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Course Curriculum

Module 1 – Introduction to Hadoop and its Ecosystem, Map Reduce and HDFS
  • Big Data, Factors constituting Big Data
  • Hadoop and Hadoop Ecosystem
  • Map Reduce -Concepts of Map, Reduce, Ordering, Concurrency, Shuffle, Reducing, Concurrency
  • Hadoop Distributed File System (HDFS) Concepts and its Importance
  • Deep Dive in Map Reduce – Execution Framework, Partitioner, Combiner, Data Types, Key pairs
  • HDFS Deep Dive – Architecture, Data Replication, Name Node, Data Node, Data Flow
  • Parallel Copying with DISTCP, Hadoop Archives
Module 2 – Hands on Exercises
  • Installing Hadoop in Pseudo Distributed Mode, Understanding Important configuration files, their Properties and Demon Threads
  • Accessing HDFS from Command Line
  • Map Reduce – Basic Exercises
  • Understanding Hadoop Eco-system
  • Introduction to Sqoop, use cases and Installation
  • Introduction to Hive, use cases and Installation
  • Introduction to Pig, use cases and Installation
  • Introduction to Oozie, use cases and Installation
  • Introduction to Flume, use cases and Installation
  • Introduction to Yarn
Mini Project – Importing Mysql Data using Sqoop and Querying it using Hive Module 3 – Map Reduce
  • How to develop Map Reduce Application, writing unit test
  • Best Practices for developing and writing, Debugging Map Reduce applications
Module 4 – Pig 1. Introduction to Pig
  • What Is Pig?
  • Pig’s Features
  • Pig Use Cases
  • Interacting with Pig
2. Basic Data Analysis with Pig
  • Pig Latin Syntax
  • Loading Data
  • Simple Data Types
  • Field Definitions
  • Data Output
  • Viewing the Schema
  • Filtering and Sorting Data
  • Commonly-Used Functions
  • Hands-On Exercise: Using Pig for ETL Processing
Module 5 – Hive 1. Introduction to Hive
  • What Is Hive?
  • Hive Schema and Data Storage
  • Comparing Hive to Traditional Databases
  • Hive vs. Pig
  • Hive Use Cases
  • Interacting with Hive
2. Relational Data Analysis with Hive
  • Hive Databases and Tables
  • Basic HiveQL Syntax
  • Data Types
  • Joining Data Sets
  • Common Built-in Functions
  • Hands-On Exercise: Running Hive Queries on the Shell, Scripts, and Hue
Module 6 – Hadoop Stack Integration Testing
  • Why Hadoop testing is important
  • Unit testing
  • Integration testing
  • Performance testing
  • Diagnostics
  • Nightly QA test
  • Benchmark and end to end tests
  • Functional testing
  • Release certification testing
  • Security testing
  • Scalability Testing
  • Commissioning and Decommissioning of Data Nodes Testing
  • Reliability testing
  • Release testing
Module 7 – Roles and Responsibilities of Hadoop Testing 
  • Understanding the Requirement, preparation of the Testing Estimation, Test Cases, Test Data, Test bed creation, Test Execution, Defect Reporting, Defect Retest, Daily Status report delivery, Test completion.
  • ETL testing at every stage (HDFS, HIVE, HBASE) while loading the input (logs/files/records etc) using sqoop/flume which includes but not limited to data verification, Reconciliation.
  • User Authorization and Authentication testing (Groups, Users, Privileges etc)
  • Report defects to the development team or manager and driving them to closure.
  • Consolidate all the defects and create defect reports.
  • Validating new feature and issues in Core Hadoop.
Module 8 – Framework called MR Unit for Testing of Map-Reduce Programs
  • Report defects to the development team or manager and driving them to closure.
  • Consolidate all the defects and create defect reports.
  • Validating new feature and issues in Core Hadoop
  • Responsible for creating a testing Framework called MR Unit for testing of Map-Reduce programs.
Module 9 – Unit Testing
  • Automation testing using the OOZIE.
  • Data validation using the query surge tool.
Module 10 – Test Execution of Hadoop _customized
  • Test plan for HDFS upgrade
  • Test automation and result
Module 11 – Test Plan Strategy Test Cases of Hadoop Testing
  • How to test install and configure

Hadoop Testing training

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Hadoop Testing training

Hadoop Testing training institutes in marathahalli bangalore Hadoop Testing Training course is to make you enable to learn and understand …


    Hadoop Testing training institutes in marathahalli bangalore

    Hadoop Testing Training course is to make you enable to learn and understand to test and rectify errors from Hadoop projects performance. This course will enable you to learn about Hadoop Software, Hadoop Architecture, HDFS, Mapreduce Jobs, Hive, PIG, POC and lab exercise.

