How To Fix BRAIN517 - Display table break point reached


BRAIN517 - Overview

  • Message type: E = Error

  • Message class: BRAIN -

  • Message number: 517

  • Message text: Display table break point reached

  • Show details Hide details
  • A piece of coding and the complex data structure SX_REPORT are generated
    for a query in a time-consuming process. The SX_REPORT is then stored
    in the cluster table RSIX and also redundantly for quicker access in the
    shared buffer.
    During this generation, the query definition and all of the metadata
    information (DTA class) are processed. A range of flags and control
    tables are created that accelerate the processing considerably during
    runtime.
    The following list gives an overview of the individual components:
    RKB1D: Along with the KEY of the query and the attributes
    from RSRREPDIR, this bar contains the execution mode, that is those
    flags that control the way in which the query is executed.
    RKB1F: All flags of the query are collected here. The
    most important flags are shown in the <ZK>Technical Information</>
    screen.
    BUGR: Detailed information about the elimination of
    internal business volume.
    <DS:TX.BRAIN-CELL>CELL</>: Structure elements or <DS:TX.BRAIN-KID>KID
    </>s.
    <DS:TX.BRAIN-CHAFREE>CHAFREE</>: Free characteristics of the query.
    COA: Attributes or their basic characteristics on which
    the cache depends.
    <DS:TX.BRAIN-CSX>CSX</>: Details of the selection of constants.
    CTTNM: Collects the currency translation types.
    <DS:TX.BRAIN-CUDIM>CUDIM</>: Controls currency translation.
    CUDIM_LRECH: Required for the unit abbreviations in the
    formula 'Before Aggregation'.
    CUDIM_SUMM: Analog ( see also <DS:TX.BRAIN-LRECH>SUMM und LRECH
    </>)
    IC_VAL: Validity slice characteristics for non-cumulative
    cubes.
    KFB: Describes which FEMS and which basic key figures go
    into a <DS:TX.BRAIN-KID>KID</> (authorization check).
    LFMM: Additional information for an S container for
    non-cumulatives.
    <DS:TX.BRAIN-LRECH>LRECH</>: Formulas after aggregation.
    PARTPROV: All parts of the MultiProvider with their own
    flags.
    <DS:TX.BRAIN-RTIME>RTIME</>: Times for non-cumulatives.
    <DS:TX.BRAIN-SEL>SEL</>: All selections.
    <DS:TX.BRAIN-SFC>SFC</>: All characteristics, navigation attributes and
    units.
    SFK: Collects all basic key figures.
    SH: Collects all hierarchies in the query.
    <DS:TX.BRAIN-SN>SN</>: Collects the hierarchy nodes.
    <DS:TX.BRAIN-LRECH>SUMM</>: Formulas after aggregation.
    <DS:TX.BRAIN-VAR>VAR</>: All variables.
    VAR_LRECH: Numerical variables with replacement paths.
    VCHECK: Controls the validation of variables, that is,
    the dependencies among variables.
    <DS:TX.BRAIN-VREP>VREP</>: Controls the replacement of variables.
    <DS:TX.BRAIN-VREP>VREP_CMP</>: Compounding information for the
    replacement of variables.
    <DS:TX.BRAIN-WGR>WGR</>: Description of S container

    The system issues an error message and will not allow you to continue with this transaction until the error is resolved.


    Error message extract from SAP system. Copyright SAP SE.


Smart SAP Assistant

  • What is the cause and solution for SAP error message BRAIN517 - Display table break point reached ?
    The SAP error message BRAIN517: Display table break point reached typically occurs in the context of SAP BW (Business Warehouse) or SAP BI (Business Intelligence) when you are trying to display a large dataset or when the system has reached a predefined limit for displaying data in a report or query.
    
    Cause: Data Volume: The error is often triggered when the volume of data being processed exceeds the limits set in the system configuration. Query Design: The design of the query or report may not be optimized for handling large datasets, leading to performance issues. System Settings: There may be system settings or parameters that limit the number of records displayed in a report or query.
    Solution: Limit Data Volume: Try to limit the amount of data being retrieved by applying filters or reducing the time frame of the data being queried. Optimize Queries: Review and optimize the query design. This may involve: Reducing the number of key

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