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Big Data Analysis with Scala and Spark, École polytechnique fédérale de Lausanne

4.7
1,778 notes
371 avis

À propos de ce cours

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: https://www.coursera.org/learn/parprog1....

Meilleurs avis

par CC

Jun 08, 2017

The sessions where clearly explained and focused. Some of the exercises contained slightly confusing hints and information, but I'm sure those mistakes will be ironed out in future iterations. Thanks!

par CR

Apr 10, 2017

Great introduction to spark. Fun assignments. Since it was the first ever session, there were quite a few kinks with the assignments. But the discussion forums rescued me any time I was stuck.

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356 avis

par Robert Camilo Martinez Paez

Feb 12, 2019

Excellent videos, explanation, and resources!

par Michaël Moo Penn

Feb 05, 2019

Talk about how to set Scala version in Eclipse

par Michael Reynolds

Feb 04, 2019

Great course, but week 4 leaves out some key Spark SQL concepts that you need to finish the last project, such as the use of when(). Also, the part about DataSets is gone through rather quickly and without nearly as much detail as RDD and DataFrames.

par Konrad Cala

Jan 27, 2019

A lot things to learn and experiment.

Challenging assignments.

par Luis

Jan 27, 2019

If you know the subject, may be easy. If you don't know the subject, too dense and abstract with not enough practical examples/exercises before the assignments (specially for week4). Would have been better to break the videos into smaller ones, include more practical concrete examples/exercises during the videos (as very well done by Pr. Obersky during the 1st Course of the Specialization). There could have been room to break week4 into material for 2 weeks. Still, inresting.

par Msellek Ahmed

Jan 26, 2019

Great course ! Thanks for the effort

par Greg Jones

Jan 24, 2019

Assignments are challenging but reasonable and can be completed in the estimated time. The assignments seem a little out of sync with the course, though. Material taught in week 2 was recommended to be used on the week 1 assignment.

par Murat AKIN

Jan 20, 2019

It was very challenging, but also informative. Thanks a lot.

par David F. Snyder

Jan 15, 2019

Very informative. Well-organized presentation.

par sheng wang

Jan 10, 2019

Very useful course and great materials and assignments.