Hadoop MCQ Questions Answers

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Hadoop multiple choice questions List

What is Hadoop used for?

Using straightforward programming concepts, the Hadoop platform enables the distributed processing of massive data volumes across clusters of computers. From a single server to thousands of devices, each providing local computing, and storage, it is intended to scale up. 

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Is Hadoop a python?

Although Java is the most popular language to implement Hadoop, it may be done in any language. Hadoop streaming, on the other hand, enables the use of any programming language with a standardized input and output format. Therefore, if you wanted to, you could theoretically write your Hadoop code in Python. However, Java continues to be the language of choice for the great majority of Hadoop users. 

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What is Hadoop and its example?

Hadoop is a Java-based Apache open-source technology that enables the distributed processing of massive data collections across computer clusters. From a single server to thousands of devices, each providing local computing, and storage, it is intended to scale up.

Hadoop may be used, for instance, to analyze log data from web servers to find patterns in user activity. If you want to learn more about it, you should stick with Quizack, where you will get the best possible collection of Hadoop multiple choice questions and answers to help you in tests and interviews.

Is Hadoop a coding?

Hadoop is not a programming language, no. It is a framework of open-source software that permits the distributed processing of massive data sets across computer clusters. It uses a straightforward programming style for handling massive amounts of data and is built in Java. You may test your knowledge of your subject by using Quizack to locate the most useful database of Hadoop MCQ questions and answers.

Is Hadoop similar to SQL?

SQL and Hadoop are two completely distinct technologies. While SQL is a standard language for accessing databases, Hadoop is a system for handling and storing large amounts of data. Despite the fact that they may both be used to work with massive data volumes, their capabilities and designs differ. 

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