Ultimate access to all questions.
Upgrade Now 🚀
Sign in to unlock AI tutor
In a Spark Structured Streaming job that processes time-sensitive data, what is the best method to ensure fault tolerance and enable the job to recover from failures?
A
Disabling checkpoints to boost processing speed.
B
Utilizing local file storage for checkpointing to reduce latency.
C
Configuring HDFS or a cloud-based storage system for checkpointing the streaming state.
D
Depending entirely on Spark's in-memory state management for recovery.
