Big Data and Hadoop for Absolute Beginners
Big data is a term used to refer large data sets that is very complex for traditional data-processing application softwares to adequately process it. Big data are originally associated with three key concepts which are, volume, variety, and velocity. This course covers main Big Data topics such as Hadoop, Map-Reduce and YARN.
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Big Data and Hadoop for Absolute Beginners
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Includes
  • 5 Hrs of lecture Videos
  • 73 hands-on practice exercises
  • 12 Assessment exercises
  • 210 knowledge based questions
  • Lifetime access
About the Course

This course helps you to understand the detailed introduction about the tools used to process Big Data, storage in HDFS and retrieval using HBase, Resource allocation by YARN Customizing, Testing and Debugging MapReduce.

Course Objectives

Upon successful completion of the course, the learner will be able to

  • Learn about Big Data, storing and retrieval of Big Data in HDFS and HBase.

  • Learn about processing, testing and debugging the Big Data using Map Reduce.

  • Learn about Resource allocation using YARN

Course Content
Introduction to Big Data

In this module, you will learn about the list of Big Data elements, various types of Big Data and the importance of structuring data. You will be learning the usage of Big Data across industries, career opportunities in Big Data, significance of Social Media data in business context, application of Big Data for fraud management in the financial sector, fraud management in Insurance using Big Data, application of Big Data in Retail Industry and the concept of distributed computing in relation to Big Data.

  • 2 Videos
  • 2 Hrs
  • 40 Problems
Understanding the Hadoop 2 Ecosystem

In this module, you will learn about the various components of the Hadoop 2 Ecosystem, process of storing files in Hadoop Distributed File System (HDFS), role of Hadoop MapReduce and the process of storing data with HBase. You will be learning how Hive aids mining Big Data, roles of various components of Hadoop ecosystem such as Zookeeper, Sqoop, Oozie and Flume, role of map and reduce in MapReduce, techniques to optimize MapReduce tasks, roles HBase and Hive play in processing of Big Data and some applications of MapReduce.

  • 2 Videos
  • 2 Hrs
  • 40 Problems
Storing data in Hadoop 2 - HDFS and HBase

In this module, you will learn about the Hadoop Distributed File System (HDFS), how to work with HDFS files, the role of HDFS Federation, the architecture and the role of HBase. You will be learning the characteristics of HBase schema design, how to implement basic programming for Hbase, the best capabilities of HBase and HDFS for effective data storage.

  • 3 Videos
  • 18 Hrs 15 Mins
  • 75 Problems
Working with MapReduce on YARN

In this module, you will learn about the MapReduce 2 framework, how to apply the steps to build and execute a basic MapReduce on YARN program, how to apply various techniques for designing MapReduce implementation, process of building joins with MapReduce and the techniques to build iterative MapReduce applications.

  • 2 Videos
  • 10 Hrs 15 Mins
  • 51 Problems
Customizing MapReduce fundamentals

In this module, you will learn about the implement controlling of MapReduce execution with InputFormat, implement reading data with custom RecordReader, organize output data with custom OutputFormats, how to write data with custom RecordWriter, how to optimize MapReduce execution with a combiner and the implement controlling reducer execution with partitioners.

  • 2 Videos
  • 4 Hrs 15 Mins
  • 34 Problems
Testing and Debugging MapReduce Applications

Module description In this module, you will perform unit testing of MapReduce applications using MRUnit, perform local testing of MapReduce applications and use logging for Hadoop testing.

  • 2 Videos
  • 1 Hrs
  • 30 Problems
Working with YARN

In this module, you will learn about the advantages of YARN over MapReduce in Hadoop 1.0, YARN ecosystem, YARN architecture, key concepts of YARN API and the schedule jobs with YARN.

  • 2 Videos
  • 1 Hrs 15 Mins
  • 25 Problems
You will Learn through our Scientifically Designed & Proven 5 Step Practice Oriented Learning Process
iLearn
In this session, you will find video lectures and other resources to learn the concepts.
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In this session, you will start designing and creating your own programs.
iExplore
In this session, you will find interesting set of activities which will make you explore more on the specific topic.
iAssess
In this session, you will have activities to self assess your knowledge and skills on the specific topic.
iAnalyse
In this session, you will find varieties of exercises to improve your code analysis, testing and debugging skills.
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Harihara Budra P, XII std

Harihara Budra P, XII std
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