How To Fix RSAR197 - Record &:Contents & from field & cannot be converted in type & ->longtext

SAP Error Message - Details

• Message type: E = Error

• Message class: RSAR - Data Transfer and Metadata Maintenance

• Message number: 197

• Message text: Record &:Contents & from field & cannot be converted in type & ->longtext

What causes this issue?

Value '&V2&' from field &V3& is not convertible into the DDIC data type
&V4& in data record &V1&. The field content could not be transferred int
o the typed transfer structure.

System Response

The data to be loaded has a data error.
The loading of the InfoPackage from the source system was cancelled.

How to fix this error?

Check the source data in the source system for conformity.
If the data in the source system is correct or the error for each data r
ecord occurs cumulatively, an extractor error probably exists. This can
originate from programs or DDIC structures in the extraction environment
that are no longer current.
Replicate and regenerate the DataSource.
If you load the InfoPackage in the mode <LS>Start Data Load Immedi
ately</>, a new call of the Data Warehousing Workbench is necessary
after the generation of the DataSource(s).

Procedure for System Administrators

The system issues an error message and will not allow you to continue with this transaction until the error is resolved.

Error message extract from SAP system. Copyright SAP SE.

Smart SAP Assistant

• What is the cause and solution for SAP error message RSAR197 - Record &:Contents & from field & cannot be converted in type & ->longtext ?

  The SAP error message RSAR197 typically indicates an issue with data conversion during the extraction or loading process, particularly when dealing with long text fields. This error occurs when the system attempts to convert a record from one data type to another, and the conversion fails due to incompatible data formats or lengths.
  Cause:
  
  Data Type Mismatch: The source field's data type does not match the target field's expected data type. For example, if the source field is a string and the target expects a long text format, the conversion may fail.
  Length Exceedance: The data in the source field exceeds the maximum length that can be accommodated in the target field.
  Invalid Characters: The source data may contain characters that are not valid for the target field type.
  Configuration Issues: There may be issues in the configuration of the data extraction or transformation process, such as incorrect mappings or transformations.
  
  Solution:
  
  Check Data Types: Verify that the data types of the source and target fields are compatible. Ensure that the source field can be converted to the target field's data type.
  Adjust Field Lengths: If the source data exceeds the target field's length, consider increasing the length of the target field or truncating the source data appropriately.
  Data Cleansing: Review the source data for any invalid characters or formats that may cause conversion issues. Cleanse the data as necessary.
  Review Transformation Logic: If you are using a transformation process (like in SAP BW), check the transformation rules and mappings to ensure they are correctly defined.
  Debugging: Use transaction codes like RSA3 (for data extraction) or RSA1 (for data modeling) to test the extraction process and identify the specific record causing the issue.
  Consult Documentation: Refer to SAP documentation or notes related to the specific version you are using for any known issues or additional troubleshooting steps.
  
  Related Information:
  
  Transaction Codes: 
  
  RSA3: Test Data Extraction
  RSA1: Data Warehousing Workbench
  
  
  SAP Notes: Check for any relevant SAP Notes that may address this specific error or provide additional context.
  Data Dictionary: Review the data dictionary (SE11) for the relevant tables and fields to understand their definitions and constraints.
  
  If the issue persists after trying the above solutions, consider reaching out to SAP support or consulting with a technical expert who specializes in SAP data extraction and transformation processes.