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Message type: E = Error
Message class: RSPLF - Planning Framework
Message number: 019
Message text: &1 records read, &2 generated, &3 changed, &4 deleted
Since SAP believes that this specific error message is 'self-explanatory,' no more information has been given.The majority of messages in the SAP system have a message text, however this is frequently insufficient to comprehend or resolve the problem.
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RSPLF019
- &1 records read, &2 generated, &3 changed, &4 deleted ?The SAP error message RSPLF019 is related to the SAP BW (Business Warehouse) system and typically occurs during the execution of a process chain or data load. This message provides a summary of the data processing results, indicating how many records were read, generated, changed, and deleted during the operation.
Cause:
The message RSPLF019 is not necessarily an error but rather an informational message that summarizes the results of a data processing operation. The numbers in the message represent:
If you are seeing this message in a context where you expected a different outcome (e.g., no records should have been deleted), it could indicate an issue with the data transformation or loading process.
Review the Process Chain: Check the process chain or data load that triggered this message. Ensure that the logic for data transformation and loading is correct.
Check Data Sources: Verify the data sources to ensure that they contain the expected data. If records are being deleted unexpectedly, it may be due to incorrect data handling or transformation rules.
Analyze Data Flow: Use transaction codes like RSA1 (Data Warehousing Workbench) to analyze the data flow and see where records are being generated, changed, or deleted.
Check for Data Quality Issues: Sometimes, data quality issues can lead to unexpected results. Ensure that the data being loaded meets the required quality standards.
Review Change Logs: If applicable, check change logs or audit trails to understand why certain records were deleted or changed.
Consult Documentation: Refer to SAP documentation or notes related to the specific data load or process chain for any known issues or additional guidance.
Testing: If possible, run the process in a test environment with a smaller dataset to observe the behavior and identify any issues without affecting production data.
If the message is part of a larger error context or if you are experiencing issues beyond this informational message, further investigation may be required to identify the root cause.
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