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A custom course designed by Hadoop experts to provide knowledge and skills in the MapReduce Framework field and help you solve use cases using MapReduce concepts.
HADOOP MAPREDUCE FRAMEWORK - I. Learning Objectives: In this module, you will understand the Hadoop MapReduce framework and how MapReduce works on data stored in HDFS. You will learn about YARN concepts in MapReduce. Topics: MapReduce use cases, traditional way Vs MapReduce way, why MapReduce, Hadoop 2.x MapReduce architecture, Hadoop 2.x MapReduce components, YARN MR application execution flow, YARN workflow, program anatomy MapReduce, demo in MapReduce. . Click on the "go to course" button to learn more details at edureka!
HADOOP MAPREDUCE FRAMEWORK-II. Learning Objectives: In this module, you will understand concepts such as Input Splits in MapReduce, Combiner & Partitioner, and Demos in MapReduce using different data sets. Topics: MapReduce Input Splits, Combiner, Partitioner, MapReduce Demos. . Click on the "go to course" button to learn more details at edureka!
ADVANCED MAPEDUCE . Learning Objectives: In this module, you will learn advanced MapReduce concepts such as Counters, Distributed Cache, MRunit, Reduce Union, Custom Input Format, Stream Input Format, and how to deal with complex MapReduce programs. Topics: Counters, Distributed Cache, MR Unit, Union Reduction, Custom Input Format, Stream Input Format. . Click on the "go to course" button to learn more details at edureka!
Instructor-led sessions will address all your concerns in real time.
Unlimited access to the course's online learning repository.
Develop a project with live accompaniment, based on any of the cases seen
In each class you will have practical tasks that will help you apply the concepts taught.
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Doesn't sound great!
All edureka instructors are industry professionals with a minimum of 10-12 years of relevant IT experience. They are experts in each subject covered by the course and are trained by edureka to provide a high-level learning experience for students.
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