in WorkflowJobs/importDatasetJob.py [0:0]
def start_orders_import_job(s3DataPath, datasetName, datasetGroupArn, role_arn):
# Specify the schema of your dataset here. Make sure the order of columns matches the raw data files.
schema = {
"Attributes": [
{
"AttributeName": "timestamp",
"AttributeType": "timestamp"
},
{
"AttributeName": "item_id",
"AttributeType": "string"
},
{
"AttributeName": "demand",
"AttributeType": "integer"
},
{
"AttributeName": "location",
"AttributeType": "string"
}
]
}
response = forecast.create_dataset(
Domain="INVENTORY_PLANNING",
DatasetType='TARGET_TIME_SERIES',
DatasetName=datasetName,
DataFrequency=DATASET_FREQUENCY,
Schema = schema)
TargetdatasetArn = response['DatasetArn']
workflow_params['targetTimeSeriesDataset'] = TargetdatasetArn
updateDatasetResponse = forecast.update_dataset_group(DatasetGroupArn=datasetGroupArn, DatasetArns=[TargetdatasetArn])
# Orders dataset import job
datasetImportJobName = 'INVENTORY_DSIMPORT_JOB_TARGET'
ds_import_job_response=forecast.create_dataset_import_job(DatasetImportJobName=datasetImportJobName,
DatasetArn=TargetdatasetArn,
DataSource= {
"S3Config" : {
"Path": s3DataPathOrders,
"RoleArn": role_arn
}
},
TimestampFormat=TIMESTAMP_FORMAT
)
ds_import_job_arn=ds_import_job_response['DatasetImportJobArn']
workflow_params['ordersImportJobRunId'] = ds_import_job_arn
return {
"importJobArn": ds_import_job_arn,
"datasetGroupArn": datasetGroupArn,
"ordersDatasetArn": TargetdatasetArn
}