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Big Data Testing:
This Hadoop Testing 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. With this Hadoop testing training 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?

  1. A clear understanding of the Hadoop and Hadoop ecosystems
  2. HDFS architecture, flow of data, data replication, Namenode and Datanode
  3. Master MapReduce concepts , Mapper and Reducer functions, Concurrency, Shuffle and Ordering
  4. Unit Testing of Hadoop Mapper on a Mapreduce application
  5. Deploy Pig for big data analysis and Hive for relational data analysis and test the application
  6. Deep understanding of Hadoop Testing and the Workflow process
  7. Design, formulate and implement Hadoop test scenarios, test cases and test scripts
  8. Using big data testing tools for detecting bugs and rectifying it
  9. Learn MRUnit framework for testing MapReduce jobs without Hadoop clusters
  10. 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

Hadoop Testing Course:
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

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

How to develop Map Reduce Application, writing unit test, Best Practices for developing and writing, Debugging Map Reduce applications



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