Hadoop HA

Hadoop High Availability (HA) is a critical feature in the Hadoop ecosystem that ensures the reliability and fault tolerance of Hadoop components, particularly the Hadoop Distributed File System (HDFS) and the ResourceManager in Hadoop YARN. HA is essential to minimize downtime and data loss in a Hadoop cluster. Here are key aspects of Hadoop High Availability:

1. NameNode HA (HDFS HA):

   • In HDFS, the NameNode is a critical component that manages the metadata and namespace of the file system. NameNode HA ensures that there is a standby NameNode that can take over in case the active NameNode fails.
   • HDFS HA typically involves configuring two NameNodes: one active and one standby. The standby NameNode keeps a synchronized copy of the active NameNode’s metadata. If the active NameNode fails, the standby can quickly take over, reducing downtime.

2. Quorum-based Journaling:

   • To keep the standby NameNode synchronized with the active NameNode, a quorum-based journaling mechanism is used. Journal nodes store and replicate the edit logs from the active NameNode to the standby NameNode.

3. ResourceManager HA (YARN HA):

   • In YARN, ResourceManager HA ensures the availability of the resource manager, which manages and allocates cluster resources for running applications. Like HDFS HA, ResourceManager HA involves having an active and standby ResourceManager.
   • The ResourceManager state, including application submissions and cluster resource information, is kept highly available by using ZooKeeper or another mechanism to manage failover.
4. Fencing Mechanisms:
5. • To prevent “split-brain” scenarios where both the active and standby components try to become active simultaneously, fencing mechanisms are implemented. Fencing ensures that only one component is active at any given time.

6. Automatic Failover:

   • Hadoop HA configurations are designed to automatically detect failures and initiate failover to the standby component. This minimizes the need for manual intervention during failures.

7. Data Replication (HDFS):

   • HDFS also provides data replication as a form of fault tolerance. Data is replicated across multiple DataNodes, so even if a DataNode fails, the data remains available from other replicas.

8. Client Redirection:

   • To maintain client access to HDFS and YARN resources during a failover event, HA configurations include mechanisms for client redirection to the new active component.

9. Configuration and Testing:

   • Setting up HA configurations in Hadoop requires careful configuration of components and thorough testing to ensure that failover works as expected.