Answer-first summary for fast verification
Answer: Check the logs for any specific error messages related to the OutOfMemoryError.
Option B is the correct first step in troubleshooting a failed Spark job due to an OutOfMemoryError. Checking the logs will provide insights into the specific cause of the error, which could be due to various reasons such as memory leaks, inefficient data structures, or improper configuration. While options A and C could be part of the resolution strategy, they should be considered after diagnosing the issue. Option D is not advisable as it does not address the root cause of the failure.
Author: LeetQuiz Editorial Team
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As a data engineer, you are troubleshooting a failed Spark job. The job has failed with an OutOfMemoryError. What steps would you take to diagnose and resolve this issue?
A
Increase the memory allocated to the Spark executors.
B
Check the logs for any specific error messages related to the OutOfMemoryError.
C
Optimize the Spark job by reducing the data shuffling across the nodes.
D
Restart the Spark job without making any changes.
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