Big Data Analysis with Scala and Spark

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Description
Manipulating big data distributed over a cluster using functional concepts is rampant in industry, and is arguably one of the first widespread industrial uses of functional ideas. This is evidenced by the popularity of MapReduce and Hadoop, and most recently Apache Spark, a fast, in-memory distributed collections framework written in Scala. In this course, we'll see ho...
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Course Content

Getting Started + Spark Basics

Reduction Operations & Distributed Key-Value Pairs

Partitioning and Shuffling

Structured data: SQL, Dataframes, and Datasets

About Educator
Prof. Heather Miller
Assistant Professor
Heather Miller is an assistant professor in Carnegie Mellon University's School of Computer Science. Previously, she was a research scientist at EPFL, and the co-founder and executive director of the Scala Center.
Course Info
Course Duration

28h

Course Language

English

Course Level

Beginner

Certification

Yes

Free
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