Fix GCP BigQuery Query Cache Errors
When working with GCP BigQuery, you may encounter a configuration error that prevents your data pipeline or messaging system from working. This guide explains the most common mistake with query cache and shows the exact fix.
A Common Mistake
Running the same expensive query multiple times without using cached results, wasting slot resources and increasing costs.
The incorrect command:
SELECT COUNT(DISTINCT user_id) FROM events WHERE event_date = '2024-01-15'
# Run 10 times by different analysts
Error output:
Each run: 30 seconds, 500 GB processed.
10 runs: 500 seconds, 5 TB total.
Cost: ~$25 total.
No results are cached because results_cache_mode is set to UNTIL_CHANGED and the query is not exactly byte-identical (different whitespace).
The Correct Approach
The right way to configure query cache in GCP BigQuery:
SELECT COUNT(DISTINCT user_id) FROM events WHERE event_date = '2024-01-15'
# Run once, use cached results
Successful result:
First run: 30 seconds, 500 GB.
Subsequent runs (same query text): <1 second, 0 bytes processed.
Cost: ~$2.50 (for first run only).
Cached results are used for identical queries for 24 hours.
How to Prevent This
Write queries with consistent formatting to maximize cache hits. Use the same SQL text for repeated queries. Cached results are invalidated when source data changes. Results are cached per user/project for ~24 hours. Use materialized views for transformed data that changes.
FAQ
Built by the developers of Doda Browser, DodaZIP, and Durga Antivirus Pro. Secure your cloud with DodaTech.
Built by the developers of DodaTech
Doda Browser, DodaZIP & Durga Antivirus Pro