Use SparkML Serving with Amazon SageMaker

The Amazon SageMaker Python SDK SparkML Serving model and predictor and the Amazon SageMaker open-source SparkML Serving container support deploying Apache Spark ML pipelines serialized with MLeap in SageMaker to get inferences.

For information about using the SparkML Serving container to deploy models to SageMaker, see SageMaker Spark ML Container GitHub repository. For information about the Amazon SageMaker Python SDK SparkML Serving model and predictors, see the SparkML Serving Model and Predictor API documentation.