Explanation:
Diagnosing a memory error typically involves increasing the resources available to handle the workload. Reviewing and optimizing the code for memory usage is also crucial to prevent future failures.
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You are tasked with repairing and rerunning a failed Databricks job that processes large datasets. The job failed due to a memory error. Describe the steps you would take to diagnose the issue, modify the job settings, and ensure successful rerun of the job.
A
Increase the memory allocation for the cluster, review the code for memory-intensive operations, and rerun the job.
B
Reduce the dataset size, keep the cluster memory allocation unchanged, and rerun the job.
C
Add more worker nodes to the cluster, optimize the code for memory usage, and rerun the job.
D
Switch to a different cluster type with higher memory capacity, refactor the code to handle memory more efficiently, and rerun the job.