Message type: E = Error
Message class: CK - Product Costing Messages
Message number: 575
Message text: Internal error during parallel processing
The status information is contradictory. Server &v1& is still in the
list of active modes, but the system cannot find any parallel modes.
The row of materials that was being processed when the error occurred
begins with material/plant &v2& and ends with material/plant &v3&.
The program running on server &v1& probably attempted to issue some
type of error message. At the present time, this is not supported by
background parallel processing.
The system ends the run.
&What_to_do&
Start the run again, either online or (without parallel processing) in
the background. You only have to select costing level &v4& for
processing because that is where the error occurred.
Now when the error occurs, it will either be displayed (if you are
working online) or will cause a termination (if you are working in
background mode). In any case you will receive more information on the
error.
Error message extract from SAP system. Copyright SAP SE.
CK575
- Internal error during parallel processing ?The SAP error message CK575, which states "Internal error during parallel processing," typically occurs in the context of the Controlling (CO) module, particularly during the execution of costing runs or when processing large volumes of data in parallel. This error can be caused by various factors, including system configuration issues, data inconsistencies, or resource limitations. Causes: System Resource Limitations: Insufficient memory or CPU resources can lead to internal errors during parallel processing. Data Inconsistencies: Issues with the data being processed, such as missing or corrupted records, can trigger this error.
Configuration Issues: Incorrect settings in the costing configuration or parallel processing parameters may lead to errors. Software Bugs: There may be bugs in the SAP version you are using that affect parallel processing. Solutions: Check System Resources: Monitor the system's memory and CPU usage. If resources are low, consider increasing them or optimizing the workload. Review Data Integrity: Check for inconsistencies in the data being processed. This may
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