Checkpoint writes to HDFS fail when storage capacity is exhausted, causing checkpoint timeout failures and preventing state persistence for fault tolerance.
Network connectivity issues between HDFS cluster nodes disrupt checkpoint data transfers, causing timeout failures and preventing distributed state snapshots from completing successfully.
DataNodes experiencing high block report delays prevent timely metadata synchronization with NameNode, causing slowdowns in checkpoint completion, job scheduling, and data replication operations.
Insufficient data block replicas in HDFS due to DataNode failures or network issues compromise fault tolerance for externalized checkpoints and savepoints, risking data loss on recovery.
NameNode failures due to hardware issues, resource exhaustion, or software bugs make the entire HDFS filesystem and all stored checkpoints/savepoints inaccessible, halting all Hadoop-dependent jobs.
Default HDFS write buffer settings cause RequestBodyTooLarge errors when writing files larger than ~12GB through Hadoop/HDFS commands, failing checkpoint persistence and data uploads.
When Hadoop jobs fail and restart without HA, reusing fixed job IDs causes FileAlreadyExistsException on checkpoint metadata files in HDFS, leading to JobManager crashes and restart loops.
