Learn How to Create Hadoop MapReduce Jobs in Python
4.0 (16 ratings)
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Learn How to Create Hadoop MapReduce Jobs in Python

Hadoop MapReduce Jobs Using Python
4.0 (16 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
360 students enrolled
Created by Inflame Tech
Last updated 8/2016
English
English
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Current price: $10 Original price: $20 Discount: 50% off
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Includes:
  • 4.5 hours on-demand video
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I Learn?
  • Understand what is Hadoop?
  • Understand MapReduce i.e. Heart of Big Data and Hadoop.
  • Running Jobs using Python.
  • Design and Implement Mapper and Reducer phase in Python
  • Execute and Run Hadoop Streaming Jobs
  • Integrate Mapper phase and Reducer phase with Java Driver Class
View Curriculum
Requirements
  • Basics of Computer Science
  • Basics of Hadoop would be benificial but not required
  • Basics of Object Oriented Programming
Description


Apache Hadoop is an open-source software framework for distributed storage and distributed processing of very large data sets on computer clusters built from commodity hardware. MapReduce is the heart of Apache Hadoop. MapReduce is a framework which allows developers to develop hadoop jobs in different languages. So in this course we'll learn how to create MapReduce Jobs with Python.This course will provide you an in-depth knowledge of concepts and different approaches to analyse datasets using Python Programming. 

This course on MapReduce Jobs with Python will help you to understand MapReduce Jobs Programming in Python, how to set up an environment for the running MapReduce Jobs in Python, how to submit and execute MapReduce applications in Python environment. We will start from beginning and then dive into the advanced concepts of MapReduce.

Who is the target audience?
  • Big Data Professionals
  • Hadoop Developers
  • Python Developers who want to go in the field of Big Data
  • Students who are interested in Hadoop MapReduce
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Curriculum For This Course
37 Lectures
04:40:27
+
Start Here
37 Lectures 04:40:27




2.2 Comparison with RDBMS
04:10

2.3 HDFS in Hadoop
07:29

2.4 Cluster modes of Hadoop
02:42

2.5 HDFS and MapReduce
04:47

3.1 MapReduce Model
03:39

3.2 Why MapReduce
05:25

3.3 Map and Reduce Operation
05:19

3.4 Data Flow In MapReduce
05:35

3.5 MapReduce Daemons
07:07

4.1 Introduction to Hadoop Streaming
04:31

4.2 Streaming Command Options
07:28

4.3 Generic Command Options
03:11

4.4 MapReduce Sample Program-1
28:56

4.5 MapReduce Sample Program-2
21:52

5.1 Chaining of MR Jobs
10:34

5.2 Custom Combiner
17:51

5.3 GenericOptionParser
03:28

5.4 Distributed Cache
11:17

6.1 JUnit Testing
09:27

6.2 Analysis of IRIS dataset
11:11

6.3 Built-in and Custom Counters in Hadoop
12:58

6.4 Custom Partititioner
05:47

6.5 Hadoop Sequence File Format
06:09

6.6 Read Write Sequence File
05:27

7.1 Hadoop Data Types
01:46

7.2 Processing of XML File
06:49

7.3 Data Compression with Hadoop
15:14

7.4 Data Serialization using Avro-Theo
09:21

8.1 Limitations of Hadoop 1.x
07:28

8.2 Hadoop 2.x with YARN
07:27

8.3 YARN and its Processing Application
04:54

8.4 YARN MR Application Execution Flow
05:26

8.5 Hadoop 2.x Cluster Architecture
02:56
About the Instructor
Inflame Tech
3.8 Average rating
104 Reviews
996 Students
7 Courses

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