software Consideration
  3. Popular Hadoop Distribution

Hadoop 2.x and Its Features

  1. Limitations of Hadoop 1.x
  2. features of Hadoop 2.0
  3. YARN framework, MRv2
  4. Hadoop high availability and federation
  5. yarn ecosystem and Hadoop 2.0 Cluster setup

Setting up Hadoop High Availability

  1. Configuring Hadoop 2 with high availability
  2. upgrading to Hadoop 2

Hadoop Developer Course Syllabus

Introduction to Big Data & Hadoop and its Ecosystem

  1. What is Big Data.
  2. Where does Hadoop Fit in?
  3. Introduction to Hadoop Ecosystem software.

Hadoop Architecture

  1. Components of Hadoop
  2. Functions of different components
  3. Difference between Hadoop 1.x & 2.x

Map Reduce

  1. Details discussion about architecture of Map Reduce
  2. Different components of Map Reduce
  3. Map Reduce Example
  4. Lab Session

Hadoop Installation and Setup

  1. Hadoop Cluster Modes
  2. Psudo Distributed Cluster setup
  3. Fully Distributed Cluster setup
  4. Explanation of Hadoop Configurations.

Practical Session

  1. Accessing HDFS
  2. Saving and retrieving data from HDFS
  3. Running Map-Reduce Jobs
  4. Optimizing Map Reduce
  5. Looking at various components of Mar Reduce in Action

Deep Dive into Hive

Hive Introduction

  • Understanding Hive Architecture
  • Relational Database vs Hive
  • Storing Data in Hive
  • Hive Schema

Hive for Data Analysis

  • Understanding HQL
  • Basic Syntax
  • Table & Databases
  • Data Types
  • Hive Queries

Data Management with Hive
Optimizations in Hive
UDFs
Lab Session


Sqoop

  1. Introduction to Sqoop
  2. Sqoop Installation
  3. Importing Data from RDBMS
  4. Saving Imported data into HDFS
  5. Lab Session

Flume


Oozie


HBase

  1. Introduction to HBase
  2. Application of HBase
  3. Understanding HBase data model
  4. Accessing HBase Tables through Hbase-shell
  5. HBase API
  6. Lab Session

Apache Spark

  1. Understanding Apache Spark
  2. Difference between Spark and Hadoop
  3. Working with data in Spark
  4. Spark RDDs
  5. Transformation and Actions in Spark
  6. Lab Session

Project

Putting all the different components together to demonstrate a real-life data processing environment.


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Q. What is the prerequisite for this training?

To learn the core concepts of big data and hadoop ecosystem, the two important skills that professional must know are –Java and Linux.Keeping that in mind we have added one complementary course named "Just enough Java and Linux"with our Hadoop Administration and developer course .

Q.What are the career prospects in this field?

Hadoop is the hottest technology right now. So making a career shift towards Hadoop might seem like the best thing to do.By 2018, the Big Data market will be about $46.34 billion dollars worth. This is as per an IDC forecast.The Government and Federal agencies of several countries are now beginning to adopt Hadoop because of its open source nature and distributed computing capabilities.Professionals who have graduated from college few years ago and who are not into any of the big data positions are enthusiastic to know about the skills and knowledge required to apply for most of the open big data positions. With novel and lucrative career opportunities in Big Data and Hadoop, this is the right time for professionals to learn hadoop, one of the most complex and challenging open source framework.

Q.Can I learn Hadoop if I am not from  java backgrounds?

There is a myth that only professionals with experience in java programming background can learn hadoop. However, the reality is that professionals from Business Intelligence (BI) background, Data warehouse (DW) background, SAP background, ETL background, Mainframe background or any other technology domain can start learning hadoop as most of the organizations across various industries are now moving to Hadoop technology for storing and analysing petabytes of data.

