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    MapReduce Architecture for Big Data

    Posted By: Sigha
    MapReduce Architecture for Big Data

    MapReduce Architecture for Big Data
    .MP4 | Video: 1280x720, 30 fps(r) | Audio: AAC, 44100 Hz, 2ch | 180 MB
    Duration: 38 mins | Genre: eLearning Video | Language: English

    Importance of Combiner in Maprduce


    What you'll learn

    In this module, we will understand what is Map Reduce and what is the necessity of Map reduce in big data world

    Requirements

    Basic knowledge of Java
    Knowledge of programming would be beneficial
    Experience of coding

    Description

    MapReduce Architecture for Big Data:

    In this module, we will understand what is Map Reduce and what is the necessity of Map reduce in big data world, We will learn how map reduce is different from traditional programming and map reduce framework as a whole. MapReduce is a programming model suitable for processing of huge data thus are very useful for performing large-scale data analysis using multiple machines in the cluster.

    The tutorials will include the following :

    1.Introduction to Mapreduce
    2.Data Flow Architecture of Mapreduce
    3.Concept of Mapper
    4.How Reducer works
    5.Importance of Combiner in Maprduce
    6.Understanding Partitioner
    7.Input Format
    8.Speculative Execution
    9.Input split VS Block
    10.Counters
    11.Job Optimization and Performance Tuning
    12.Example on how Map and Reduce work
    13.Implementing example of Map and Reduce programmatically.

    Who this course is for:

    Mapreduce Beginners
    Professionals who want to learn Mapreduce
    Graduates looking to build a career in Big Data Analytics
    Anyone who wants to learn a Big Data

    MapReduce Architecture for Big Data