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Build end-to-end Apache Spark pipelines with Amazon MWAA, Batch Processing Gateway, and Amazon EMR on EKS clusters
- Amazon EMR on EKS provides managed Spark integration with AWS services and existing Kubernetes patterns for data platforms.
- Batch Processing Gateway (BPG) manages Spark workloads across multiple EMR on EKS clusters efficiently.
- Integrating Amazon MWAA with BPG enhances job scheduling and orchestration for building comprehensive data processing pipelines.
- Scenario of HealthTech Analytics showcases the use case for routing Spark workloads based on security and cost requirements.
- Integration of Amazon MWAA, BPG, and EMR on EKS clusters facilitates workload distribution and isolation.
- Custom BPGOperator in Amazon MWAA streamlines job submission, routing to EMR on EKS clusters, and monitoring tasks.
- Benefits include separation of responsibilities, centralized code management, and modular design for enterprise data platforms.
- BPGOperator handles job initialization, submission, monitoring, and execution across the pipeline.
- Deployment steps involve setup of common infrastructure, configuring BPG, and integrating BPGOperator with Amazon MWAA.
- Migration to BPG-based infrastructure involves setting up Airflow connections and migrating existing DAGs seamlessly.
- Cleaning up resources post-implementation and experimenting with the architecture in AWS environments are encouraged.
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