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Apache Spark™ is a unified analytics engine for large-scale data processing. It provides high-level APIs in Scala, Java, Python, and R, and an optimized engine that supports general computation graphs for data analysis. It also supports a rich set of higher-level tools including Spark SQL for SQL and DataFrames, MLlib for machine learning, GraphX for graph processing, and Structured Streaming for stream processing. The SageMaker Spark Container is a Docker image used to run batch data processing workloads on Amazon SageMaker using the Apache Spark framework. The container images in this repository are used to build the pre-built container images that are used when running Spark jobs on Amazon SageMaker using the SageMaker Python SDK. The pre-built images are available in the Amazon Elastic Container Registry (Amazon ECR), and this repository serves as a reference for those wishing to build their own customized Spark containers for use in Amazon SageMaker.
Features
- This project is licensed under the Apache-2.0 License
- The simplest way to get started with the SageMaker Spark Container is to use the pre-built images via the SageMaker Python SDK
- To get started building and testing the SageMaker Spark container, you will have to setup a local development environment
- Many available SageMaker Spark Images
- Build the pre-built container images that are used when running Spark jobs on Amazon SageMaker
- It provides high-level APIs in Scala, Java, Python, and R
Project Samples
