/AWS1/CL_ML=>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¶
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 aDataSource
. Amazon ML uses the statistics internally duringMLModel
training. This parameter must be set totrue
if theDataSource
needs to be used for
MLModel
training.