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Message type: E = Error
Message class: CNV20551 - message for package 20551 (company code delete)
Message number: 359
Message text: Field length exceeded; defined length: &1 (domain &2); input length: &3
The specified value for the field length (&V3&) is higher than the
defined length value (&V1&) for the domain of the given object type
(OBJECTTYPE=&V2&).
The system issues an error message and will not allow you to continue with this transaction until the error is resolved.
The specified value is obviously not correct.
Check this and correct the value as required.
Error message extract from SAP system. Copyright SAP SE.
CNV20551359
- Field length exceeded; defined length: &1 (domain &2); input length: &3 ?The SAP error message CNV20551359 indicates that a field's input length exceeds the defined length for that field in the database. This error typically occurs during data migration or data import processes, where the data being processed does not conform to the expected format or length defined in the SAP system.
Cause:
- Data Length Mismatch: The input data for a specific field is longer than the maximum length defined for that field in the database schema.
- Incorrect Data Mapping: During data migration, the mapping of source data to target fields may not have been configured correctly, leading to longer input values.
- Data Quality Issues: The source data may contain unexpected characters or formatting that increase the length of the data being imported.
Solution:
- Check Field Definitions: Review the field definitions in the SAP system to understand the maximum allowed length for the field in question. This can usually be found in the Data Dictionary (SE11).
- Validate Input Data: Inspect the input data to identify any values that exceed the defined length. You may need to truncate or modify these values to fit within the allowed limits.
- Adjust Data Mapping: If the error occurs during a data migration process, ensure that the mapping of source fields to target fields is correct and that the lengths are compatible.
- Data Cleansing: Implement data cleansing processes to ensure that the data being imported adheres to the expected formats and lengths.
- Error Handling: If applicable, implement error handling in your data import process to catch and log these errors for further analysis.
Related Information:
By following these steps, you should be able to identify the cause of the error and implement a solution to resolve it.
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