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Big Data Analysis with Scala and Spark, Федеральная политехническая школа Лозанны

4.7
Оценки: 1,867
Рецензии: 382

Об этом курсе

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....

Лучшие рецензии

автор: 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!

автор: 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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Рецензии: 367

автор: BOUDRAHEM

Apr 16, 2019

Everything was excellent. This was one of the best courses I have attended so far

автор: Rodion Gorkovenko

Apr 15, 2019

Course is good to have some practice in spark and scala. However it seems to be long forsaken by staff and some issues with assignments require doing archaeology in the forums. Also it is quite unpleasant to see that while specialization emphasizes functional programming, some auxiliary code in assignments is written in the worst manner of imperative programming... Why use scala then?

автор: Light0617

Apr 14, 2019

wonderful!!!

автор: Ngoc-Bien NGUYEN

Apr 04, 2019

bon cours

автор: Kevin Lawrence

Apr 02, 2019

I loved this course - it was a great introduction to Spark. At the end, I wasn't (and am still not) clear on type-safe operations on Datasets, and now to write Tests to verify this.

These will be one of the targets of my upcoming research and study.

автор: Subodh Chiwate

Mar 30, 2019

Thanks Prof. Miller !

автор: Šejla Čebirić

Mar 20, 2019

Brilliant lecturer and slides! The only problem is assignments not being clear on the expected outputs. Sometimes it takes more time to figure out what exactly is asked than to find the solution. A few more test cases or detailed examples would help.

автор: Varlamova Elena

Mar 10, 2019

It was amazing!!! Very useful course!

автор: Симкин Иван Михайлович

Mar 10, 2019

Perfectly. Very competent teacher and good tasks. Requires knowledge of scala.

автор: Edgar Diaz

Mar 10, 2019

Favorite so far out of the Scala Specialization Course. It was executed really well, and taught really well, too. Kinda wish they would add more exercises to help us get more experience with some of the concepts, but that's something you can always just do by yourself either way.