/AWS1/IF_CPD=>UPDATEENDPOINT()¶
About UpdateEndpoint¶
Updates information about the specified endpoint. For information about endpoints, see Managing endpoints.
Method Signature¶
METHODS /AWS1/IF_CPD~UPDATEENDPOINT
IMPORTING
!IV_ENDPOINTARN TYPE /AWS1/CPDCOMPREHENDENDPOINTARN OPTIONAL
!IV_DESIREDMODELARN TYPE /AWS1/CPDCOMPREHENDMODELARN OPTIONAL
!IV_DESIREDINFERENCEUNITS TYPE /AWS1/CPDINFERENCEUNITSINTEGER OPTIONAL
!IV_DESIREDDATAACCESSROLEARN TYPE /AWS1/CPDIAMROLEARN OPTIONAL
!IV_FLYWHEELARN TYPE /AWS1/CPDCOMPREHENDFLYWHEELARN OPTIONAL
RETURNING
VALUE(OO_OUTPUT) TYPE REF TO /aws1/cl_cpdupdateendptrsp
RAISING
/AWS1/CX_CPDINTERNALSERVEREX
/AWS1/CX_CPDINVALIDREQUESTEX
/AWS1/CX_CPDRESOURCEINUSEEX
/AWS1/CX_CPDRESRCLIMITEXCDEX
/AWS1/CX_CPDRESOURCENOTFOUNDEX
/AWS1/CX_CPDRESOURCEUNAVAILEX
/AWS1/CX_CPDTOOMANYREQUESTSEX
/AWS1/CX_CPDCLIENTEXC
/AWS1/CX_CPDSERVEREXC
/AWS1/CX_RT_TECHNICAL_GENERIC
/AWS1/CX_RT_SERVICE_GENERIC.
IMPORTING¶
Required arguments:¶
iv_endpointarn TYPE /AWS1/CPDCOMPREHENDENDPOINTARN /AWS1/CPDCOMPREHENDENDPOINTARN¶
The Amazon Resource Number (ARN) of the endpoint being updated.
Optional arguments:¶
iv_desiredmodelarn TYPE /AWS1/CPDCOMPREHENDMODELARN /AWS1/CPDCOMPREHENDMODELARN¶
The ARN of the new model to use when updating an existing endpoint.
iv_desiredinferenceunits TYPE /AWS1/CPDINFERENCEUNITSINTEGER /AWS1/CPDINFERENCEUNITSINTEGER¶
The desired number of inference units to be used by the model using this endpoint.
Each inference unit represents of a throughput of 100 characters per second.
iv_desireddataaccessrolearn TYPE /AWS1/CPDIAMROLEARN /AWS1/CPDIAMROLEARN¶
Data access role ARN to use in case the new model is encrypted with a customer CMK.
iv_flywheelarn TYPE /AWS1/CPDCOMPREHENDFLYWHEELARN /AWS1/CPDCOMPREHENDFLYWHEELARN¶
The Amazon Resource Number (ARN) of the flywheel
RETURNING¶
oo_output TYPE REF TO /aws1/cl_cpdupdateendptrsp /AWS1/CL_CPDUPDATEENDPTRSP¶
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->updateendpoint(
iv_desireddataaccessrolearn = |string|
iv_desiredinferenceunits = 123
iv_desiredmodelarn = |string|
iv_endpointarn = |string|
iv_flywheelarn = |string|
).
This is an example of reading all possible response values
lo_result = lo_result.
IF lo_result IS NOT INITIAL.
lv_comprehendmodelarn = lo_result->get_desiredmodelarn( ).
ENDIF.