Managed Service for Apache Spark lets you run interactive data exploration, prototype machine learning workflows, and develop Spark applications by using Jupyter notebooks. This integration provides direct access to scalable compute clusters and serverless environments for distributed data processing.
- To work with clusters, you can install and run a Jupyter notebook on a Managed Service for Apache Spark cluster.
- For domain-specific workloads, you can run a genomics analysis in a JupyterLab notebook on Managed Service for Apache Spark.
- For serverless development, you can use the Managed Service for Apache Spark JupyterLab plugin for serverless batch and interactive notebook sessions.
- You can also create a Managed Service for Apache Spark-enabled Vertex AI Workbench instance to run notebooks within a unified data science platform.