課程資料
報名日期
全年招生
課程級別
學習模式
修業期
5 小時 55 分鐘
教學語言
英語
授課導師
J Garg - Real Time Learning
評分
3次瀏覽
課程簡介
Learn Hadoop Mapreduce from Scratch to Real-time Implementation using Hands-On Mapreduce examples.
Mapreduce framework is the closest to Hadoop in terms of processing Big data. It is considered as atomic processing unit in Hadoop and that is why it is never going to be obsolete.
Knowing only basics of MapReduce (Mapper, Reducer etc) is not sufficient to work in any Real-time Hadoop Mapreduce project of companies. These basics are just tip of the iceberg in Mapreduce programming. Real-time Mapreduce is way more than that. In Live Big data projects we have to override lot many default implementations of Mapreduce framework to make them work according to our requirements.
This course is an answer to the question "What concepts of Hadoop Mapreduce are used in Live Big data projects and How to implement them in a program ?" To answer this, every Mapreduce concept in the course is explained practically via a Mapreduce program.
Every lecture in this course is explained in 2 Steps.
Step 1 : Theory - Explanation of a Hadoop component
Step 2 : Practicals - How to implement that component in a MapReduce program.
The overall inclusions and benefits of this course:
Complete Hadoop Mapreduce explained from scratch to Real-Time implementation.
Each and Every Hadoop concept is backed by a HANDS-ON Mapreduce code.
Advance level Mapreduce concepts which are even not available on Internet.
For non Java backgrounder's help, All Mapreduce Java codes are explained line by line in such a way that even a non technical person can understand.
Mapreduce codes and Datasets used in lectures are attached for your convenience.
Includes multiple sections on 'Case Studies' that are asked generally in Hadoop Interviews.
課程章節
- 10 個章節
- 53 堂課
- 第 1 章 Introduction
- 第 2 章 Default structure of various classes in Mapreduce
- 第 3 章 Word Count program in Mapreduce
- 第 4 章 Mapreduce programs - Examples
- 第 5 章 Distributed Cache Implementation
- 第 6 章 Dealing with Input Split Class
- 第 7 章 Multiple Inputs & Output class
- 第 8 章 Joins in Mapreduce
- 第 9 章 Counters in Mapreduce
- 第 10 章 Creating Custom Input Formatter
課程內容
- Every concept that comes under Hadoop Mapreduce framework from SCRATCH to LIVE PROJECT Implementation.
- Learn to write Mapreduce Codes in a Real-Time working environment.
- Understand the working of each and every component of Hadoop Mapreduce with Hands-On examples.
- Override the default implementation of Mapreduce 's Java classes and code it according to custom requirements.
- ADVANCE level Mapreduce concepts which are not easily available online.
- Real-time Mapreduce Case studies asked in Hadoop Interviews with its proper Mapreduce code run on cluster.
評價
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AAjibade Lukuman Saheed
Very rewarding experience, I want to go over it again for better understanding of some aspects. This would enable me to enroll for an advanced Mapreduce programming course
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SSridhar Kalakonda
Very detailed and informative. Definitely helps in understanding the concepts clearly.
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AAnonymized User
Even though the course covers all the topics about Mapreduce but it is very poorly made and very distructive presentation. There are plenty number of examples but input text files don't have headers, and its difficut to remember what represents every field. In addition, the questions in quizzes are unclear and confusing.
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SSusan Liya
The course goes into good depth of map reduce, which is the unique feature to this course only. Other courses only explain basics of map reduce. How ever like all other Mapreduce courses this course also fails to setup initial premise and directly dive into technicalities. There should be videos like what is mapreduce, why we are learning, when and why to use, explaining terminologies. in first video Instructor uses words like Mapper and reducer when student doesn't even understand the context. Which is not unique to this course, every course on MR out there is like that. However if you have a basic knowledge of MR and you want to expand on that, then this course is the best one available. Instructor dives into great depths and cover almost all topics of MR. I would definitely recommend this course if you are looking to make career in Big Data.
