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Message type: E = Error
Message class: CNV_10020 - Message class for package 10020
Message number: 090
Message text: Data for &1 &2 has already been written in table &3
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CNV_10020090
- Data for &1 &2 has already been written in table &3 ?The SAP error message CNV_10020090 indicates that there is an attempt to write data to a table where the data for the specified key (identified by &1 and &2) has already been written. This typically occurs during data migration or data transfer processes, especially when using SAP's data migration tools or during system conversions.
Cause:
- Duplicate Data: The most common cause of this error is that the data being processed is already present in the target table. This can happen if the migration process is run multiple times without proper cleanup or if there are overlapping data sets.
- Incorrect Logic in Data Migration: If the logic used to extract or transform data is flawed, it may lead to attempts to insert records that already exist.
- Concurrency Issues: If multiple processes are trying to write to the same table simultaneously, it may lead to conflicts and this error.
Solution:
- Check for Duplicates: Before running the migration or data transfer process, check the target table for existing records that match the keys (identified by &1 and &2). If duplicates are found, you may need to adjust your data extraction or transformation logic.
- Adjust Migration Logic: Review the data migration logic to ensure that it correctly handles existing records. This may involve implementing checks to skip records that already exist or updating them instead of inserting.
- Use Transaction Management: If applicable, implement transaction management to ensure that data is written in a controlled manner, reducing the chances of concurrency issues.
- Cleanup Previous Data: If the previous migration runs are no longer needed, consider cleaning up the target table before re-running the migration.
- Log and Analyze: Enable detailed logging during the migration process to capture more information about the records being processed. This can help identify patterns or specific records causing the issue.
Related Information:
By following these steps, you should be able to identify the root cause of the error and implement a solution to resolve it.
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