CREATEWHATIFFORECAST()`¶

About CreateWhatIfForecast¶

A what-if forecast is a forecast that is created from a modified version of the baseline forecast. Each what-if forecast incorporates either a replacement dataset or a set of transformations to the original dataset.

Method Signature¶

METHODS /AWS1/IF_FCS~CREATEWHATIFFORECAST
  IMPORTING
    !IV_WHATIFFORECASTNAME TYPE /AWS1/FCSNAME OPTIONAL
    !IV_WHATIFANALYSISARN TYPE /AWS1/FCSARN OPTIONAL
    !IT_TIMESERIESTRANSFORMATIONS TYPE /AWS1/CL_FCSTIMESERIESTRANSF00=>TT_TIMESERIESTRANSFORMATIONS OPTIONAL
    !IO_TIMESERIESREPLCMTSDATASRC TYPE REF TO /AWS1/CL_FCSTIMESERIESREPLCS00 OPTIONAL
    !IT_TAGS TYPE /AWS1/CL_FCSTAG=>TT_TAGS OPTIONAL
  RETURNING
    VALUE(OO_OUTPUT) TYPE REF TO /aws1/cl_fcscreatewhatiffcrsp
  RAISING
    /AWS1/CX_FCSINVALIDINPUTEX
    /AWS1/CX_FCSLIMITEXCEEDEDEX
    /AWS1/CX_FCSRESRCALRDYEXISTSEX
    /AWS1/CX_FCSRESOURCEINUSEEX
    /AWS1/CX_FCSRESOURCENOTFOUNDEX
    /AWS1/CX_FCSCLIENTEXC
    /AWS1/CX_FCSSERVEREXC
    /AWS1/CX_RT_TECHNICAL_GENERIC
    /AWS1/CX_RT_SERVICE_GENERIC.

IMPORTING¶

Required arguments:¶

`iv_whatifforecastname` `TYPE /AWS1/FCSNAME` `/AWS1/FCSNAME`¶

The name of the what-if forecast. Names must be unique within each what-if analysis.

`iv_whatifanalysisarn` `TYPE /AWS1/FCSARN` `/AWS1/FCSARN`¶

The Amazon Resource Name (ARN) of the what-if analysis.

Optional arguments:¶

`it_timeseriestransformations` `TYPE /AWS1/CL_FCSTIMESERIESTRANSF00=>TT_TIMESERIESTRANSFORMATIONS` `TT_TIMESERIESTRANSFORMATIONS`¶

The transformations that are applied to the baseline time series. Each transformation contains an action and a set of conditions. An action is applied only when all conditions are met. If no conditions are provided, the action is applied to all items.

`io_timeseriesreplcmtsdatasrc` `TYPE REF TO /AWS1/CL_FCSTIMESERIESREPLCS00` `/AWS1/CL_FCSTIMESERIESREPLCS00`¶

The replacement time series dataset, which contains the rows that you want to change in the related time series dataset. A replacement time series does not need to contain all rows that are in the baseline related time series. Include only the rows (measure-dimension combinations) that you want to include in the what-if forecast.

This dataset is merged with the original time series to create a transformed dataset that is used for the what-if analysis.

This dataset should contain the items to modify (such as item_id or workforce_type), any relevant dimensions, the timestamp column, and at least one of the related time series columns. This file should not contain duplicate timestamps for the same time series.

Timestamps and item_ids not included in this dataset are not included in the what-if analysis.

`it_tags` `TYPE /AWS1/CL_FCSTAG=>TT_TAGS` `TT_TAGS`¶

A list of tags to apply to the what if forecast.

RETURNING¶

`oo_output` `TYPE REF TO /aws1/cl_fcscreatewhatiffcrsp` `/AWS1/CL_FCSCREATEWHATIFFCRSP`¶

Domain /AWS1/RT_ACCOUNT_ID

Primitive Type NUMC

Examples¶

Syntax Example¶

This is an example of the syntax for calling the method. It includes every possible argument and initializes every possible value. The data provided is not necessarily semantically accurate (for example the value "string" may be provided for something that is intended to be an instance ID, or in some cases two arguments may be mutually exclusive). The syntax shows the ABAP syntax for creating the various data structures.

DATA(lo_result) = lo_client->createwhatifforecast(
  io_timeseriesreplcmtsdatasrc = new /aws1/cl_fcstimeseriesreplcs00(
    io_s3config = new /aws1/cl_fcss3config(
      iv_kmskeyarn = |string|
      iv_path = |string|
      iv_rolearn = |string|
    )
    io_schema = new /aws1/cl_fcsschema(
      it_attributes = VALUE /aws1/cl_fcsschemaattribute=>tt_schemaattributes(
        (
          new /aws1/cl_fcsschemaattribute(
            iv_attributename = |string|
            iv_attributetype = |string|
          )
        )
      )
    )
    iv_format = |string|
    iv_timestampformat = |string|
  )
  it_tags = VALUE /aws1/cl_fcstag=>tt_tags(
    (
      new /aws1/cl_fcstag(
        iv_key = |string|
        iv_value = |string|
      )
    )
  )
  it_timeseriestransformations = VALUE /aws1/cl_fcstimeseriestransf00=>tt_timeseriestransformations(
    (
      new /aws1/cl_fcstimeseriestransf00(
        io_action = new /aws1/cl_fcsaction(
          iv_attributename = |string|
          iv_operation = |string|
          iv_value = '0.1'
        )
        it_timeseriesconditions = VALUE /aws1/cl_fcstimeseriescond=>tt_timeseriesconditions(
          (
            new /aws1/cl_fcstimeseriescond(
              iv_attributename = |string|
              iv_attributevalue = |string|
              iv_condition = |string|
            )
          )
        )
      )
    )
  )
  iv_whatifanalysisarn = |string|
  iv_whatifforecastname = |string|
).

This is an example of reading all possible response values

lo_result = lo_result.
IF lo_result IS NOT INITIAL.
  lv_longarn = lo_result->get_whatifforecastarn( ).
ENDIF.

/AWS1/IF_FCS=>CREATEWHATIFFORECAST()¶