What is the data replication mechanism in Hadoop?
The Hadoop data replication mechanism is implemented through the Hadoop Distributed File System (HDFS). In HDFS, data is divided into multiple data blocks, and each data block is replicated multiple times and stored on different nodes to achieve fault tolerance and high availability. By default, each data block is replicated 3 times, meaning it is stored on 3 different nodes.
The data replication mechanism in Hadoop ensures that data remains available in case of node failure by using multiple copies of data to replace the data on the faulty node. Additionally, data replication can also improve data access performance by fetching data from the nearest node rather than a remote one.
Hadoop also offers mechanisms to optimize data replication, such as adjusting the number of replica copies and prioritizing nodes with better hardware performance for data replication. These optimizations can be configured based on specific needs and performance requirements.
More tutorials
What are the differences between Storm and Hadoop?(Opens in a new browser tab)
How to handle a failure of a Hadoop data node(Opens in a new browser tab)
What are the replication strategies available in Cassandra?(Opens in a new browser tab)
How to handle the issues of node failure and data recovery in Cassandra?(Opens in a new browser tab)
How to add or remove nodes in a Cassandra cluster?(Opens in a new browser tab)