put pyspark dataframe to kinesis stream

Traceback (most recent call last): File "data.py", line 88, in <module> generate(STREAM_NAME, boto3.client('kinesis',region_name='us-east-2')) File "data.py", line 83, in generate PartitionKey='partitionkey') File "/usr/lib/python2.7/site-packages/botocore/client.py", line 386, in _api_call return self._make_api_call(operation_name, kwargs) File "/usr/lib/python2.7/site-packages/botocore/client.py", line 678, in _make_api_call api_params, operation_model, context=request_context) File "/usr/lib/python2.7/site-packages/botocore/client.py", line 726, in _convert_to_request_dict api_params, operation_model) File "/usr/lib/python2.7/site-packages/botocore/validate.py", line 319, in serialize_to_request raise ParamValidationError(report=report.generate_report()) botocore.exceptions.ParamValidationError: Parameter validation failed: Invalid type for parameter Data, value: DataFrame[label: double, features: vector], type: <class 'pyspark.sql.dataframe.DataFrame'>, valid types: <type 'str'>, <type 'bytearray'>, file-like object

can someone explain how to pass a pyspark dataframe to sagemaker-pyspark model through kinesis. my data is in libsvm format. thanks in advance.