Athena Federated Query - MySQL - Lambda timeout troubleshooting

To troubleshoot the Lambda timeout issue in your Athena federated query to Aurora MySQL, you can take several steps:

1. Increase Lambda function timeout: Although you've already set it to the maximum of 15 minutes, this confirms that the operation is indeed taking longer than the allowed time.

2. Examine Lambda execution logs: Carefully review the CloudWatch logs for the Lambda function. Look for any error messages or warnings that might indicate the cause of the timeout.

3. Monitor Lambda function behavior: Pay close attention to memory usage and execution duration. You may need to adjust the memory allocation if the function is running out of resources.

4. Check federated data source logs: Look at the logs and error messages from your Aurora MySQL database to see if there are any issues or errors on that end.

5. Analyze query performance: Review the Athena query itself to see if it can be optimized. Consider breaking down the large query into smaller, more manageable chunks.

6. Investigate data quality: Since you mentioned the possibility of "bad data," examine the data in your Aurora MySQL database for any anomalies or inconsistencies that might be causing issues during the query execution.

7. Use Amazon Athena Query Metrics: These can provide insights into query performance and help identify bottlenecks.

8. Enable AWS X-Ray: This can help you trace and analyze the behavior of your Lambda function and identify performance bottlenecks.

9. Implement error handling and logging: Add more detailed logging and error handling in your Lambda function code to capture any issues that might occur during execution.

10. Consider using a different approach: For very large datasets, you might want to explore other data transfer methods like AWS Database Migration Service (DMS) or breaking down the data transfer into smaller batches.

As for increasing the log level of the Lambda function, you can modify your Lambda function's code to use a lower log level (e.g., DEBUG instead of INFO) and include more detailed logging statements throughout your code. This will provide more granular information about the function's execution.

Remember that there might be limitations with the ListTableMetadata API when dealing with a large number of tables. If possible, try to reduce the number of tables in your data source, aiming for fewer than 1000 tables per catalog for optimal performance.
Sources
Troubleshoot issues in Athena - Amazon Athena
Troubleshoot ETIMEDOUT error in my Lambda function | AWS re:Post