You can backfill data for up to 2 years for most PMA connectors. In your first report in Data Explorer, set the date range to the entire range of data you want to export and click Set Range.
Rolling updates
In BigQuery, click Edit Export. Refresh period can be set to monthly, weekly, daily, or hourly.
Make sure your report's date range in Data Explorer is at least as long as the refresh period in BigQuery. Failing to do so may result in data missing from your backfill.
For example:
- If your report's date range is one week but your export refreshes monthly, your export will fail to include data from before the last week of the month.
- If your report's date range is one week and your export refreshes daily, your export will overwrite the past seven days, every day.
A range of 30 days with a daily or weekly refresh period can be an ideal choice for e-commerce to settle orders that are returned. However, excessively frequent backfills with large date ranges, such as a year's data refreshed every hour, can cause BigQuery to hang. Frequent large requests can also increase your BigQuery charges.
Date Partitioning
How PMA exports to BigQuery
When your export runs, we will first delete any of your export data in BigQuery that falls within the date range of your export. We will then create new tables based on the date range of your export and populate these tables with the export data.
Exports ranging less than 60 days
Our exports to BigQuery are partitioned by date. Exports that span less than 60 days will be partitioned by day. In Google Cloud console, the daily partitions are visible under the Filter dropdown next to the table name.
Exports ranging 60 days or more
Exports spanning 60 days or more will be partitioned by month. In Google Cloud console, monthly partitions are visible under the Filter dropdown next to the table name.