Hadoop Quiz / MCQ Set 5

Hadoop Quiz: Test Your Knowledge with These 8 MCQs 

Welcome to the ultimate Hadoop Quiz! If you're looking to test your knowledge and expertise in Hadoop, you've come to the right place. In this article, we have compiled a set of ten multiple-choice questions (MCQs) that will challenge your understanding of various Hadoop concepts, tools, and applications. Whether you are a Hadoop enthusiast, a data engineer, a developer, or someone curious about this powerful big data framework, this quiz is designed to cater to all levels of expertise. So, whether you're a beginner looking to explore the world of Hadoop or an experienced professional aiming to brush up your skills, we've got you covered. Our Hadoop MCQ quiz covers a diverse range of topics, including Hadoop Distributed File System (HDFS), MapReduce, YARN, Hive, Pig, HBase, and much more. Each question is thoughtfully crafted to challenge your understanding and help you grasp the core concepts better. So, let's put your Hadoop knowledge to the test and see how much you really know about this revolutionary technology. Don't worry; it's all in good fun, and you might even discover new insights along the way. 

Dive into the quiz and see if you can score a perfect ten! Get ready to showcase your Hadoop prowess and boost your confidence in handling big data challenges. Let's get started and embark on this exciting Hadoop journey together!

1. Which technology is used to import and export data in Hadoop?
Zookeeper
Sqoop
Avro
HBase

2. Avro
Output of the mapper and output of the combiner has to be same key value pair and they can be heterogeneous
Output of the mapper and output of the combiner has to be same key value pair. Only if the values satisfy associative and commutative property it can be done.
Combiner can be applied always to any data
none

3. HDFS block size is larger as compared to the size of the disk blocks so that
Only HDFS files can be stored in the disk used.
The seek time is maximum
A single file larger than the disk size can be stored across many disks in the cluster.
Transfer of a large files made of multiple disk blocks is not possible.

4. In Hadoop 2.x release HDFS federation means
Allow a cluster to scale by adding more namenodes.
Adding more physical memory to both namenode and datanode.
Adding more physical memory to both namenode and datanode.
Allowing namenodes to communicate with each other.

5. The hdfs command put is used to
The hadfs command put is used to
Copy files from HDFS to local filesystem.
Copy files or directories from local file system to HDFS.
Copy files or directories from HDFS to local filesystem.

6. The role of a Journal node is to
Report the activity of various components handled by resource manager
Report the edit log information of the blocks in the data node.
Report the Schedules when the jobs are going to run
No use

7. The source of HDFS architecture in Hadoop originated as
The source of HDFS architecture in Hadoop originated as
Yahoo distributed filesystem
Facebook distributed filesystem
Azure distributed filesystem

8. All the files in a directory in HDFS can be merged together using
getmerge
mergeall
mergeall
putmerge

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1. As part of the HDFS high availability a pair of primary namenodes are configured. What is true for them?
When a client request comes, one of them chosen at random serves the request. One of them is active while the other one remains powered off.
The standby node takes periodic checkpoints of active namenode’s namespace.
Datanodes send block reports to only one of the namenodes.

2. Which of the below property gets configured on core-site.xml ? Replication factor
Directory names to store hdfs files.
Host and port where MapReduce task runs.
Java Environment variables.

3. The input split used in MapReduce indicates The average size of the data blocks used as input for the program
The location details of where the first whole record in a block begins and the last whole record in the block ends.
Splitting the input data to a MapReduce program into a size already configured in the mapred-site.xml
None of these

4. What is the default input format? The default input format is TextInputFormat with byte offset as a key and entire line as a value.
The default input format is a sequence file format. The data needs to be preprocessed before using the default input format.
There is no default input format. The input format always should be specified.
The default input format is xml. Developer can specify other input formats as appropriate if xml is not the correct input.

5. Which one of the following statements is false regarding the Distributed Cache?
The files in the cache can be text files, or they can be archive files like zip and JAR files. The Hadoop framework will ensure that any files in the Distributed Cache are distributed to all map and reduce tasks.
The Hadoop framework will copy the files in the Distributed Cache on to the slave node before any tasks for the job are executed on that node.
Disk I/O is avoided because data in the cache is stored in memory.

6. The main role of the secondary namenode is to
Copy the filesystem metadata from primary namenode. Copy the filesystem metadata from NFS stored by primary namenode
Copy the filesystem metadata from NFS stored by primary namenode
Periodically merge the namespace image with the edit log.

7. The namenode knows that the datanode is active using a mechanism known as heartbeats
datapulse
h-signal
Active-pulse

8. Running Start-dfs.sh results in Starting namenode and resource manager
Starting datanode only
Starting namenode only
Starting namenode and datanode



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