'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 `COMPLETED` or `PENDING` status
can only be used 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.
:type data_source_id: string
:param data_source_id: A user-supplied ID that uniquely identifies the
`DataSource`. Typically, an Amazon Resource Number (ARN) becomes
the ID for a `DataSource`.
:type data_source_name: string
:param data_source_name: A user-supplied name or description of the
`DataSource`.
:type rds_data: dict
:param rds_data:
The data specification of an Amazon RDS `DataSource`:
+ DatabaseInformation -
+ `DatabaseName ` - Name of the Amazon RDS database.
+ ` InstanceIdentifier ` - 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 - Role (DataPipelineDefaultResourceRole) assumed by an
Amazon Elastic Compute Cloud (EC2) instance to carry out the copy
task from Amazon RDS to Amazon S3. For more information, see `Role
templates`_ for data pipelines.
+ ServiceRole - Role (DataPipelineDefaultRole) assumed by the AWS Data
Pipeline service to monitor the progress of the copy task from
Amazon RDS to Amazon Simple Storage Service (S3). For more
information, see `Role templates`_ for data pipelines.
+ SecurityInfo - Security information to use to access an Amazon RDS
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 Amazon RDS instance.
+ SelectSqlQuery - Query that is used to retrieve the observation data
for the `Datasource`.
+ S3StagingLocation - Amazon S3 location for staging RDS data. The data
retrieved from Amazon RDS using `SelectSqlQuery` is stored in this
location.
+ DataSchemaUri - 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 representing the splitting
requirement of a `Datasource`. Sample - ` "{"randomSeed":"some-
random-seed",
"splitting":{"percentBegin":10,"percentEnd":60}}"`
:type role_arn: string
:param role_arn: The role that Amazon ML assumes on behalf of the user
to create and activate a data pipeline in the users account and
copy data (using the `SelectSqlQuery`) query from Amazon RDS to
Amazon S3.
:type compute_statistics: boolean
:param compute_statistics: 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
an `MLModel` training. This parameter must be set to `True` if the
``DataSource `` needs to be used for `MLModel` training.'

def create_data_source_from_rds(self, data_source_id, rds_data, role_arn, data_source_name=None, compute_statistics=None):

    params = {'DataSourceId': data_source_id, 'RDSData': rds_data, 'RoleARN': role_arn}
    if (data_source_name is not None):
        params['DataSourceName'] = data_source_name
    if (compute_statistics is not None):
        params['ComputeStatistics'] = compute_statistics
    return self.make_request(action='CreateDataSourceFromRDS', body=json.dumps(params))
