MapReduce is actually MapReduce included in modern computing that uses the JAVA programming language, uses two processes namely Map and Reduce which makes it able to process parallel to .....

BASICS OF BIG DATA

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Question [CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]

MapReduce is actually MapReduce included in modern computing that uses the JAVA programming language, uses two processes namely Map and Reduce which makes it able to process parallel to ____

A	Multiple Node
B	Branch nodes
C	Single Node
D	Half Duplex
E	Single Netoe,

Explanation:

Detailed explanation-1: -Basically Hadoop Streaming allows us to write Map/reduce jobs in any languages (such as Python, Perl, Ruby, C++, etc) and run as mapper/reducer. Thus it enables a person who is not having any knowledge of Java to write MapReduce job in the language of its own choice.

Detailed explanation-2: -There are two phases in the MapReduce program, Map and Reduce. The Map task includes splitting and mapping of the data by taking a dataset and converting it into another set of data, where the individual elements get broken down into tuples i.e. key/value pairs.

Detailed explanation-3: -Limitations of Hadoop MapReduce and Apache Spark No Support for Real-time Processing: Hadoop MapReduce is only good for Batch Processing. Apache Spark only supports near Real-Time Processing. Requirement of Trained Personnel: The two platforms can only be used by users with technical expertise.

Detailed explanation-4: -MapReduce processes data in parallel by dividing the job into the set of independent tasks. So, parallel processing improves speed and reliability.

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BASICS OF BIG DATA