Introduction to Spark with Python

After lots of ground-breaking work led by the UC Berkeley AMP Lab, Spark was developed to utilize distributed, in-memory data structures to improve data processing speeds over Hadoop for most workloads. In this post, we’re going to cover the architecture of Spark and basic transformations and actions using a real dataset. If you want to write and run your own Spark code, check out the interactive version of this post on Dataquest.

via Introduction to Spark with Python

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