Summary
Running Spark on Kubernetes builds a single workflow for Spark-based data preparation and ML tasks, using Kubernetes for isolated workloads, resource limits and on-demand scaling. Yaron Haviv explains how this unifies analytics and data science on one cloud-native architecture without a separately managed big data cluster.
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