1. What does HDFS stand for in the context of Hadoop?
a) High-Density File System
b) Hadoop Data File System
c) Hadoop Distributed File System
d) High-Durability File System
Answer:
c) Hadoop Distributed File System
Explanation:
HDFS stands for Hadoop Distributed File System. It is a distributed file system designed to run on commodity hardware and is highly fault-tolerant.
2. What is the primary purpose of HDFS?
a) Real-time data processing
b) High-performance computing
c) Storing large files across multiple machines
d) Data warehousing
Answer:
c) Storing large files across multiple machines
Explanation:
The primary purpose of HDFS is to store large files across multiple machines. It breaks down large files into blocks and distributes them across multiple nodes in a cluster.
3. In HDFS, what is a 'Block'?
a) A single unit of storage
b) The smallest unit of data
c) A type of file
d) A part of the NameNode
Answer:
a) A single unit of storage
Explanation:
In HDFS, a 'Block' is a single unit of storage, which is a portion of a file. Large files are split into blocks, which are then distributed across the cluster.
4. What is the role of the NameNode in HDFS?
a) It stores all the data
b) It manages the file system namespace
c) It handles the computation
d) It acts as a backup server
Answer:
b) It manages the file system namespace
Explanation:
The NameNode in HDFS manages the file system namespace. It maintains the file system tree and metadata for all files and directories, and keeps track of where across the cluster the file data is kept.
5. What is the default block size in HDFS?
a) 64 MB
b) 128 MB
c) 256 MB
d) 512 MB
Answer:
b) 128 MB
Explanation:
The default block size in HDFS is 128 MB. This large block size helps in reducing the overhead of managing a large number of small blocks.
6. What is a DataNode in HDFS?
a) A node that only stores metadata
b) A master node that manages the cluster
c) A node that stores and retrieves blocks
d) A backup node for the NameNode
Answer:
c) A node that stores and retrieves blocks
Explanation:
In HDFS, a DataNode is responsible for storing and retrieving blocks when told to by clients or the NameNode. DataNodes are the workhorses that store and process the data.
7. How does HDFS achieve fault tolerance?
a) By using RAID configurations
b) Through data replication across multiple nodes
c) By automatically backing up data to the cloud
d) Using checksums for data verification
Answer:
b) Through data replication across multiple nodes
Explanation:
HDFS achieves fault tolerance by replicating data blocks across multiple nodes. This ensures that if one node fails, the data is still accessible from another node.
8. What happens when a file is deleted in HDFS?
a) It is permanently deleted immediately
b) It is moved to a trash directory for a configurable time
c) It is archived for future recovery
d) It remains in the file system but becomes inaccessible
Answer:
b) It is moved to a trash directory for a configurable time
Explanation:
When a file is deleted in HDFS, it is moved to a trash directory where it stays for a configurable period before being permanently deleted. This allows recovery of accidentally deleted files.
9. Can HDFS be used with programming languages other than Java?
a) No, HDFS can only be accessed using Java
b) Yes, but only with Python and Ruby
c) Yes, HDFS can be accessed using various programming languages
d) Only Java and Scala are supported
Answer:
c) HDFS can be accessed using various programming languages
Explanation:
While HDFS is written in Java, it can be accessed using various programming languages through libraries and APIs that interact with the Hadoop system.
10. What is the purpose of the Secondary NameNode in HDFS?
a) To replace the primary NameNode in case of failure
b) To store a second copy of the data
c) To perform checkpointing of the file system metadata
d) To balance the load between DataNodes
Answer:
c) To perform checkpointing of the file system metadata
Explanation:
The Secondary NameNode in HDFS periodically creates checkpoints of the file system metadata, which can be used for recovery. It does not replace the primary NameNode in case of failure.
11. What is a 'rack-aware' replication policy in HDFS?
a) Replicating data across different geographies
b) Avoiding replication in the same rack
c) Replicating data within the same rack
d) Distributing replicas of data blocks on different racks
Answer:
d) Distributing replicas of data blocks on different racks
Explanation:
A 'rack-aware' replication policy in HDFS aims to distribute replicas of data blocks across different racks. This enhances fault tolerance by ensuring data availability even if an entire rack fails.
12. How does HDFS handle large files?
a) By compressing them into smaller sizes
b) By splitting them into fixed-size blocks
c) By storing them on a single node
d) HDFS cannot handle large files
Answer:
b) By splitting them into fixed-size blocks
Explanation:
HDFS handles large files by splitting them into fixed-size blocks (default 128 MB). These blocks are then distributed across multiple nodes in the cluster.
13. In HDFS, what is 'safemode'?
a) A secure mode for confidential data
b) A maintenance state where no changes to the file system are allowed
c) A mode for safely shutting down the cluster
d) A read-only mode for accessing files
Answer:
b) A maintenance state where no changes to the file system are allowed
Explanation:
'Safemode' in HDFS is a maintenance state during startup where the NameNode does not allow any modifications to the file system. It allows the system to reach a stable state before becoming fully operational.
