HA in Hadoop

High Availability (HA) in Hadoop is a critical feature that ensures that the Hadoop cluster remains operational even if some of the essential services fail. It minimizes the risk of system downtime, thereby providing uninterrupted service.

In Hadoop, HA is primarily implemented for the Hadoop Distributed File System (HDFS) NameNode and the YARN ResourceManager.

1. NameNode HA: In earlier versions of Hadoop, the NameNode was a single point of failure. If the NameNode failed, the entire HDFS cluster would become inoperative. NameNode HA solves this problem by having multiple NameNodes. Active and Standby NameNodes are configured, and they have the same metadata. If the Active NameNode fails, one of the Standby NameNodes takes over as the Active NameNode.
2. ResourceManager HA: ResourceManager manages resources and schedules applications in a Hadoop cluster. ResourceManager HA ensures that if the Active ResourceManager fails, a Standby ResourceManager can take over.

Here are some key components and considerations for implementing HA in Hadoop:

• ZooKeeper: Apache ZooKeeper is often used to automate the failover process. It helps in electing a new Active NameNode if the current one fails.
• Shared Storage: The metadata of the NameNode must be stored in shared storage, accessible by both the Active and Standby NameNodes, to ensure that they have consistent data.
• Fencing: This method prevents the “split-brain” scenario where two NameNodes believe they are the Active NameNode. Fencing ensures that the old Active NameNode is isolated if a new one has been elected.
• Configuration: Implementing HA requires careful planning and design. You’ll need to modify the Hadoop configuration files and ensure that the necessary network and hardware resources are available.