This Hadoop Testing Online Training will provide you with the right skills to detect, analyze and rectify errors in Hadoop framework. You will be trained in the Hadoop software, architecture, MapReduce, HDFS, and various components like Pig, Hive, Sqoop, Flume and Oozie. You will be fully equipped in various test case scenarios, Proof of Concepts implementation and real world scenarios.
WHAT YOU WILL LEARN IN THIS HADOOP TESTING TRAINING?
- A clear understanding of the Hadoop and Hadoop ecosystems
- HDFS architecture, flow of data, data replication, Namenode and Datanode
- Master MapReduce concepts , Mapper and Reducer functions, Concurrency, Shuffle and Ordering
- Unit Testing of Hadoop Mapper on a Mapreduce application
- Deploy Pig for big data analysis and Hive for relational data analysis and test the application
- Deep understanding of Hadoop Testing and the Workflow process
- Design, formulate and implement Hadoop test scenarios, test cases and test scripts
- Using big data testing tools for detecting bugs and rectifying it
- Learn MRUnit framework for testing MapReduce jobs without Hadoop clusters
- Get trained for the Cloudera Hadoop Certification
WHO SHOULD TAKE THIS HADOOP TESTING COURSE?
- Big Data and Hadoop Developers
- Quality Assurance, tester, tech support and system administrators
WHAT ARE THE PREREQUISITES FOR LEARNING HADOOP TESTING?
No prerequisite is required to learn Hadoop testing.
WHY SHOULD YOU TAKE HADOOP TESTING COURSE?
- Global Hadoop Market to Reach $84.6 Billion by 2021 – Allied Market Research
- Shortage of 1.4 -1.9 million Big Data Hadoop Analysts in US alone by 2018– Mckinsey
- Hadoop Testing Professionals in the US can get a salary of $132,000 – indeed.com
Hadoop is being deployed across the board in enterprises around the world. With each passing day the scale and complexities of the task that Hadoop Big Data is expected to achieve is getting bigger. With more and more Hadoop developers and Hadoop architects deployed on Hadoop projects there is an equal and urgent necessity of Hadoop testers. This Big Data testing training will ensure that you gain the right skills which will open up opportunities in the Big Data testing domain as a Hadoop Tester.
Hadoop Job Market Is Hotting Up – Check The Facts Yourself!
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Hadoop Testing Course Content
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Introduction To Hadoop And Its Ecosystem, Mapreduce And Hdfs
Introduction to Hadoop and its constituent ecosystem, understanding MapReduce 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
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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
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Mapreduce
How to develop Map Reduce Application, writing unit test, Best Practices for developing and writing, Debugging Map Reduce applications
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Introduction To Pig & Its Features
What Is Pig?, Pig’s Features, Pig Use Cases, Interacting with Pig, 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
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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, 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
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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
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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.
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FRAMEWORK CALLED MR UNIT FOR TESTING OF MAPREDUCE PROGRAMS
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Framework Called Mr Unit For Testing Of Mapreduce 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 MapReduce programs.
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Unit Testing
Automation testing using the OOZIE, Data validation using the query surge tool.
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Test Execution Of Hadoop _Customized
Test plan for HDFS upgrade, Test automation and result
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Test Plan Strategy Test Cases Of Hadoop Testing
How to test install and configure Hadoop Testing Projects Project Work Project 1 – Working with MapReduce, Hive, Sqoop Problem Statement– It describes that how to import MySQL data using Sqoop and querying it using hive and also describes how to run the word count MapReduce job. Project 2 – Hadoop Testing using MR Problem Statement – It describes how to test MapReduce codes with MR unit.
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