14. What is the function of the 'fsck' command in HDFS?
a) To fix corrupted files
b) To check the health of the file system
c) To compress data in the file system
d) To change file permissions
Answer:
b) To check the health of the file system
Explanation:
The 'fsck' (file system check) command in HDFS is used to check the health of the file system, report any problems with files or blocks, and provide overall statistics.
15. Can HDFS be accessed through a web browser?
a) No, it requires a command-line interface
b) Yes, via the HDFS Web UI
c) Only through third-party tools
d) Web access is read-only
Answer:
b) Yes, via the HDFS Web UI
Explanation:
HDFS can be accessed through a web browser via the HDFS Web UI, which allows users to browse the file system, upload, and download files.
16. What is the role of the 'Balancer' in HDFS?
a) To balance the load on the NameNode
b) To distribute blocks evenly across the DataNodes
c) To balance network traffic
d) To allocate resources evenly among users
Answer:
b) To distribute blocks evenly across the DataNodes
Explanation:
The 'Balancer' in HDFS is a utility that redistributes data blocks across DataNodes to ensure that the data is evenly distributed, enhancing system balance and performance.
17. How are read operations performed in HDFS?
a) Data is always read from the primary replica
b) Data is read from the nearest replica
c) Read operations require approval from the NameNode
d) Data is read in a round-robin fashion from all replicas
Answer:
b) Data is read from the nearest replica
Explanation:
In HDFS, read operations are performed by reading data from the nearest replica of a block, reducing the latency and network traffic.
18. What happens if a DataNode fails in HDFS?
a) The entire file system becomes inaccessible
b) DataNode is automatically replaced by a standby node
c) The system replicates the blocks stored on the failed node
d) Data is permanently lost
Answer:
c) The system replicates the blocks stored on the failed node
Explanation:
If a DataNode fails, HDFS ensures that another copy of the blocks stored on the failed node is created on other DataNodes, maintaining the desired replication level and preventing data loss.
19. Can HDFS handle simultaneous read and write operations on the same file?
a) Yes, without any constraints
b) No, HDFS does not support simultaneous read and write operations
c) Only read operations are allowed during a write
d) Write operations must wait until all reads are completed
Answer:
b) No, HDFS does not support simultaneous read and write operations
Explanation:
HDFS does not support simultaneous read and write operations on the same file. A file in HDFS must be closed before it can be read.
20. What is the main advantage of HDFS's replication strategy?
a) Reducing storage costs
b) Minimizing network usage
c) Enhancing data security
d) Improving fault tolerance and data availability
Answer:
d) Improving fault tolerance and data availability
Explanation:
The main advantage of HDFS's replication strategy is that it significantly improves fault tolerance and data availability by replicating data blocks across multiple DataNodes.
21. How does HDFS ensure data integrity?
a) By using checksums for each block of data
b) By using checksums for each block of data
c) Through user authentication and authorization
d) By encrypting data
Answer:
b) By using checksums for each block of data
Explanation:
HDFS ensures data integrity by using checksums for each block of data. When data is read, HDFS verifies it against the stored checksums to ensure that the data has not been corrupted during storage.
22. What is the role of 'Heartbeat' messages in HDFS?
a) To synchronize data across DataNodes
b) To inform the NameNode that a DataNode is alive
c) To check the connectivity between clients and the cluster
d) To balance the load across DataNodes
Answer:
b) To inform the NameNode that a DataNode is alive
Explanation:
In HDFS, 'Heartbeat' messages are sent periodically from each DataNode to the NameNode. These messages inform the NameNode that the DataNode is functioning correctly and is part of the cluster.
23. Can HDFS be deployed on commodity hardware?
a) Yes, it is designed to run on commodity hardware
b) No, it requires specialized high-end hardware
c) Only if the commodity hardware meets specific performance criteria
d) HDFS is hardware agnostic
Answer:
a) Yes, it is designed to run on commodity hardware
Explanation:
HDFS is designed to be deployed on commodity hardware. Its architecture is built to handle hardware failures, making it suitable for lower-cost hardware.
24. What is the purpose of the 'hadoop fs' command-line tool?
a) To configure Hadoop clusters
b) To perform file operations on HDFS
c) To monitor HDFS performance
d) To execute MapReduce jobs
Answer:
b) To perform file operations on HDFS
Explanation:
The 'hadoop fs' command-line tool is used for performing various file operations on HDFS, such as copying, moving, deleting, and listing files.
25. How does HDFS handle the 'small files problem'?
a) By automatically merging small files into larger ones
b) Small files are not a problem in HDFS
c) By storing small files outside of HDFS
d) HDFS is not optimized for handling a large number of small files
Answer:
d) HDFS is not optimized for handling a large number of small files
Explanation:
HDFS faces challenges with a large number of small files because each file, directory, and block in HDFS is represented as an object in the NameNode's memory, which can lead to memory exhaustion. HDFS is optimized for fewer, large files rather than many small ones.