MapReduce Architecture for Big Data

[Bo0mB0oma]

 

 

MapReduce Architecture for Big Data

.MP4 | Video: 1280x720, 30 fps® | 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

 

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