FUNDAMENTALS OF COMPUTER

Detailed explanation-1: -MapReduce is a programming paradigm designed for processing huge volumes of data in parallel by dividing the job (submitted work) into a set of independent tasks (sub-job).

Detailed explanation-2: -A software framework and programming model called MapReduce is used to process enormous volumes of data. Map and Reduce are the two stages of the MapReduce program’s operation.

Detailed explanation-3: -MapReduce is a programming paradigm that enables massive scalability across hundreds or thousands of servers in a Hadoop cluster. As the processing component, MapReduce is the heart of Apache Hadoop. The term “MapReduce” refers to two separate and distinct tasks that Hadoop programs perform.

Detailed explanation-4: -MapReduce is a programming model or pattern within the Hadoop framework that is used to access big data stored in the Hadoop File System (HDFS). It is a core component, integral to the functioning of the Hadoop framework.

Detailed explanation-5: -At a high level, MapReduce breaks input data into fragments and distributes them across different machines. The input fragments consist of key-value pairs. Parallel map tasks process the chunked data on machines in a cluster. The mapping output then serves as input for the reduce stage.