The error code DTS_E_PRIMEOUTPUTFAILED
in SQL Server Integration Services (SSIS) indicates that a component in a data flow task failed to produce the expected output. This error can be caused by various issues, such as data type mismatches, null values in non-nullable columns, or unexpected data format.
Here are steps to diagnose and resolve the DTS_E_PRIMEOUTPUTFAILED
error:
Review Error Details:
- Check the detailed error message in the SSIS log or error output. This can provide more context about which component failed and why.
Identify the Failing Component:
- Determine which component in the data flow task is causing the error. The error message should indicate the name or type of the component that failed.
Examine Data Flow Path:
- Look at the data flow path leading to the failing component. Check for any transformations, data conversions, or data sources that might be causing issues.
Check Data Types and Metadata:
- Ensure that data types are consistent across components. Mismatched data types can cause prime output failures.
- Verify that the metadata for the columns matches the expected data format.
Handle Null Values:
- Ensure that null values are properly handled. If a non-nullable column receives a null value, it will cause an error.
Inspect Data Quality:
- Check the source data for any anomalies or unexpected values that might cause the component to fail.
- Cleanse and validate data before processing it in the SSIS package.
Review Component Configuration:
- Check the configuration settings of the failing component. Ensure that all required properties and settings are correctly configured.
Enable Debugging and Logging:
- Enable SSIS logging to capture detailed information about the data flow execution. This can help pinpoint the exact cause of the failure.
- Use data viewers to inspect data at various points in the data flow to see where the issue arises.
Example Scenario and Solution
Scenario: A Data Conversion transformation is failing because it encounters a string value that cannot be converted to an integer.
Steps to Resolve:
Inspect the Source Data:
- Check the source data to identify any non-integer values in the column being converted.
Update Data Conversion Settings:
- Configure the Data Conversion transformation to handle invalid data gracefully, such as by redirecting rows with conversion errors to an error output.
Add Error Handling Logic:
- Add a Derived Column transformation before the Data Conversion to clean or filter the data. For example, you can use a conditional expression to replace invalid values with a default integer.
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