Big Data Analysis with Scala and Spark

École Polytechnique Fédérale de Lausanne

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 how the data parallel paradigm can be extended to the distributed case, using Spark throughout. We'll cover Spark's programming model in detail, being careful to understand how and when it differs from familiar programming models, like shared-memory parallel collections or sequential Scala collections. Through hands-on examples in Spark and Scala, we'll learn when important issues related to distribution like latency and network communication should be considered and how they can be addressed effectively for improved performance. Learning Outcomes. By the end of this course you will be able to: - read data from persistent storage and load it into Apache Spark, - manipulate data with Spark and Scala, - express algorithms for data analysis in a functional style, - recognize how to avoid shuffles and recomputation in Spark, Recommended background: You should have at least one year programming experience. Proficiency with Java or C# is ideal, but experience with other languages such as C/C++, Python, Javascript or Ruby is also sufficient. You should have some familiarity using the command line. This course is intended to be taken after Parallel Programming:

Certificate Available ✔

Get Started / More Info
Big Data Analysis with Scala and Spark
More Algorithms Courses

Artificial Intelligence: an Overview

Politecnico di Milano

This Specialization is intended for beginners seeking to enter the artificial intelligence world. Through five courses, you will cover artificial intelligence technical...

Mind and Machine

University of Colorado Boulder

This specialization examines the ways in which our current understanding of human thinking is both illuminated and challenged by the evolving techniques and ideas...

Everyday Excel, Part 3 (Projects)

University of Colorado Boulder

"Everyday Excel, Part 3 (Projects)" is a continuation of "Everyday Excel, Parts 1 and 2". It is a capstone, projects-based course in which you...

Robot Localization with Python and Particle Filters

Coursera Project Network

In this one hour long project-based course, you will tackle a real-world problem in robotics. We will be simulating a robot that can move around in an unknown environment,...