BigQuery Export Limitations

BigQuery Export Limitations

Info
Your data exports to BigQuery may encounter errors in certain situations such as large export sizes. This article will help you identify and resolve common BigQuery export issues including timeout errors, "Failed to Fetch" errors, and hung exports.

Date Field Requirement

Data Builder reports exported to BigQuery must include at least one date field.

Alert
Without a date field, the export will fail to complete successfully.

To resolve this issue:

  1. Go to Reports > Data Builder and locate your report.
  2. Click the three-dots action menu and select Edit.
  3. Add the date field Date to your report.
  4. Click Save Changes and run your export again.

Export Limitations

If you are using connectors other than Facebook Ads or GA4, make sure the report you are trying to export contains fewer than 40,000 rows of data. If you are backfilling a large amount of your historical data into BigQuery, you may need to take additional steps to make sure your exports are under BigQuery's limits. This limitation does not apply to Facebook Ads or GA4. 

Your export should run in under 10 minutes. If the export runs for 30 minutes or more, it has hung and needs to be cancelled. To stop the hung export, click Edit Export.

The BigQuery section of your PMA hub, highlighting the pencil icon to edit one of the exports.

Do not make any changes to the export. Click Update.

The dialog box to configure the export.

The hung export is now stopped.

Timeout Errors and "Failed to Fetch" Errors

When exporting large or complex datasets, you may encounter timeout errors or "Failed to Fetch" errors. These errors typically occur when requesting too much data at once, such as a report with many fields covering a long date range.

Common causes of timeout errors:

  • Long date ranges (e.g., a full year of data)
  • Large number of fields in one report
  • Excessive use of live fields (indicated by the lightning bolt ⚡ icon in Schema Explorer)

Understanding Live Fields

Live fields trigger real-time API calls to the source platform each time data is requested. While they provide the most current data, excessive use of live fields can cause timeouts, especially with long date ranges. You can identify live fields in the Schema Explorer by looking for the yellow lightning bolt icon (⚡) next to the field label.

How to Resolve Timeout Errors

To resolve timeout or "Failed to Fetch" errors, try the following approaches:

  1. Split by time period: Instead of exporting a full year at once, run separate exports for quarterly segments (Q1, Q2, Q3, Q4).
  2. Reduce live fields: Remove fields marked with the ⚡ icon to eliminate real-time API calls. Use Schema Explorer to identify these fields.
  3. Limit fields per report: Group related fields into separate reports (e.g., one report for order metrics, another for product metrics, another for customer data).

How to accommodate large datasets

If your data has caused the export to hang, try segmenting the overall date range into two smaller date ranges. Edit the report in Data Explorer to use the first date range, then go to BigQuery and run your export.

If your export completes successfully: 
  1. Return to Data Explorer.
  2. Edit your report and set Date Range to the second date range.
  3. Go to BigQuery and run your export again.
If your export is unsuccessful:

You may need to segment the overall date range into four or more date ranges.
  1. Reduce the size of the date range until the export runs successfully, indicating this range is within BigQuery's export limits.
  2. Run the export for each date range according to the instructions above.



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