Distributed Data Processing using Apache Spark and AWS SageMaker
Apache Spark is a unified analytics engine for large-scale data processing. The Spark framework is often used within the context of machine learning workflows to run data transformation or feature engineering workloads at scale.
Amazon SageMaker provides a set of prebuilt Docker images that include Apache Spark and other dependencies needed to run distributed data processing jobs on Amazon SageMaker.
This example notebook demonstrates how to use the prebuilt Spark images on SageMaker Processing using the SageMaker Python SDK.
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