Secondary Namenode: A Key Backup Component in Hadoop Cluster

Introduction

Apache Hadoop is a powerful open-source software framework for distributed storage and processing of big data on computer clusters. It consists of Hadoop Distributed File System (HDFS) for storage and MapReduce for processing data. However, with the growth of data, Hadoop clusters become bigger and more complex. As a result, it’s important to have a backup component to ensure high availability and fault tolerance. This is where Secondary Namenode comes in.

What is Secondary Namenode?

Secondary Namenode is a backup component in Hadoop clusters that performs similar functions as the primary Namenode. Essentially, it allows for the creation of a checkpoint for the primary Namenode. The checkpoint contains metadata related to the HDFS namespace, such as file-to-block mapping and replication factor. This metadata is critical for proper functioning of HDFS. By creating a checkpoint, Secondary Namenode provides a consistent view of HDFS’s namespace even in the event of Namenode failure. In addition, it can also be used to offload some Namenode operations such as periodic creation of snapshots and edits merging, thereby reducing the workload on the primary Namenode.

How does Secondary Namenode work?

Secondary Namenode periodically pulls a copy of primary Namenode’s namespace information and edits logs to generate a checkpoint, which is subsequently distributed to the datanodes for safekeeping. The checkpoint contains the most recent file-to-block mapping and replication factor, which makes it a crucial component in case of Namenode failure. The checkpoint, however, doesn’t contain the actual data stored in HDFS, which remains on the datanodes. The process of generating a checkpoint involves merging the namespace information and edits log of the primary Namenode. The edits log contains all the updates made to the namespace since the last checkpoint was created. Therefore, merging the edits log with the current namespace information is critical for maintaining consistency. It should be noted that the Secondary Namenode is not a failsafe mechanism. In case of primary Namenode failure, Automatic Failover can be configured to switch to a standby Namenode without any manual intervention.

Conclusion

A Secondary Namenode is a critical component in Hadoop clusters that enables high availability and fault tolerance. Its checkpointing mechanism ensures that metadata related to Namespace is always available for Namenode recovery. In addition, the secondary Namenode can be used to offload some of the Namenode’s workload. Secondary Namenode is not a fail-safe mechanism, and it should be used in conjunction with other fault-tolerant mechanisms such as Automatic Failover. Overall, Secondary Namenode is an integral part of the Hadoop ecosystem and has a significant role in ensuring the reliability and availability of HDFS infrastructure.