Salesforce Workbench Memory Error On Data Updates

 

Hi,

When I was working on inserting some records using Salesforce Workbench tool online, I received below error.

Error: "Workbench almost exhausted all its memory after only processing 0 rows of data. When performing a large data load, it is recommended to use a zipped request for processing with the Bulk API. To do so, rename your CSV file to 'request.txt', zip it, and try uploading again to Workbench."

Surprisingly the file I was using was not big enough that it would need to be split in to multiple files. It seems that this is another issue Workbench tool has discovered since last few weeks.

Please find workaround solution to above error below.

Solution:

1. Login to https://www.packmagix.com using your Salesforce credentials.

2. Click on Data Insert menu item in the Home tab for Data Insert operation. For other operations select other menu item as required.

3. Select a Salesforce Object you want to import . e.g. Account.

4. Default Mode of import is Parallel. Change it to Serial if required.

5. Default Batch Size is 2000. Change it if required.

6. Select a file to import using Browse button.

7. Sample data from the file will be displayed on screen.

8. Click on Map Fields button to automatically map the CSV file headers with selected Object fields by Field API Names.

9. If there are fields not auto mapped then select an Object field by searching it against corresponding CSV field name.

10. You can download the Field Mapping for your reference using Download as CSV button on Field Mapping table.

11. Click on Insert Records button to import all records from the CSV file you imported. Use Update / Upsert / Delete Records button for other operations.

12. Import results will be displayed for all batches of records processed with records failed and success counts.

13. Download the Batch results by selecting each Batch row and click on Download Selected Batch Results button.

14. You will see detailed report on data import errors and success for each row in CSV file you imported.