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Hadoop MapReduce Example | MapReduce Programming | Hadoop Tutorial For Beginners | Edureka
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Hadoop MapReduce Example | MapReduce Programming | Hadoop Tutorial For Beginners | Edureka

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( Hadoop Training: https://www.edureka.co/hadoop )
This Hadoop tutorial on MapReduce Example ( Mapreduce Tutorial Blog Series: https://goo.gl/cZmvLS ) will help you understand how to write a MapReduce program in Java. You will also get to see multiple mapreduce examples on Analytics and Testing.

Check our complete Hadoop playlist here: https://goo.gl/ExJdZs

Below are the topics covered in this tutorial:

1) MapReduce Way
2) Classes and Packages in MapReduce
3) Explanation of a Complete MapReduce Program
4) MapReduce Examples on Analytics
5) MapReduce Example on Testing - MRUnit

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#MapReduceExample #MapReduceAnalytics #MapReduceTesting

How it Works?

1. This is a 5 Week Instructor led Online Course, 40 hours of assignment and 30 hours of project work
2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
3. At the end of the training you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate!

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About the Course

Edureka’s Big Data and Hadoop online training is designed to help you become a top Hadoop developer. During this course, our expert Hadoop instructors will help you:

1. Master the concepts of HDFS and MapReduce framework
2. Understand Hadoop 2.x Architecture
3. Setup Hadoop Cluster and write Complex MapReduce programs
4. Learn data loading techniques using Sqoop and Flume
5. Perform data analytics using Pig, Hive and YARN
6. Implement HBase and MapReduce integration
7. Implement Advanced Usage and Indexing
8. Schedule jobs using Oozie
9. Implement best practices for Hadoop development
10. Work on a real life Project on Big Data Analytics
11. Understand Spark and its Ecosystem
12. Learn how to work in RDD in Spark

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Who should go for this course?

If you belong to any of the following groups, knowledge of Big Data and Hadoop is crucial for you if you want to progress in your career:
1. Analytics professionals
2. BI /ETL/DW professionals
3. Project managers
4. Testing professionals
5. Mainframe professionals
6. Software developers and architects
7. Recent graduates passionate about building successful career in Big Data

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Why Learn Hadoop?

Big Data! A Worldwide Problem?

According to Wikipedia, "Big data is collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications." In simpler terms, Big Data is a term given to large volumes of data that organizations store and process. However, it is becoming very difficult for companies to store, retrieve and process the ever-increasing data. If any company gets hold on managing its data well, nothing can stop it from becoming the next BIG success!

The problem lies in the use of traditional systems to store enormous data. Though these systems were a success a few years ago, with increasing amount and complexity of data, these are soon becoming obsolete. The good news is - Hadoop, which is not less than a panacea for all those companies working with BIG DATA in a variety of applications and has become an integral part for storing, handling, evaluating and retrieving hundreds of terabytes, and even petabytes of data.

Please write back to us at sales@edureka.co or call us at +91 88808 62004 for more information.

Customer Review:

Michael Harkins, System Architect, Hortonworks says: “The courses are top rate. The best part is live instruction, with playback. But my favorite feature is viewing a previous class. Also, they are always there to answer questions, and prompt when you open an issue if you are having any trouble. Added bonus ~ you get lifetime access to the course you took!!! Edureka lets you go back later, when your boss says "I want this ASAP!" ~ This is the killer education app... I've take two courses, and I'm taking two more.”
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