MCQs on HDFS Architecture | Hadoop HDFS
HDFS Architecture plays a crucial role in distributed storage, where large volumes of data are managed. Learn about HDFS block storage, replication, fault tolerance, and the roles of its components: NameNode, DataNode, and SecondaryNameNode.
1. HDFS Block Storage Concept
- What is the default block size in HDFS?
- A) 512MB
- B) 128MB
- C) 64MB
- D) 256MB
- How does HDFS break large files into smaller units?
- A) By dividing them into equal segments
- B) By splitting based on metadata
- C) By breaking them into blocks
- D) By dividing based on user input
- What is the maximum block size that HDFS can support?
- A) 512MB
- B) 1GB
- C) 128MB
- D) 128TB
- How does HDFS handle large files that exceed the block size?
- A) By splitting them into multiple files
- B) By chunking them into blocks
- C) By compressing the file
- D) By storing them on different servers
- Why is block-based storage important in HDFS?
- A) It improves data encryption
- B) It allows parallel processing of blocks
- C) It reduces file corruption
- D) It minimizes disk space
- What happens when a block in HDFS becomes corrupted?
- A) The file is deleted
- B) The block is replicated from another node
- C) The block is replaced automatically by the user
- D) The block is manually fixed by the admin
2. HDFS Architecture: NameNode, DataNode, SecondaryNameNode
- What is the role of the NameNode in HDFS?
- A) It stores the actual data blocks
- B) It manages the file system namespace and metadata
- C) It stores replicated data
- D) It manages user access to files
- Which of the following is NOT a task of the NameNode?
- A) Storing block locations
- B) Managing data block replication
- C) Storing actual data
- D) Managing metadata
- What does the DataNode in HDFS do?
- A) It manages the metadata
- B) It stores the actual data blocks
- C) It replicates blocks
- D) It handles user queries
- What happens when a DataNode fails?
- A) The entire HDFS fails
- B) Data is lost permanently
- C) Blocks are replicated to another DataNode
- D) The system switches to the SecondaryNameNode
- What is the primary function of the SecondaryNameNode in HDFS?
- A) It acts as a backup for the NameNode
- B) It stores data blocks
- C) It manages block replication
- D) It handles user authentication
- How does the SecondaryNameNode assist the NameNode?
- A) By providing fault tolerance
- B) By periodically merging namespace edits with the fsimage
- C) By replicating data blocks
- D) By managing data access permissions
- What happens when the NameNode goes down?
- A) Data is still accessible from DataNodes
- B) The system goes into read-only mode
- C) All HDFS services stop
- D) The SecondaryNameNode takes over automatically
- Which component is responsible for monitoring the health of DataNodes?
- A) NameNode
- B) DataNode
- C) SecondaryNameNode
- D) JobTracker
- Which of the following statements is true about HDFS architecture?
- A) DataNodes store metadata
- B) NameNode stores actual data
- C) SecondaryNameNode does not provide fault tolerance
- D) DataNodes are responsible for data storage
3. Block Replication and Fault Tolerance
- What is the default replication factor for blocks in HDFS?
- A) 2
- B) 3
- C) 4
- D) 5
- Why is block replication important in HDFS?
- A) It ensures data integrity
- B) It increases storage space
- C) It helps in distributed computing
- D) It provides fault tolerance and data availability
- What happens when a DataNode with a block replica goes down?
- A) The block is removed from the system
- B) The block is replicated to another DataNode
- C) The block becomes unavailable for use
- D) The SecondaryNameNode handles the block
- How does HDFS handle multiple replica failures?
- A) By initiating a recovery mechanism
- B) By deleting the replica
- C) By switching to a backup system
- D) By using a new replication strategy
- What happens when the replication factor of a block is reduced in HDFS?
- A) The block is replicated to other DataNodes
- B) The block is removed from the system
- C) The block is archived
- D) The system enters safe mode
- In case of a node failure, which operation does HDFS perform to maintain fault tolerance?
- A) Decrease block replication
- B) Increase the replication factor
- C) Delete the corrupted blocks
- D) Switch to a secondary file system
- How does HDFS ensure the availability of data in case of block loss?
- A) By enabling dynamic block replication
- B) By restoring from a backup
- C) By storing data only in one DataNode
- D) By using a recovery log
4. Data Locality in HDFS
- What is data locality in HDFS?
- A) Storing data in the same physical location for faster access
- B) Storing data on separate DataNodes for security
- C) Storing data in a remote location for disaster recovery
- D) Storing data randomly across nodes
- How does HDFS improve data locality?
- A) By storing data based on access frequency
- B) By ensuring data is stored closer to compute nodes
- C) By storing data in a cloud environment
- D) By using in-memory data storage
- What happens when a job requires data from a remote DataNode in HDFS?
- A) The job is delayed until data is fetched
- B) The system switches to another node
- C) The data is copied to the local DataNode
- D) The data is replicated
- Why is data locality important in distributed systems like HDFS?
- A) It minimizes network traffic and latency
- B) It reduces block replication
- C) It improves fault tolerance
- D) It ensures better security
- How does HDFS handle jobs that do not have good data locality?
- A) By sending data to the processing node
- B) By creating multiple replicas of the data
- C) By storing the data on a new DataNode
- D) By changing the block size
- What does the NameNode do to enhance data locality?
- A) It selects a node for computation close to where data is stored
- B) It replicates the data across the cluster
- C) It archives old data blocks
- D) It loads data into memory
- How does HDFS determine which node is best for processing data?
- A) By evaluating the workload of each DataNode
- B) By checking the availability of replication nodes
- C) By considering network distance and resource availability
- D) By analyzing disk health
- How can HDFS ensure that data is processed locally?
- A) By scheduling computation tasks near data storage locations
- B) By reducing the replication factor
- C) By balancing data between nodes
- D) By creating backup copies in the same location
Answers
| Qno | Answer |
|---|---|
| 1 | B) 128MB |
| 2 | C) By breaking them into blocks |
| 3 | B) 1GB |
| 4 | B) By chunking them into blocks |
| 5 | B) It allows parallel processing of blocks |
| 6 | B) The block is replicated from another node |
| 7 | B) It manages the file system namespace and metadata |
| 8 | C) Storing actual data |
| 9 | B) It stores the actual data blocks |
| 10 | C) Blocks are replicated to another DataNode |
| 11 | A) It acts as a backup for the NameNode |
| 12 | B) By periodically merging namespace edits with the fsimage |
| 13 | B) The system goes into read-only mode |
| 14 | A) NameNode |
| 15 | D) DataNodes are responsible for data storage |
| 16 | B) 3 |
| 17 | D) It provides fault tolerance and data availability |
| 18 | B) The block is replicated to another DataNode |
| 19 | A) By initiating a recovery mechanism |
| 20 | A) The block is replicated to other DataNodes |
| 21 | B) Increase the replication factor |
| 22 | A) By enabling dynamic block replication |
| 23 | A) Storing data in the same physical location for faster access |
| 24 | B) By ensuring data is stored closer to compute nodes |
| 25 | A) The job is delayed until data is fetched |
| 26 | A) It minimizes network traffic and latency |
| 27 | A) By sending data to the processing node |
| 28 | A) It selects a node for computation close to where data is stored |
| 29 | C) By considering network distance and resource availability |
| 30 | A) By scheduling computation tasks near data storage locations |