HDFS Interview questions (with short answers)-1

Here are the top interview questions of Hadoop Distributed File System (HDFS) with solutions:

1. What is HDFS, and what are its key features?

HDFS is a distributed file system that stores and manages large datasets across multiple commodity servers. Its key features include fault tolerance, data locality, scalability, and integration with other Hadoop ecosystem components.

2. How does HDFS store and manage large data sets?

HDFS stores large data sets by dividing them into smaller blocks and distributing them across multiple DataNodes in a cluster. The NameNode manages the metadata for the file system and provides instructions to the DataNodes on where to store and retrieve data.

3. What are the main components of HDFS?

The main components of HDFS are the NameNode, DataNodes, and clients.

4. What is the role of the NameNode in HDFS?

The NameNode manages the file system namespace and controls access to files by clients. It stores metadata for all files and directories, including file permissions, ownership, and replication factor.

5. What is the role of DataNodes in HDFS?

The DataNodes in HDFS store the actual data blocks of files and communicate with the NameNode to receive instructions on storing and retrieving data.

6. How does HDFS ensure fault tolerance?

HDFS ensures fault tolerance by replicating data blocks across multiple DataNodes in the cluster. If one DataNode fails, the data can be retrieved from a replica on another DataNode.

7. What is the replication factor in HDFS, and how does it affect performance?

The replication factor in HDFS is the number of copies of a data block stored across DataNodes. A higher replication factor provides greater fault tolerance but can impact performance and storage capacity.

8. How does HDFS support data locality?

HDFS supports data locality by storing data blocks on the same node where the computation is performed. This reduces network traffic and improves performance.

9. How does HDFS integrate with other components of the Hadoop ecosystem?

HDFS can be easily integrated with other Hadoop ecosystem components, such as MapReduce, YARN, and Hive, to process and analyze large datasets efficiently.

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10. What is the role of the Secondary NameNode in HDFS?

The Secondary NameNode in HDFS periodically merges the edit logs with the fsimage file to create a new checkpoint for the NameNode.

11. What are the different types of file systems supported by Hadoop?

Hadoop supports different file systems, including HDFS, Local file systems, S3 file systems, and more.

12. How can you increase the performance of HDFS?

You can increase the performance of HDFS by adjusting the block size, and replication factor and configuring DataNode and NameNode parameters for optimal performance.

13. What is a block in HDFS, and how does it relate to data storage?

A block in HDFS is the smallest data unit the system can store and manage. It is typically 64MB in size and is distributed across multiple DataNodes.

14. What is the default block size in HDFS, and how can it be changed?

The default block size in HDFS is 64MB, but it can be changed by setting the dfs.block.size configuration parameter in the HDFS configuration file.

15. What is the significance of the block size in HDFS performance?

The block size in HDFS can impact performance by affecting the number of files stored on the system, the amount of data that can be read and written at once, and the amount of network traffic generated by data transfers.