Post date: Feb 09, 2019 12:12:6 PM
Why there is issue of single point of failure in Hadoop?
As namenode is master and responsible for assigning task to slaves (datanodes)
when it fails it will take down whole cluster and lose of connection with datanodes impacting availability of data. Hence it’s a problem
Which is the single node (single point), which is very critical in Hadoop cluster
Namenode is single point which is very critical. It can be considered as starting point for the task which assigns further work to slaves. Failing of namenode affects availability of data which is one of the pillar for hadoop. So it’s very critical.
What are the available solutions to handle single point of failure in Hadoop 1?
To handle the single point of failure, we can use another setup configuration which can backup NameNode metadata. If the primary NameNode will fail our setup can switch to secondary (backup) and no any type to shutdown will happen for Hadoop cluster.
How Single point of failure issue has been addressed in Hadoop 2?
HDFS High Availability of Namenode is introduced with Hadoop 2. In this two separate machines are getting configured as NameNodes, where one NameNode always in working state and anther is in standby. Working Name node handling all clients request in the cluster where standby is behaving as the slave and maintaining enough state to provide a fast failover on Working Name node.