There are many reasons why Python has emerged as the number one language for data science. It’s easy to get started and relatively forgiving for beginners, yet it’s also powerful and extensible enough for experts to take on complex tasks. But there’s one aspect of Python that has bedeviled developers in the big data age: Getting Python to scale past a single node. Solving that dilemma is the number one goal of Project Ray.
The name “Ray” will ring a bell if you’ve been following the goings-on at RISELab, the advanced computing laboratory formed at UC Berkeley. As the follow-on to AMPLab, which gave us Spark, Tachyon (now Alluxio), and Mesos, there are certain expectations for impactful technologies to flow from RISELab. So far, Ray is the top candidate to achieve escape velocity and thrive in the open source world.
Author: Alex Woodie
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