That sounds like an unexpectedly high cost for data extraction. The billing in BigQuery can sometimes be influenced by the way you're extracting the data. Here are a few potential reasons for this discrepancy:
If you're extracting the data and transferring it to another location or service within North America, you might be incurring egress charges for that transfer. Even if the data extraction itself is within the free tier limits, moving data to another Google Cloud service or to a different location could accrue additional costs.
Inefficient queries that scan unnecessary data or use JOINs extensively can result in higher-than-expected costs. Optimizing your SQL queries to minimize data scanned can reduce costs significantly.
You can try exporting data in a compressed format like gzip can reduce the size of data transferred, potentially decreasing egress charges.
Sometimes, the charges might be due to other activities within your Google Cloud project that generate egress traffic. Ensure that there aren't any other processes or services causing high egress traffic within your project.
To troubleshoot:
1. Double-check the settings and destination of your data extraction process.
2. Review the query used for extraction to ensure it's optimized.
3. Consider using compression and efficient file formats during extraction.
4. Monitor other activities within your project that might be contributing to egress traffic.
For a better solution, reach out to Google Cloud Support with specific details about your extraction process and billing concerns could help in identifying the exact reason behind the unexpected charges.
LinkedIn
Twitter
