When encountering a quotaExceeded error in BigQuery, you should follow these steps to diagnose and mitigate the issue:
* Understand the Error:
* The error message indicates that a quota was exceeded (either a short-term rate limit or a longer- term limit).
* The response payload contains information about which quota was reached.
* Quotas can fall into two categories:
* rateLimitExceeded: Short-term limits. Retry the operation after a few seconds using exponential backoff.
* quotaExceeded: Longer-term limits. Wait 10 minutes or longer before retrying the operation.
* Search Errors in Cloud Audit Logs (Option A):
* Cloud Audit Logs provide detailed information about API requests and responses.
* By searching the logs, you can identify the specific API call that triggered the quotaExceeded error.
* This helps you understand which resource or operation exceeded the quota.
* View Errors in Cloud Monitoring (Option C):
* Cloud Monitoring (formerly known as Stackdriver) provides insights into your Google Cloud resources.
* Check the monitoring dashboard for any alerts related to BigQuery quotas.
* You can set up custom monitoring rules to track specific quotas and receive notifications.
* Other Options:
* B. Configure Cloud Trace: Cloud Trace is used for performance analysis and latency tracking. It' s not directly related to quota issues.
* D. Use Information Schema Views: Information schema views provide metadata about your datasets and tables but won't help diagnose quota errors.
* E. Use BigQuery Bl Engine: There is no such tool called "BigQuery Bl Engine." This option is invalid.
Remember that some quotas replenish incrementally over a 24-hour period, so you don't always need to wait a full 24 hours after reaching the limit. If you consistently hit longer-term quotas, consider workload optimization or requesting a quota increase