FUNDAMENTALS OF COMPUTER

DATABASE FUNDAMENTALS

BASICS OF BIG DATA

Question [CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
MapReduce works as?
A
Analytical
B
Cluster Failover
C
Distribution
D
Storage Management
Explanation: 

Detailed explanation-1: -MapReduce is a big data analysis model that processes data sets using a parallel algorithm on computer clusters, typically Apache Hadoop clusters or cloud systems like Amazon Elastic MapReduce (EMR) clusters. A software framework and programming model called MapReduce is used to process enormous volumes of data.

Detailed explanation-2: -MapReduce-Introduction. MapReduce is a programming model for writing applications that can process Big Data in parallel on multiple nodes. MapReduce provides analytical capabilities for analyzing huge volumes of complex data.

Detailed explanation-3: -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-4: -MapReduce serves two essential functions: it filters and parcels out work to various nodes within the cluster or map, a function sometimes referred to as the mapper, and it organizes and reduces the results from each node into a cohesive answer to a query, referred to as the reducer.

Detailed explanation-5: -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.

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