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. Ifyou consistently hit longer-term quotas, consider workload optimization or requesting a quota increase
