Important HDFS MCQ Questions with Answers (Set 2) | Big Data Technology

This set of HDFS MCQ covers advanced concepts of Big Data Technology related to Rack Awareness, Data Replication, HDFS Read and Write Operations, DataStreamer, pipeline architecture, and Name Node management. Useful for university semester examinations, and competitive exams.

Topic: Big Data Technology – HDFS | Set: 2

Difficulty: Medium to Hard | Total Questions: 15

HDFS MCQ Questions

Q1. Why should HDFS not be used for “low latency data access”?

• A. It cannot store data for long periods
• B. It prioritizes total data throughput over the time to fetch the first record
• C. It only works with slow network cables
• D. It requires manual intervention for every read

Q2. What is a major disadvantage of having “lots of small files” in HDFS?

• A. It makes the Data Nodes too hot
• B. It consumes too much Name Node memory for metadata
• C. It increases the replication factor automatically
• D. Small files cannot be replicated

Q3. If a file is 700 MB and the block size is 128 MB, how many blocks will HDFS create?

• A. 5
• B. 6
• C. 7
• D. 4

Q4. What is the main purpose of “Rack Awareness” in HDFS?

• A. To organize hardware for better aesthetics
• B. To provide fault tolerance and minimize network latency
• C. To ensure all blocks are stored on the same rack
• D. To speed up the Name Node’s CPU

Q5. According to the Rack Awareness algorithm (replication = 3), where are the replicas placed?

• A. All three on one local rack
• B. One on a local rack and two on a different rack
• C. Three different racks for every block
• D. All on the same Data Node

Q6. What technical operation does the Secondary Name Node perform to help the primary Name Node?

• A. It takes over as master if the primary fails
• B. It merges the change log (edits) with the existing file system image (fsimage)
• C. It stores the actual data blocks for backup
• D. It manages the network switches

Q7. Which object does a client call to initiate a file read in HDFS?

• A. DataNode.read()
• B. FileSystem.open()
• C. NameNode.fetch()
• D. RPC.execute()

Q8. How does the client know which Data Nodes have the blocks it needs to read?

• A. It asks every Data Node in the cluster
• B. It makes an RPC call to the Name Node
• C. It guesses based on previous reads
• D. The information is stored in the client’s local hard drive

Q9. What happens if a Name Node’s test fails when a client tries to create a new file?

• A. The file is created anyway
• B. The client receives an error message like an IOException
• C. The Data Node fixes the error
• D. The Name Node restarts automatically

View Answer & Explanat

Q10. What is the role of the “DataStreamer” in the HDFS write process?

• A. It reads data from the Data Nodes to the client
• B. It selects Data Nodes and requests new blocks from the Name Node
• C. It deletes old replicas to save space
• D. It encrypts the data before it leaves the client

Q11. During a write operation, what is the “pipeline”?

• A. The physical fiber optic cables
• B. The series of Data Nodes chosen to store replicas
• C. The list of metadata in the Name Node
• D. The backup secondary storage

Q12. How does HDFS ensure that a block has been successfully written to all replicas?

• A. It assumes success if the first node receives it
• B. It uses an internal “ack queue” to wait for acknowledgments
• C. The Name Node checks every 10 minutes
• D. Data Nodes send a text message to the administrator

Q13. Can an existing file in HDFS be modified or edited?

• A. Yes, at any time
• B. No, it adheres to the Write Once, Read Many paradigm
• C. Only by the Secondary Name Node
• D. Yes, but only the metadata

Q14. How does the Name Node maintain the correct replication factor if a node fails?

• A. It manually copies files from its own memory
• B. It monitors block reports and adds or removes replicas as needed
• C. It shuts down the entire cluster
• D. It asks the client to re-upload the data

Q15. What is the main benefit of distributing data traffic across all Data Nodes?

• A. It makes the system easier to debug
• B. It increases throughput, scalability, and availability
• C. It reduces the need for a Name Node
• D. It allows the use of smaller hard drives

Conclusion

These advanced HDFS MCQ Questions help strengthen concepts related to Rack Awareness, Data Replication, pipeline architecture, Name Node operations, DataStreamer, and distributed storage systems. These topics are frequently asked in university semester exams, and technical interviews.

For better understanding, also practice concepts related to MapReduce, YARN, Hadoop Architecture, and Big Data processing frameworks.

Fore theory and concepts, refer to Hadoop HDFS.

What’s Next?

• MapReduce MCQs
• Hadoop Architecture MCQs
• YARN MCQs