Sometimes, very large exports can become unstable and time out. It's very common to have exports that are several hundreds of fields wide and most of the time those exports will run without any issues. However, there are cases when the data volumes in combination with a very wide schema can cause exports to consistently fail.
Fortunately, there are ways to improve stability.
Option 1: Reduce the number of fields in the export
An easy fix is to reduce the number of fields in the export. Ask yourself if you need all the chosen fields. If not, take them out of the selection.
Calculated fields can be extra computation heavy, for example those based on Date, like Week number (ISO), Year, Week number, Month, Day of week, Week and Month number. Removing those can help.
Option 2: Split the export into smaller parts
If you need all of the chosen fields, you can get it to work by splitting up the export.
One common and recommended way to split up your export is to do it by Data Source type. For this, you would set up one export per Data Source type (one for X Ads, one for Facebook, etc).
To do this, create a new export and select only the fields you want from the specific Data Source type. Then add a filter like; 'Data Source type' exactly matches (e.g. Facebook ads) to filter out values from common fields such as Cost.
Duplicate the export and make one for each Data Source type that you want to export.
This also gives you the benefits of a more clean schema and resulting dataset where there are fewer empty rows.
If you still have issues with your export, please reach out to the Support Chat or send an email to email@example.com.