MapReduce is a programming model and an associated implementation for processing and generating large data sets with a parallel, distributed algorithm on a cluster.
A MapReduce program is composed of a Map() procedure that performs filtering and sorting and a Reduce() method that performs a summary operation. The “MapReduce System” orchestrates the processing by marshalling the distributed servers, running the various tasks in parallel, managing all communications and data transfers between the various parts of the system, and providing for redundancy and fault tolerance.
MapReduce is a framework for processing parallelizable problems across huge datasets using a large number of computers (nodes), collectively referred to as a cluster or a grid. Processing can occur on data stored either in a filesystem (unstructured) or in a database (structured). MapReduce can take advantage of locality of data, processing it on or near the storage assets in order to reduce the distance over which it must be transmitted.
MapReduce Training Overview
Take your knowledge to the next level with MapReduce training course that delivers the key concepts and expertise participants need to create Project, Class, Package. From MapReduce Programming to developing MapReduce Application. Our training course is the best preparation for the realworld challenges faced by the developers.
MapReduce Training Curriculum
Aspects of Java
How to Create New Java project
How to create New Java Class
Hello World program
How to run this program
Types of integer
Class creation & name given
Creation of package
Sub-class & super Class
Map-Reducing in Inheritance
What is the method of overloading
Difference between overloading & overriding
Method of overriding
Basic concept of abstract
Abstract class demo
Difference between Abstract & concrete class
Implementation of abstract class in Java
Difference between JRE & JBM
Word count example
Introduction and characteristics of big data
Introduction of Hadoop and its work
What is HDFS and its explanation with example
Introduction to Map Reduce?
What is Map Phase?
What is Reduce Phase?
Introduction to Hadoop ecosystem
How Hadoop solve problems of typical distributed system
What is Sqoop and its working
What is Qozie and its working
What is Pig and its working
What is Flume and its working
What is Hive and its working
HDFS Storage Mechanism
How files are Stored / Read / Written in HDFS
Introduction to Mapreduce and HDFS
MapReduce job Execution
Shuffle & Sort Phase
Map Reduce in detail
Comparison b/w YARN and MRV1
Cloudera Developer Certification Overview
Hands on Exercises on Map Reduce
Introduction to Mapper, Box classes and Reducer
Input Formats and Output Formats
How to filter File Inputs
How to work on amazon cluster
Our trainers have relevant experience in implementing real-time solutions on different queries related to different topics. Mindmajix verifies their technical background and expertise.
We record each LIVE class session you undergo through and we will share the recordings of each session/class.
Trainer will provide the Environment/Server Access to the students and we ensure practical real-time experience and training by providing all the utilities required for the in-depth understanding of the course.
If you are enrolled in classes and/or have paid fees, but want to cancel the registration for certain reason, it can be attained within 48 hours of initial registration. Please make a note that refunds will be processed within 30 days of prior request.
The Training itself is Real-time Project Oriented.
Yes. All the training sessions are LIVE Online Streaming using either through WebEx or GoToMeeting, thus promoting one-on-one trainer student Interaction.
There are some Group discounts available if the participants are more than 2.
As we are one of the leading providers of Online training, We have customers from USA, UK, Canada, Australia, UAE, Qatar, NZ, Singapore, Malaysia, India and other parts of the world. We are located in USA. Offering Online Training in Cities like
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