MapReduce Architecture for Big Data
2.9 (51 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
11,545 students enrolled

MapReduce Architecture for Big Data

Importance of Combiner in Maprduce
2.9 (51 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
11,545 students enrolled
Last updated 2/2019
English
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Current price: $13.99 Original price: $19.99 Discount: 30% off
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This course includes
  • 38 mins on-demand video
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
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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
Course content
Expand all 5 lectures 38:15
+ Mapper and Reducer
2 lectures 17:01
MapReduce Mapper in Detail
11:36
MapReducer Reducer in Detail
05:25
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