Troubleshooting Import Errors

Import Management > All > [Select Import Job on screen]

This page outlines the common import validation and parsing errors found in Replenishment +. Use the tables below to determine the root of the error and potential solutions for the issue.

Validation Errors

Validation errors are some of the most common import errors. These arise when the data in the file does not match the data type required for the field or if the data does not match the rules for the field.

Validation errors will often display the rule that has been broken by the error in the Error field. This will be a helpful reference for many of the errors as they give a hint on how to fix the validation error.

Parts with validation errors will still be uploaded into R+ and the data will be changed or removed.

Validation Error	Definition	Solution
key_notfound	The PartNumber-Revision-Location combination in the row does not exist in R+.
key_alreadyexists	Indicates a duplicate record in the file.	Confirm whether the record is a duplicate or a typo in the file. Fix or remove the duplicate row from the CSV.
generic_warning	Multiple warnings fall under this category, usually because the data does not match a specific rule. See the Error column to view particular rule. A data point with warning will still be uploaded - it is usually just changed to 0.	Ensure the value in the row in the CSV file follows the rule in the Error field in R+.
generic_error	Multiple errors fall under this category, usually because the data does not match a specific rule. See the Error column to view particular rule.	Ensure the value in the row in the CSV file follows the rule in the Error field in R+.
circular_reference	Found only in Bill of Materials file. Indicates that the row contains a parent-child relationship that already exists in the file.	Remove the row from the file. Reconfirm that all required parent-child relationships for the Finished Good are included in the file.
GreaterThanValidator	The values entered are below a certain quantity, usually 0. When this happens, the value with this error will be changed to 0. See the error field to see what the acceptable quantity for this field is.	Fix the values in those rows in the CSV file by ensuring they are greater than the quantity specified in the Error field in R+ (usually 0).
LengthValidator	The values entered are greater than a specified length for the field. When this happens, the value with this error will erased and the field will be made blank. See the Error field to see what the acceptable quantity for this field is.	Fix the text/values in those rows in the CSV file by ensuring they are less than the quantity specified in the Error field in R+.
InclusiveBetweenValidator	The values entered are outside a specified range for the field. When this happens, the value with this error will be changed to 0. See the Error field to see what the acceptable range is.	Fix the value in the row in the CSV file by ensuring it falls between the range listed in the Error field in R+.

Parsing Errors

Parsing errors are less common but can be more difficult to resolve. These arise when there is an issue with the structure of the file. R+ does not recognize how to import the data that is in the file and does not import or recognize any of the data.

Each Parsing Error will contain a "carrot" dropdown arrow that will expand on the source of the issue. The below example will walk through how to read one of these errors using the dropdown.

• Row - The row in the CSV file

• Type - The file type

• Field Index - The number of column with the error in it (e.g. 9 = column I in the CSV file)

• Field Name - The name of the column with the error in it

• Field Value - The value in the file that is sparking the error. (e.g. ' ' = the field is blank)

There will often be two gray boxes that list the same information, followed by a third gray box that explains how R+ will process the field that has the error. In the example above, R+ does not recognize the ADU field and will mark the field as null.