CREATEDATASOURCEFROMS3()`¶

About CreateDataSourceFromS3¶

Creates a DataSource object. A DataSource references data that can be used to perform CreateMLModel, CreateEvaluation, or CreateBatchPrediction operations.

CreateDataSourceFromS3 is an asynchronous operation. In response to CreateDataSourceFromS3, Amazon Machine Learning (Amazon ML) immediately returns and sets the DataSource status to PENDING. After the DataSource has been created and is ready for use, Amazon ML sets the Status parameter to COMPLETED. DataSource in the COMPLETED or PENDING state can be used to perform only CreateMLModel, CreateEvaluation or CreateBatchPrediction operations.

If Amazon ML can't accept the input source, it sets the Status parameter to FAILED and includes an error message in the Message attribute of the GetDataSource operation response.

The observation data used in a DataSource should be ready to use; that is, it should have a consistent structure, and missing data values should be kept to a minimum. The observation data must reside in one or more .csv files in an Amazon Simple Storage Service (Amazon S3) location, along with a schema that describes the data items by name and type. The same schema must be used for all of the data files referenced by the DataSource.

After the DataSource has been created, it's ready to use in evaluations and batch predictions. If you plan to use the DataSource to train an MLModel, the DataSource also needs a recipe. A recipe describes how each input variable will be used in training an MLModel. Will the variable be included or excluded from training? Will the variable be manipulated; for example, will it be combined with another variable or will it be split apart into word combinations? The recipe provides answers to these questions.

Method Signature¶

METHODS /AWS1/IF_ML~CREATEDATASOURCEFROMS3
  IMPORTING
    !IV_DATASOURCEID TYPE /AWS1/ML_ENTITYID OPTIONAL
    !IV_DATASOURCENAME TYPE /AWS1/ML_ENTITYNAME OPTIONAL
    !IO_DATASPEC TYPE REF TO /AWS1/CL_ML_S3DATASPEC OPTIONAL
    !IV_COMPUTESTATISTICS TYPE /AWS1/ML_COMPUTESTATISTICS OPTIONAL
  RETURNING
    VALUE(OO_OUTPUT) TYPE REF TO /aws1/cl_ml_credatasrcfrms3out
  RAISING
    /AWS1/CX_ML_IDEMPOTENTPRMMIS00
    /AWS1/CX_ML_INTERNALSERVEREX
    /AWS1/CX_ML_INVALIDINPUTEX
    /AWS1/CX_ML_CLIENTEXC
    /AWS1/CX_ML_SERVEREXC
    /AWS1/CX_RT_TECHNICAL_GENERIC
    /AWS1/CX_RT_SERVICE_GENERIC.

IMPORTING¶

Required arguments:¶

`iv_datasourceid` `TYPE /AWS1/ML_ENTITYID` `/AWS1/ML_ENTITYID`¶

A user-supplied identifier that uniquely identifies the DataSource.

`io_dataspec` `TYPE REF TO /AWS1/CL_ML_S3DATASPEC` `/AWS1/CL_ML_S3DATASPEC`¶

The data specification of a DataSource:

DataLocationS3 - The Amazon S3 location of the observation data.

DataSchemaLocationS3 - The Amazon S3 location of the DataSchema.

DataSchema - A JSON string representing the schema. This is not required if DataSchemaUri is specified.

DataRearrangement - A JSON string that represents the splitting and rearrangement requirements for the Datasource.

Sample - "{\"splitting\":{\"percentBegin\":10,\"percentEnd\":60}}"

Optional arguments:¶

`iv_datasourcename` `TYPE /AWS1/ML_ENTITYNAME` `/AWS1/ML_ENTITYNAME`¶

A user-supplied name or description of the DataSource.

`iv_computestatistics` `TYPE /AWS1/ML_COMPUTESTATISTICS` `/AWS1/ML_COMPUTESTATISTICS`¶

The compute statistics for a DataSource. The statistics are generated from the observation data referenced by a DataSource. Amazon ML uses the statistics internally during MLModel training. This parameter must be set to true if the DataSource needs to be used for MLModel training.

RETURNING¶

`oo_output` `TYPE REF TO /aws1/cl_ml_credatasrcfrms3out` `/AWS1/CL_ML_CREDATASRCFRMS3OUT`¶

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->createdatasourcefroms3(
  io_dataspec = new /aws1/cl_ml_s3dataspec(
    iv_datalocations3 = |string|
    iv_datarearrangement = |string|
    iv_dataschema = |string|
    iv_dataschemalocations3 = |string|
  )
  iv_computestatistics = ABAP_TRUE
  iv_datasourceid = |string|
  iv_datasourcename = |string|
).

This is an example of reading all possible response values

lo_result = lo_result.
IF lo_result IS NOT INITIAL.
  lv_entityid = lo_result->get_datasourceid( ).
ENDIF.

/AWS1/IF_ML=>CREATEDATASOURCEFROMS3()¶