Big Data With Mapreduce - Hands-On

[LeeAndro]

Published 6/2022MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHzLanguage: English | Size: 1.10 GB | Duration: 2h 59m

Master concepts and applications of MapReduce in Big Data

What you'll learn
You will learn how to work with mass data, unstructured data
Working with various kinds of data and try to get all of them on the same page anyway is what you will study here.​

In addition to data processing, you will also learn to develop a program in HIVE, PIG, MapReduce, and Sqoop.
You will see and learn how the sub-modules of Hadoop like PIG or HIVE could be used to reduce the complexity of the program.
Requirements
MapReduce or Hadoop is something that people get barely get exposure to as compared to the programming languages. It could be considered a unique technology. So it is obvious that one must have to possess below skills to being learning the MapReduce certification course. Programming Fundamental: You must know the basics of programming as you will be supposed to write programs in HIVE, PIG and so on. Though it is not the sole of Hadoop, you should have some idea about coding. Good Communication: As the processed outcome has to be presented to the next action takers, you should have good communication skills. Well, not just here but everywhere you must have some unique to present data. Analysis fundamentals: MS Excel provides us an interface where we can work with data. Thought the size of data is not that much but still, it gives you an idea of how the data could be processed.
Description
MapReduce can be defined as the sub-module of Hadoop that offer huge scalability of data spread across numerous of commodity clusters. MapReduce comprises of two things that work consecutively to process the analytics. The process in both the different parts is done in a parallel manner helping save a lot of while working with significant data. In the traditional data analysis approach, the data was analyzed serially and MapReduce overcomes that problem.As it's named sound, it involves mapping and reducing process which is done by mappers and reducers. The dataset gets divided equally among different mappers and all of the processes or analyses the data in a parallel manner. Once the mapper produces the outcome, reducers come in to generate the outcome. The role of the reducer is to collect the data from all the mappers and then process their outcome to get the final result.For instance, if Flipkart needs to find out the total sell in 2018 in Mumbai. The entire process will flow below.The entire dataset will be divided into months which means the sell data of one year will be divided into 12 months like how much they made each month from which location.The dataset will be then assigned to 12 mappers.Each mapper will find out in which city and how of how much the goods were sold.After the mappers generate the report, now it comes to the turn of reducers.The reducers will grab the sell value from every month for Mumbai location.Eventually, they will all sell value to generate the outcome.In this MapReduce training course, you will learn something that is going to be the next big thing soon, generating lots of opportunities in the new future. You will learn how to work with mass data, unstructured data. Working with various kinds of data and try to get all of them on the same page anyway is what you will study here. In technical terms, you will be getting a practical insight into the working of data scientists. In addition to data processing, you will also learn to develop a program in HIVE, PIG, MapReduce, and Sqoop.Every organization has its requirement for data analysis so it is very important to develop a customized program that can generate the desired output. You will see and learn how the sub-modules of Hadoop like PIG or HIVE could be used to reduce the complexity of the program. In addition to all those vital things, you will learn which framework should you use and in which case. By the you come to the end of the MapReduce certification, you will be enough cognizant to play with abundant data.

Overview

Section 1: MapReduce Fundamentals

Lecture 1 Secondary Sort Hadoop

Lecture 2 Creating Composite Key

Lecture 3 Continue on Composite Key

Lecture 4 Word Count Group

Lecture 5 Importance of Partition

Lecture 6 Hadoop FS - LS

Lecture 7 Joins in Hadoop

Lecture 8 Creating Configuration Object

Lecture 9 Setup Method

Lecture 10 Map Side Join Mapper

Lecture 11 Hadoop Commands

Lecture 12 Combiner in Hadoop

Lecture 13 Continue on Combiner in Hadoop

Lecture 14 Uploading Combiner Jar

Lecture 15 Introduction to Real World

Lecture 16 Ratings Mapper

Lecture 17 Movie and Ratings Runner

Lecture 18 Movie and Rating Calc Jar

Lecture 19 Total Ratings By A User

Lecture 20 User Rating Reducer

Lecture 21 User Rating Class

Lecture 22 Yarn Basic Tutorial

Lecture 23 Node Manager

MapReduce is the kind of technology that needs some prior experience as data analytics to learn it efficiently. It is kind of a vast topic and hence mostly preferred by working professionals. So if we talk about the target audience. Of course, working folks will be the best audience who can opt for this MapReduce certification course to enhance their expertise. Coming to students, most of them prefer to have internships to b their professional careers. So all the students who want to work as an intern in reputed organizations should learn MapReduce as it can give a good kick start to their career. By using several modules taught here like HIVE or PIG, students can leverage it to make some basic projects as well. People who are working in any other domain of information technology but wants to jump in as data scientists could be the perfect audience for this MapReduce certification course as nothing is best than a person willing to learn. Though it will be a bit hard to b the things right after chag the domain, it's also true that it won't take much to have you dive deep into this technology.

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