The situation you're describing, where the current usage exceeds the set quota limit, could be due to a few factors:
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Query Completion Time: If you ran a query that started before the quota was reached and it completed after the quota was exceeded, the total bytes processed by that query might push the usage over the limit. BigQuery processes queries atomically, meaning that if a query starts, it will complete even if it pushes you over your quota.
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Delayed Reporting: There could be a delay in the reporting of the quota usage. This means that some queries that were executed just before the limit was reached might only be reported after the limit has been exceeded.
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Quota Calculation Method: The way BigQuery calculates quota usage might not be straightforward. It could include additional factors like the data processed by query execution plans or other internal metrics.
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Caching: BigQuery does not charge for queries that return cached results, but it's possible that if the cache expires and the query re-runs, it could contribute to the quota unexpectedly.
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Background Processes: There might be background processes or automated scripts that are running queries on your behalf which you might not have accounted for.
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Billing Cycle Alignment: The quota usage might not align perfectly with the billing cycle, especially if changes to quotas are made mid-cycle.
If you consistently see that the usage exceeds the quota by a small margin and it's causing issues, you might want to set a slightly lower quota to create a buffer or reach out to Google Cloud Support for a more detailed explanation of how the quota usage is calculated and reported.
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