Summary
Ray, the open source distributed framework from UC Berkeley's RISELab, scales Python applications from a laptop to a cluster with low-latency task scheduling, distributed state management, near-linear scaling and an intuitive API. The talk shows how Ray works with Spark to build scalable enterprise data applications and when to choose Ray over alternatives.
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