For locally attached storage in HDFS, what HDFS replication factor should be used?

For locally attached storage in HDFS, what HDFS replication factor should be used?

• A. 1
• B. 2
• C. 3
• D. 4

Answer: (C)

In a Hadoop Distributed File System (HDFS), the replication factor is a key parameter that determines how many copies of each data block are stored across the cluster. Using a replication factor of three is generally the best practice for several reasons. Firstly, a replication factor of three provides a balance between fault tolerance and storage efficiency. This means that if one of the nodes in the cluster fails, there will still be at least two other copies of the data available on different nodes. This redundancy ensures high availability, which is crucial for maintaining data integrity and reliability in distributed systems. Secondly, with three copies, the system can continue to operate effectively in the event of a node failure, as well as during routine maintenance or upgrades. This level of replication allows for data accessibility and minimizes the risk of data loss. Moreover, the overhead of storing three copies is justified for the high availability it provides, especially in big data environments where data loss can have significant repercussions. Choosing a replication factor higher than three, such as four, would consume more storage resources unnecessarily, while a replication factor of two might not offer enough redundancy, particularly in the case of failures. Therefore, a replication factor of three is recommended as it strikes an optimal balance for reliability and resource utilization in HDFS

In a Hadoop Distributed File System (HDFS), the replication factor is a key parameter that determines how many copies of each data block are stored across the cluster. Using a replication factor of three is generally the best practice for several reasons.

Firstly, a replication factor of three provides a balance between fault tolerance and storage efficiency. This means that if one of the nodes in the cluster fails, there will still be at least two other copies of the data available on different nodes. This redundancy ensures high availability, which is crucial for maintaining data integrity and reliability in distributed systems.

Secondly, with three copies, the system can continue to operate effectively in the event of a node failure, as well as during routine maintenance or upgrades. This level of replication allows for data accessibility and minimizes the risk of data loss.

Moreover, the overhead of storing three copies is justified for the high availability it provides, especially in big data environments where data loss can have significant repercussions.

Choosing a replication factor higher than three, such as four, would consume more storage resources unnecessarily, while a replication factor of two might not offer enough redundancy, particularly in the case of failures. Therefore, a replication factor of three is recommended as it strikes an optimal balance for reliability and resource utilization in HDFS