How To Fix FINS_ML_ACDOCA_UTIL004 - Parallel precompacting processing: system or communication failure.


FINS_ML_ACDOCA_UTIL004 - Overview

  • Message type: E = Error

  • Message class: FINS_ML_ACDOCA_UTIL - Messages for XPRA

  • Message number: 004

  • Message text: Parallel precompacting processing: system or communication failure.

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  • Self-Explanatory Message

    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.

    To make things easier, more detailed information is frequently added to describe the issue, how to fix it, and the necessary steps or configuration modifications.

    Unfortunately, there isn't any extra information in this error notice.



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Smart SAP Assistant

  • What is the cause and solution for SAP error message FINS_ML_ACDOCA_UTIL004 - Parallel precompacting processing: system or communication failure. ?
    The SAP error message FINS_ML_ACDOCA_UTIL004 indicates a problem during the parallel precompacting processing of the ACDOCA table, which is part of the Universal Journal in SAP S/4HANA. This error typically arises due to system or communication failures during the execution of a background job or a process that involves data manipulation in the ACDOCA table.
    Causes:
    
    System Resource Issues: Insufficient memory or CPU resources can lead to failures in processing.
    Database Locking: If the ACDOCA table is locked by another process, it can cause communication failures.
    Network Issues: Problems with network connectivity can interrupt communication between the application server and the database.
    
    Configuration Issues: Incorrect settings in the system configuration can lead to failures in parallel processing. Software Bugs: There may be bugs in the SAP software that affect the processing of ACDOCA. Solutions: Check System Resources: Monitor the system's CPU and memory usage. If resources are low, consider increasing them or optimizing other processes. Review Background Jobs: Check

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