Amazon Machine Learning
API Reference (API Version 2014-12-12)


Creates a DataSource object from an Amazon Relational Database Service (Amazon RDS). A DataSource references data that can be used to perform CreateMLModel, CreateEvaluation, or CreateBatchPrediction operations.

CreateDataSourceFromRDS is an asynchronous operation. In response to CreateDataSourceFromRDS, 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 the COMPLETED or PENDING state can be used only to perform >CreateMLModel>, CreateEvaluation, or CreateBatchPrediction operations.

If Amazon ML cannot 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.

Request Syntax

{ "ComputeStatistics": boolean, "DataSourceId": "string", "DataSourceName": "string", "RDSData": { "DatabaseCredentials": { "Password": "string", "Username": "string" }, "DatabaseInformation": { "DatabaseName": "string", "InstanceIdentifier": "string" }, "DataRearrangement": "string", "DataSchema": "string", "DataSchemaUri": "string", "ResourceRole": "string", "S3StagingLocation": "string", "SecurityGroupIds": [ "string" ], "SelectSqlQuery": "string", "ServiceRole": "string", "SubnetId": "string" }, "RoleARN": "string" }

Request Parameters

For information about the parameters that are common to all actions, see Common Parameters.

The request accepts the following data in JSON format.


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.

Type: Boolean

Required: No


A user-supplied ID that uniquely identifies the DataSource. Typically, an Amazon Resource Number (ARN) becomes the ID for a DataSource.

Type: String

Length Constraints: Minimum length of 1. Maximum length of 64.

Pattern: [a-zA-Z0-9_.-]+

Required: Yes


A user-supplied name or description of the DataSource.

Type: String

Length Constraints: Maximum length of 1024.

Pattern: .*\S.*|^$

Required: No


The data specification of an Amazon RDS DataSource:

  • DatabaseInformation -

    • DatabaseName - The name of the Amazon RDS database.

    • InstanceIdentifier - A unique identifier for the Amazon RDS database instance.

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

  • ResourceRole - A role (DataPipelineDefaultResourceRole) assumed by an EC2 instance to carry out the copy task from Amazon RDS to Amazon Simple Storage Service (Amazon S3). For more information, see Role templates for data pipelines.

  • ServiceRole - A role (DataPipelineDefaultRole) assumed by the AWS Data Pipeline service to monitor the progress of the copy task from Amazon RDS to Amazon S3. For more information, see Role templates for data pipelines.

  • SecurityInfo - The security information to use to access an RDS DB instance. You need to set up appropriate ingress rules for the security entity IDs provided to allow access to the Amazon RDS instance. Specify a [SubnetId, SecurityGroupIds] pair for a VPC-based RDS DB instance.

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

  • S3StagingLocation - The Amazon S3 location for staging Amazon RDS data. The data retrieved from Amazon RDS using SelectSqlQuery 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}}"

Type: RDSDataSpec object

Required: Yes


The role that Amazon ML assumes on behalf of the user to create and activate a data pipeline in the user's account and copy data using the SelectSqlQuery query from Amazon RDS to Amazon S3.

Type: String

Length Constraints: Minimum length of 1. Maximum length of 110.

Required: Yes

Response Syntax

{ "DataSourceId": "string" }

Response Elements

If the action is successful, the service sends back an HTTP 200 response.

The following data is returned in JSON format by the service.


A user-supplied ID that uniquely identifies the datasource. This value should be identical to the value of the DataSourceID in the request.

Type: String

Length Constraints: Minimum length of 1. Maximum length of 64.

Pattern: [a-zA-Z0-9_.-]+


For information about the errors that are common to all actions, see Common Errors.


A second request to use or change an object was not allowed. This can result from retrying a request using a parameter that was not present in the original request.

HTTP Status Code: 400


An error on the server occurred when trying to process a request.

HTTP Status Code: 500


An error on the client occurred. Typically, the cause is an invalid input value.

HTTP Status Code: 400


The following is a sample HTTP request and response of the CreateDataSourceFromRDS operation.

Sample Request

POST / HTTP/1.1 Host: machinelearning.<region>.<domain> x-amz-Date: <Date> Authorization: AWS4-HMAC-SHA256 Credential=<Credential>, SignedHeaders=contenttype;date;host;user-agent;x-amz-date;x-amz-target;x-amzn-requestid,Signature=<Signature> User-Agent: <UserAgentString> Content-Type: application/x-amz-json-1.1 Content-Length: <PayloadSizeBytes> Connection: Keep-Alive X-Amz-Target: AmazonML_20141212.CreateDataSourceFromRDS { "DataSourceId": "ml-rds-data-source-demo", "DataSourceName": "ml-rds-data-source-demo", "RDSData": { "DatabaseInformation": { "InstanceIdentifier": "demo", "DatabaseName": "demo" }, "SelectSqlQuery": "select feature1, feature2, feature3, ...., featureN from RDS_DEMO_TABLE;", "DatabaseCredentials": { "Username": "demo_user", "Password": "demo_password" }, "S3StagingLocation": "s3://mldemo/data/", "DataSchemaUri": "s3://mldemo/schema/mldemo.csv.schema", "ResourceRole": "DataPipelineDefaultResourceRole", "ServiceRole": "DataPipelineDefaultRole", "SubnetId": "subnet-XXXX", "SecurityGroupIds": ["sg-XXXXXX", "sg-XXXXXX"] }, "RoleARN": "arn:aws:iam::<awsAccountId>:role/<roleToAssume>" }

Sample Response

HTTP/1.1 200 OK x-amzn-RequestId: <RequestId> Content-Type: application/x-amz-json-1.1 Content-Length: <PayloadSizeBytes> Date: <Date> { "DataSourceId":"ml-rds-data-source-demo" }

See Also

For more information about using this API in one of the language-specific AWS SDKs, see the following: