How does Hadoop handle data replication and its significance in a Hadoop cluster

Hadoop handles data replication by replicating data blocks across different nodes in a cluster. The default replication factor in Hadoop is 3, meaning each data block is replicated three times for fault tolerance and data reliability.

The significance of data replication in a Hadoop cluster includes:

• Fault Tolerance: Data replication ensures that even if a node fails, the data is still available on other nodes, reducing the risk of data loss.
• Performance: Replicating data allows for parallel processing and faster data access as multiple copies of the data are available on different nodes.
• Reliability: With multiple copies of data spread across nodes, the chances of data loss due to hardware failure are minimized, ensuring data integrity.
• Load Balancing: Replicating data helps in distributing the read and write load across nodes, improving overall cluster performance.