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Message type: E = Error
Message class: MDQ_RM_PROCESS - MDQ Rule Mining Process Message Class
Message number: 028
Message text: Checked Field not unique within mining result at index &1.
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MDQ_RM_PROCESS028
- Checked Field not unique within mining result at index &1. ?The SAP error message MDQ_RM_PROCESS028 indicates that there is a problem with the uniqueness of a checked field within a mining result at a specified index. This error typically arises in the context of SAP's Data Mining or Predictive Analytics functionalities, where the system expects certain fields to be unique for processing.
Cause:
The error occurs when the system encounters duplicate values in a field that is expected to be unique. This can happen due to:
- Data Quality Issues: The dataset being processed may contain duplicate entries for the field that is supposed to be unique.
- Incorrect Configuration: The configuration of the mining model or the data source may not be set up correctly, leading to conflicts in expected uniqueness.
- Data Preparation Errors: During the data preparation phase, if the data is not properly cleaned or transformed, it can lead to duplicates.
Solution:
To resolve this error, you can take the following steps:
Check Data for Duplicates:
- Review the dataset being used for the mining process. Look for duplicate entries in the field that is causing the issue.
- Use SQL queries or data profiling tools to identify and eliminate duplicates.
Data Cleansing:
- If duplicates are found, you may need to cleanse the data. This could involve removing duplicates, aggregating data, or ensuring that the field values are unique.
Review Model Configuration:
- Check the configuration of the mining model to ensure that it is set up correctly. Make sure that the fields defined as unique are indeed unique in the dataset.
Adjust Data Preparation Steps:
- If you are using data preparation steps (like transformations or aggregations), ensure that these steps do not inadvertently create duplicates.
Re-run the Mining Process:
- After addressing the duplicates and ensuring the data is clean, re-run the mining process to see if the error persists.
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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