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Big Data Hadoop Training Course Content

Big Data Hadoop Testing Course Content Chapter 1 : Understanding Big Data and Hadoop 1.1 Understand Big Data 1.2 Limitations…

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    Big Data Hadoop Testing Course Content

    Chapter 1 : Understanding Big Data and Hadoop

    • 1.1 Understand Big Data
    • 1.2 Limitations of the existing solutions for Big Data problem
    • 1.3 How Hadoop solves the Big Data problem
    • 1.4 The common Hadoop ecosystem components
    • 1.5 Hadoop Architecture
    • 1.6 HDFS
    • 1.7 Anatomy of File Write and Read
    • 1.8 Rack Awareness

    Chapter 2 : Hadoop Architecture and HDFS

    • 2.1 Hadoop Cluster Architecture
    • 2.2 Important Configuration files in a Hadoop Cluster
    • 2.3 Data Loading Techniques

    Chapter 3 : Hadoop MapReduce Framework – I

    • 3.1 Hadoop MapReduce framework and the working of MapReduce on data stored in HDFS

    Chapter 4 : Hadoop MapReduce Framework – II

    • 4.1 Input Splits in MapReduce
    • 4.2 Combiner & Partitioner and Demos on MapReduce using different data sets

    Chapter 5 :Advanced MapReduce

    • 5.1 Advanced MapReduce concepts such as Counters, Distributed Cache, MRunit, Reduce Join, Custom Input Format, Sequence Input Format
    • 5.2 How to deal with complex MapReduce programs.

    Chapter 6 :Pig

    • 6.1 Introduction to Pig
    • 6.2 Types of use case we can use Pig
    • 6.3 Tight coupling between Pig and MapReduce
    • 6.4 Pig Latin scripting

    Chapter 7 : Hive

    • 7.1 Introduction to Hive concepts
    • 7.2 Querying Data in Hive and Hive UDF

    Chapter 8 : Oozie and Hadoop Project

    • 8.1 Understand working of multiple Hadoop ecosystem components together in a Hadoop implementation to solve Big Data problems
    • 8.2 We will discuss multiple data sets and specifications of the project.
    • 8.3 Sqoop demo and Apache Oozie Workflow Scheduler for Hadoop Jobs.

    Chapter 9 : Realtime Usescases

    • 9.1 Realtime usecases along with sample datasets and running big data jobs

    Chapter 10 : Live Projects

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