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When encountering intermittent failures in a series of Databricks jobs without a clear pattern, what approach should you take to diagnose and resolve these issues?
A
Implementing a comprehensive logging system within each job to gather detailed execution logs, followed by a post-failure analysis of these logs.
B
Employing a specialized monitoring tool tailored for Spark applications to obtain in-depth insights into job failures and performance challenges.
C
Leveraging Azure Databricks' built-in job monitoring capabilities to examine execution history and error logs for failure-inducing patterns.
D
Setting up Azure Monitor to alert on job failures and initiate Azure Logic Apps for prompt investigation and alerts.
