Answer-first summary for fast verification
Answer: Adjust the task to incorporate a timeout mechanism that terminates the job if it exceeds 15 minutes.
The correct approach is to modify the task to include a timeout that will terminate the job if it runs longer than the expected 15 minutes. This directly addresses the issue of jobs stalling due to network packet drops by ensuring they do not run indefinitely. For more details, refer to the [Databricks documentation on job timeouts](https://docs.microsoft.com/en-us/azure/databricks/data-engineering/jobs/jobs#timeout).
Author: LeetQuiz Editorial Team
Ultimate access to all questions.
The data engineering team has observed that a job, which typically completes in 15 minutes, occasionally stalls during the reading of remote databases due to network packet drops. Which of the following actions would best enhance the job's stability?
A
Utilize the Databricks REST API to monitor and terminate long-running jobs.
B
Adjust the task to incorporate a timeout mechanism that terminates the job if it exceeds 15 minutes.
C
Employ the Jobs runs, active runs UI section for monitoring and terminating long-running jobs.
D
Apply the Spark job timeout setting available in the Spark UI.
E
Configure the cluster timeout setting in the Job cluster UI.
No comments yet.