Taming Big Data with MapReduce and Hadoop - Hands On!

BY
Udemy

Using Hadoop and MapReduce's features, Gain a practical understanding of the big data concept.

Mode

Online

Fees

₹ 3699

Quick Facts

particular details
Medium of instructions English
Mode of learning Self study
Mode of Delivery Video and Text Based

Course overview

With the assistance of straightforward programming, Apache Hadoop is a software program that enables the distributed processing of massive data sets throughout multiple computers. MapReduce is a programming methodology that implements distributed algorithms on a network to process and produce large amounts of data. Frank Kane, the founder of Sundog Education, Sundog Education & Machine Learning Pro, and the Sundog Education Team created the Taming Big Data with MapReduce and Hadoop - Hands On online certification, which is provided through Udemy.

Taming Big Data with MapReduce and Hadoop - Hands On online course is designed to help individuals acquire the knowledge of the principles of Hadoop and MapReduce for big data operations, as well as techniques for structuring data analysis challenges such as MapReduce challenges to execute on the cloud computing technology. Taming Big Data with MapReduce and Hadoop - Hands On online classes offer 5 hours of in-depth lectures, 4 articles, and 12 downloadable materials that cover topics including big data analytics and explain the workings of several big data technologies like Hive, Pig, and Spark.

The highlights

  • Certificate of completion
  • Self-paced course
  • 5 hours of pre-recorded video content
  • 4 articles 
  • 12 downloadable resources

Program offerings

  • Online course
  • Downloadable learning resources
  • 30-day money-back guarantee
  • Unlimited access
  • Accessible on mobile devices and tv

Course and certificate fees

Fees information
₹ 3,699
certificate availability

Yes

certificate providing authority

Udemy

What you will learn

Knowledge of python Knowledge of big data Knowledge of apache spark

After completing the Taming Big Data with MapReduce and Hadoop - Hands On certification course, individuals will develop a better understanding of the principle of big data along with the strategies involved with big data analytics. Individuals will explore the concepts and features related to Hadoop and MapReduce as well as discover how to create MapReduce tasks using Python and MRJob. Individuals will be introduced to Hadoop technologies like Pig, Hive, and Spark as well as techniques for HDFS, YARN, and Hadoop clusters. Additionally, individuals will gain knowledge of Amazon Elastic MapReduce and the ability to analyze data from social networks and movie ratings.

The syllabus

Introduction, and Getting Started

  • Introduction
  • Udemy 101: Getting the Most From This Course
  • Note: Alternate download link for the MovieLens data set
  • Getting Started - Run your First MapReduce Program!

Understanding MapReduce

  • MapReduce Basic Concepts
  • A quick note on file names.
  • Walkthrough of Rating Histogram Code
  • Understanding How MapReduce Scales / Distributed Computing
  • Average Friends by Age Example: Part 1 
  • Average Friends by Age Example: Part 2
  • Minimum Temperature By Location Example
  • Maximum Temperature By Location Example
  • Word Frequency in a Book Example
  • Making the Word Frequency Mapper Better with Regular Expressions
  • Sorting the Word Frequency Results Using Multi-Stage MapReduce Jobs
  • Activity: Design a Mapper and Reducer for Total Spent by Customer
  • Activity: Write Code for Total Spent by Customer
  • Compare Your Code to Mine. Activity: Sort Results by Amount Spent
  • Compare your Code to Mine for Sorted Results.
  • Combiners

Advanced MapReduce Examples

  • Example: Most Popular Movie
  • Including Ancillary Lookup Data in the Example
  • Example: Most Popular Superhero, Part 1
  • Example: Most Popular Superhero, Part 2
  • Example: Degrees of Separation: Concepts
  • Degrees of Separation: Preprocessing the Data
  • Degrees of Separation: Code Walkthrough
  • Degrees of Separation: Running and Analyzing the Results
  • Example: Similar Movies Based on Ratings: Concepts
  • Similar Movies: Code Walkthrough
  • Similar Movies: Running and Analyzing the Results
  • Learning Activity: Improving our Movie Similarities MapReduce Job

Using Hadoop and Elastic MapReduce

  • Fundamental Concepts of Hadoop
  • The Hadoop Distributed File System (HDFS)
  • Apache YARN
  • Hadoop Streaming: How Hadoop Runs your Python Code
  • Setting Up Your Amazon Elastic MapReduce Account
  • Linking Your EMR Account with MRJob
  • Exercise: Run Movie Recommendations on Elastic MapReduce
  • Analyze the Results of Your EMR Job

Advanced Hadoop and EMR

  • Distributed Computing Fundamentals
  • Activity: Running Movie Similarities on Four Machines
  • Analyzing the Results of the 4-Machine Job
  • Troubleshooting Hadoop Jobs with EMR and MRJob, Part 1
  • Troubleshooting Hadoop Jobs, Part 2
  • ml-1m Dataset: Alternate Download Link
  • Analyzing One Million Movie Ratings Across 16 Machines, Part 1
  • Analyzing One Million Movie Ratings Across 16 Machines, Part 2

Other Hadoop Technologies

  • Introducing Apache Hive
  • Introducing Apache Pig
  • Apache Spark: Concepts
  • Spark Example: Part 1
  • Spark Example: Part 2
  • Congratulations!

Where to Go from Here

  • Bonus Lecture: More courses to explore!

Instructors

Mr Frank Kane

Mr Frank Kane
Founder
Freelancer

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