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Answer: All of the above.
Option D is the correct answer. Troubleshooting a data transformation job with performance issues requires a comprehensive approach. First, you should check the Glue job logs for any error messages or warnings that can provide insights into the root cause of the issue. Reviewing the custom script can help identify any logic errors or inefficiencies in the transformation process. Next, monitoring the job's performance metrics, such as CPU and memory usage, can help determine if the allocated resources are sufficient or if adjustments are needed. Finally, verifying the data format and schema in the S3 bucket and ensuring that the Glue data catalog is correctly configured can help prevent data-related issues that may impact performance. By taking all these steps, you can identify and resolve the performance issues in the data transformation job.
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You are troubleshooting a data transformation job that is experiencing performance issues. The job is using AWS Glue to read data from an Amazon S3 bucket, transform it using a custom script, and write the result back to S3. Which of the following steps should you take to identify and resolve the issue?
A
Check the Glue job logs for any error messages or warnings and review the custom script for potential issues.
B
Monitor the Glue job's performance metrics, such as CPU and memory usage, and adjust the allocated resources if necessary.
C
Verify that the data in the S3 bucket is in the expected format and schema, and ensure that the Glue data catalog is correctly configured.
D
All of the above.