  • For professionals from BI background, learning Hadoop is necessary because with data explosion it is becoming difficult for traditional databases to store unstructured data. Hadoop still has a long way to go when it comes to presenting clean and readable data solutions. BI professionals still use EDW and HDFS is unlikely to replace EDW. but there are many situations where Hadoop is much better suited than EDW. Hadoop does extremely well with file based data which is voluminous and diverse. This is where the traditional DBMS falls short. Professionals working in the BI domain can use BI equivalent of Hadoop popularly known as Pentaho.
  • For data warehousing professionals - it is a good time to learn Hadoop. Firms like Deutsche Telekom, EDF, HSBC, ING Vysya Bank all bet huge on Hadoop being the core data framework. But then all experts agree that Hadoop adds more to any data framework than it substracts. Data warehousing professionals are not going to lose their jobs - nor is EDW going to be completely replaced by Hadoop.Adding Hadoop to their skills is only going to open up more career options for data warehousing professionals. 3-4 years ago, when Hadoop was still relatively new, there was a sense that it was going to replace relational databases. But then it is all a question of using the right tools for the right job. Hadoop is not suitable for all kinds of data.No one can ignore the many benefits of Hadoop over data warehouses - but that does not mean that data warehouses are going to become the Mainframes of the 21st century. There is a huge legacy value in data warehouses - for say, transaction processing with focused index oriented queries. Hadoop will indeed provide an alternate platform for data analysis.
  • For professionals from Java background, the next most obvious progression in career is that of a Hadoop Developer or Administrator. Hadoop-Java is the most in-demand IT skill in the tidal wave of big data.
  • For professionals from ETL background, learning hadoop is the next logical step as they can use a combination of data loading tools like Flume and Sqoop along with Pig and Hive for analysis.
  • For professionals from DBA background or with expertise in SQL, learning hadoop can prove to be highly beneficial as it helps professionals translate their SQL skills for analysis using HiveQL (similar to that of SQL -key tool used for by hadoop developers for analysis). If we look at LinkedIn statistics, there is a downswing of 4% in profiles that have SQL but there is an upswing of 37% with profiles that have hadoop skill.

Q.Can I get certified after this training?

Both of our hadoop courses(Admin & Developer) has been created following Cloudera certification curriculum.So these trainings will definitely help you to pass the exam and get certified.

Q.How do I Register and Schedule my Cloudera exam?

Follow the link on each exam page to the registration form. Once you complete your registration on university.cloudera.com, you will receive an email with instructions asking you to create an account at examslocal.com in order to schedule your exam.

 

 

 

Corporate Training

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Hadoop is a free, Java-based programming framework that supports the processing of large data sets in a distributed computing environment. It is part of the Apache project sponsored by the Apache Software Foundation. Hadoop is composed of four core components—Hadoop Common, Hadoop Distributed File System (HDFS), MapReduce and YARN.

Hadoop Common
A module containing the utilities that support the other Hadoop components.

MapReduce
A framework for writing applications that process large amounts of structured and unstructured data in parallel across a cluster of thousands of machines, in a reliable, fault-tolerant manner.

HDFS
A file system that provides reliable data storage and access across all the nodes in a Hadoop cluster. It links together the file systems on many local nodes to create a single file system.

Yet Another Resource Negotiator (YARN)
The next-generation MapReduce, which assigns CPU, memory and storage to applications running on a Hadoop cluster. It enables application frameworks other than MapReduce to run on Hadoop, opening up a wealth of possibilities.

Hadoop is supplemented by an ecosystem of Apache open-source projects that extend the value of Hadoop and improve its usability.


 

  • Regular classes - 4 weeks
  • Weekend Classes - 6 weeks
  • Customized Fast Track option is available as well. Call +91-8049202039 now to customize according to your requirement
  • Experienced IT professionals
  • Having hands on practical knowledge
  • With experience of training large batches in both offline and online mode
  • Online Self Paced Training (SPT) with Videos and Documents
  • Online Instructor Led Training (ILT)

About the course:


Study9 provides a robust job market focused Hadoop training. Our Hadoop course is designed with the right mix of basic and advanced topics to get one started in the domain and enable a person to get a good job in this competitive market. Our Hadoop trainers are experienced professionals with hands on knowledge of Hadoop projects. The Hadoop course content is designed with keeping the current job market's demands in mind.Our Hadoop training course is value for money and tailor made for our students.

About Study9 Training Method


The Study9 Hadoop training courses are completely online training courses. The online Hadoop training is given using advanced training softwares to make the students comfortable with the online training. The student and teacher can talk over VOIP software, they can share each others screens, share Hadoop course contents and concerns during the class through chat window and even can see each other using Webcams. The time tested proven online Hadoop training methodologies adopted by study9 are of the most advanced ones in India. The student will feel at ease with the Hadoop training mode. And we are so confident on that, we offer a moneyback if the student is not satisfied with first Hadoop Training class.

The cloud based Hadoop training course contents are accessible from anywhere in the world. Study9 provides access for each student to an online Learning Management System that holds all the slides and videos that are part of the Hadoop training courses. The students can access them from their Laptop, Mobile, Tablets etc. The students will also give Hadoop training exams on this Learning Management System and our expert Hadoop trainers will rate their papers and provide certifications on successful completion of these Hadoop training exams.

The best part of this online Hadoop training approach is that it does not require one to waste time by travelling to a particular Hadoop training center. And the timings are flexible so that if someday the student has problems in taking the morning Hadoop training class he/she can fix an alternate time in the evening in discussion with Hadoop trainer. On need basis our Hadoop trainers can take a class in late night as well. On request basis missed Hadoop training class sessions can even be given as video lectures to the student for them to go through to be prepared for the next class.