CREATEDATASOURCEFROMREDSHIFT()`¶

About CreateDataSourceFromRedshift¶

Creates a DataSource from a database hosted on an Amazon Redshift cluster. A DataSource references data that can be used to perform either CreateMLModel, CreateEvaluation, or CreateBatchPrediction operations.

CreateDataSourceFromRedshift is an asynchronous operation. In response to CreateDataSourceFromRedshift, Amazon Machine Learning (Amazon ML) immediately returns and sets the DataSource status to PENDING. After the DataSource is created and ready for use, Amazon ML sets the Status parameter to COMPLETED. DataSource in COMPLETED or PENDING states 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 observations should be contained in the database hosted on an Amazon Redshift cluster and should be specified by a SelectSqlQuery query. Amazon ML executes an Unload command in Amazon Redshift to transfer the result set of the SelectSqlQuery query to S3StagingLocation.

After the DataSource has been created, it's ready for use in evaluations and batch predictions. If you plan to use the DataSource to train an MLModel, the DataSource also requires 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.

You can't change an existing datasource, but you can copy and modify the settings from an existing Amazon Redshift datasource to create a new datasource. To do so, call GetDataSource for an existing datasource and copy the values to a CreateDataSource call. Change the settings that you want to change and make sure that all required fields have the appropriate values.

Method Signature¶

METHODS /AWS1/IF_ML~CREATEDATASOURCEFROMREDSHIFT
  IMPORTING
    !IV_DATASOURCEID TYPE /AWS1/ML_ENTITYID OPTIONAL
    !IV_DATASOURCENAME TYPE /AWS1/ML_ENTITYNAME OPTIONAL
    !IO_DATASPEC TYPE REF TO /AWS1/CL_ML_REDSHIFTDATASPEC OPTIONAL
    !IV_ROLEARN TYPE /AWS1/ML_ROLEARN OPTIONAL
    !IV_COMPUTESTATISTICS TYPE /AWS1/ML_COMPUTESTATISTICS OPTIONAL
  RETURNING
    VALUE(OO_OUTPUT) TYPE REF TO /aws1/cl_ml_credatasrcfrmred01
  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 ID that uniquely identifies the DataSource.

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

The data specification of an Amazon Redshift DataSource:

DatabaseInformation -

DatabaseName - The name of the Amazon Redshift database.

ClusterIdentifier - The unique ID for the Amazon Redshift cluster.

DatabaseCredentials - The AWS Identity and Access Management (IAM) credentials that are used to connect to the Amazon Redshift database.

SelectSqlQuery - The query that is used to retrieve the observation data for the Datasource.

S3StagingLocation - The Amazon Simple Storage Service (Amazon S3) location for staging Amazon Redshift data. The data retrieved from Amazon Redshift using the SelectSqlQuery query is stored in this location.

DataSchemaUri - 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}}"

`iv_rolearn` `TYPE /AWS1/ML_ROLEARN` `/AWS1/ML_ROLEARN`¶

A fully specified role Amazon Resource Name (ARN). Amazon ML assumes the role on behalf of the user to create the following:

A security group to allow Amazon ML to execute the SelectSqlQuery query on an Amazon Redshift cluster

An Amazon S3 bucket policy to grant Amazon ML read/write permissions on the S3StagingLocation

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_credatasrcfrmred01` `/AWS1/CL_ML_CREDATASRCFRMRED01`¶

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->createdatasourcefromredshift(
  io_dataspec = new /aws1/cl_ml_redshiftdataspec(
    io_databasecredentials = new /aws1/cl_ml_reddatabasecreds(
      iv_password = |string|
      iv_username = |string|
    )
    io_databaseinformation = new /aws1/cl_ml_redshiftdatabase(
      iv_clusteridentifier = |string|
      iv_databasename = |string|
    )
    iv_datarearrangement = |string|
    iv_dataschema = |string|
    iv_dataschemauri = |string|
    iv_s3staginglocation = |string|
    iv_selectsqlquery = |string|
  )
  iv_computestatistics = ABAP_TRUE
  iv_datasourceid = |string|
  iv_datasourcename = |string|
  iv_rolearn = |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=>CREATEDATASOURCEFROMREDSHIFT()¶