Hadoop MCQ:  Hadoop Multiple Choice Questions and Answers

Hadoop MCQ with answers and explanations for placement tests and job interviews. These solved Hadoop MCQs are useful for the campus placement for all freshers including Engineering Students, MCA students, Computer and IT Engineers, etc.

Our Hadoop MCQ (Hadoop Multiple Choice Questions ) focuses on various parts of the Hadoop software utilities and their concept. It will be useful for anyone learning Hadoop platform Basics, Essentials, and/or Fundamentals. We will regularly update the quiz and most interesting thing is that questions come in a random sequence. So every time you will feel new questions.

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Guideline of Hadoop MCQ:

This Hadoop MCQ is intended for checking your Hadoop platform knowledge. It takes 40 minutes to pass the Hadoop MCQ. If you don’t finish the Hadoop MCQ within the mentioned time, all the unanswered questions will count as wrong. You can miss the questions by clicking the “Next” button and return to the previous questions by the “Previous” button. Every unanswered question will count as wrong. MCQ on Hadoop has features of randomization which feel you a new question set at every attempt.

In this Hadoop Quiz, we have also implemented a feature that not allowed the user to see the next question or finish the Hadoop quiz without attempting the current Hadoop MCQ.

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Hadoop MCQ

Hadoop MCQ:  Hadoop Multiple Choice Questions and Answers

1 / 25

To verify job status, look for the value **\_** in the **\_**.

2 / 25

What are the primary phases of a Reducer?

3 / 25

Partitioner controls the partitioning of what data?

4 / 25

Hadoop Core supports which CAP capabilities?

5 / 25

To perform local aggregation of the intermediate outputs, MapReduce users can optionally specify which object?

6 / 25

For high availability, use multiple nodes of which type?

7 / 25

To connect Hadoop to AWS S3, which client should you use?

8 / 25

MapReduce jobs can be written in which language?

9 / 25

 Which line of code implements a Reducer method in MapReduce 2.0?

10 / 25

To create a MapReduce job, what should be coded first?

11 / 25

Skip bad records provides an option where a certain set of bad input records can be skipped when processing what type of data?

12 / 25

In a MapReduce job, where does the map() function run?

13 / 25

In what form is Reducer output presented?

14 / 25

To get the total number of mapped input records in a map job task, you should review the value of which counter?

15 / 25

To reference a master file for lookups during Mapping, what type of cache should be used?

16 / 25

DataNode supports which type of drives?

17 / 25

Which method is used to implement Spark jobs?

18 / 25

If you started the NameNode, then which kind of user must you be?

19 / 25

SQL Windowing functions are implemented in Hive using which keywords?

20 / 25

Which command imports data to Hadoop from a MySQL database?

21 / 25

Which library should be used to unit test MapReduce code?

22 / 25

To set up Hadoop workflow with synchronization of data between jobs that process tasks both on disk and in memory, use the _ service, which is _.

23 / 25

Rather than adding a Secondary Sort to a slow Reduce job, it is Hadoop best practice to perform which optimization?

24 / 25

Hadoop Auth enforces authentication on protected resources. Once authentication has been established, it sets what type of authenticating cookie?

25 / 25

State __ between the JVMs in a MapReduce job

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