    Learning Objectives:

    • Setting up Hadoop infrastructure with single and multi node cluster on Amazon ec2 (CDH4).
    • Writing Hive and Pig Scripts and working with Sqoop.
    • Work on a Real Life Project on Big Data Testing and gain Hands on Project Experience.
    • Guidance and Quiz to prepare for Professional Certification exams like – Cloudera, etc.
    • Ability to design and test Hadoop Testing Training applications involving large data using MRUnit testing Framework.

    Recommended Audience:

    This course is recommended for:

    • QA Professionals aspiring to make a career in Big Data Analytics using Hadoop Framework.
    • System Administrators and Support Engineers who will test Hadoop works


    • Basic knowledge of QA
    • Basic knowledge of Unix, sql scripting
    • Prior knowledge of Apache Hadoop is not required

    Why Go for Hadoop Testing Training?

    Hadoop Testing Training is a combination of online running applications on a very huge scale built of commodity hardware. Hadoop is uncluttered source software which is handled by the Apache Software Foundation and it’s very helpful in storing and handling huge amounts of data inexpensively and professionally. Basically Hadoop collects huge packets of data and classifies this data using MapReduce.

    If you are looking for Hadoop Jobs and you are a Hadoop professional then there are a lot of jobs about Hadoop and related technologies. There are many companies like Google, Yahoo, Apple, Hortonworks, eBay, Facebook, ORACLE, IBM, Microsoft, and CISCO which are looking for skilled professionals having experience in this field and are capable of managing the Big Data in their companies. If you are a professional of Hadoop then you could be one of them. These companies such as Google, Facebook, and ORACLE etc are looking for the Hadoop Professionals at different levels such as database Administrators, Hadoop Professionals having complete operational skills, Hadoop engineers & also senior Hadoop engineers, big data Engineers, Hadoop developers and also Java Engineers (DSE Team).

    Research of IDC shows that the Big Data market revenue’s will grow at 31.7 percent a year and it will hit the $23.8 billion mark in 2016. According to the latest research by market the Hadoop and Big Data world widely is expected to growth about 13.9$ billion by 2017.

    Hadoop QA Professional: Hadoop QA professional is a person who tests and rectifies glitches in Hadoop and its Data base system.

    Companies Using Hadoop:

    Amazon Web Services, IBM, Hortonworks, Cloudera, Intel, Microsoft, Pivotal, Twitter, Salesforce, AT&T Stumbleupon, Ebay, Yahoo, Facebook, Hulu etc.

    Career Opportunities after Hadoop course:

    Google trends tell exponential growth of Jobs in Hadoop. Check Top Job websites for Hadoop Jobs:

    Indeed: 11000+

    Simplyhired: 12000+

    LinkedIn: 4500+ 8000+

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    This course is designed for clearing Cloudera Certification for Hadoop. At the end of the course there will be a quiz and project assignments once you complete them you will be awarded.

    Self Paced vs Instructor LED Online

    Self-Paced Courses

    • Students learn via video tutorials which can be played multiple times
    • This is a self –learning course and Learners choose their own study time
    • 24*7 support for queries and doubts clearance over email.  Session with a trainer can be arranged if required
    • Very affordable. 75% cheaper than online instructor-led courses
    • Lifetime access to video tutorials with free upgrade to latest topics

    Online Training – Instructor-Led

    • Students learn in a virtual classroom from a trainer
    • Course follows a set time table and duration where Learners can log in at the allocated time only
    • Queries addressed only in the live session
    • Costlier than self-paced

    Key Features:

      High quality interactive e-learning sessions for Self paced course. For online instructor led training, total course will be divided into sessions.
      Each module will be followed by practical assignments and lab exercises to exercise your learning . Towards the end of the course, you will be working on a project where you be expected to create a project based on your learning . Our support team is available to help through email, phone or Live Support for any help you require during Lab and Project work.
      We provide 24X7 support by email for issues and doubts in course for Self-paced training. For online training, trainer will be open to help you out 24X7 via email/ phone for any queries regarding the course. If required, the support team can also provide you live support by accessing your machine remotely. This ensures that all your doubts and problems faced during labs and project work are clarified round the clock.


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