How To Fix U6032 - Maximum number of error extracts allocated


U6032 - Overview

  • Message type: E = Error

  • Message class: U6 - Message Class for BRE

  • Message number: 032

  • Message text: Maximum number of error extracts allocated

  • Show details Hide details
  • What causes this issue?

    There is an upper limit for the number of error extracts that can be
    allocated to an agent. You have reached this limit.

    System Response

    No new error extracts have been added to the worklist.

    How to fix this error?

    Process the error extracts that are allocated to you. Once you have done
    this, you can allocate yourself a new worklist.

    Procedure for System Administrators

    In the table 'define error extracts per agent group', you can specify
    the maximum number of error extracts that can be allocated to an agent
    per message class/message number. If you do not enter anything here, the
    system uses the default maximum of 10 error extracts.

    Error message extract from SAP system. Copyright SAP SE.


Smart SAP Assistant

  • What is the cause and solution for SAP error message U6032 - Maximum number of error extracts allocated ?
    The SAP error message U6032, which states "Maximum number of error extracts allocated," typically occurs in the context of data extraction processes, particularly when dealing with data transfer or data extraction jobs in SAP systems. This error indicates that the system has reached the limit of error extracts that can be processed or stored during a data extraction operation.
    
    Cause: Exceeded Limits: The error is usually caused by exceeding the maximum number of error extracts that can be allocated. This can happen if there are numerous errors during the data extraction process, leading to a backlog of error records. Configuration Settings: The system may have specific configuration settings that limit the number of error extracts. If these settings are not adjusted to accommodate the volume of data being processed, this error can occur. Data Quality Issues: Poor data quality or inconsistencies in the source data can lead to multiple errors during extraction, contributing to

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