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Big Data Analysis with Scala and Spark, École Polytechnique Fédérale de Lausanne

4.7
Оценки: 1,679
Рецензии: 355

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: 340

автор: Denys Lobur

Dec 05, 2018

Very nice, but a little bit outdated course

автор: Sivakumar P

Nov 29, 2018

Course is very useful to understand Spark and Scala things.

автор: Deepak Dwivedi

Nov 23, 2018

Not specify & given instruction regarding how to submit the solution

автор: Camila González Williamson

Nov 16, 2018

Amazing course!

автор: Massimiliano D’Acunzo

Nov 14, 2018

Great course over Spark. It shows the syntax, but more than this, it shows the problems, the caveats, the optimization and the architecture from a wide point of view.

The assignment were designed to focus right to the point: they managed all the configuration and initialization code of the project, leaving the student to fill only the most important part, with the resulto of having, at the end of the course, working projects that could be used as "cheat sheet" to remember all the material of the course.

Massimiliano.

автор: Devaraja K R

Nov 14, 2018

Good

автор: Abhay Dubey

Nov 04, 2018

Wonderful course. Helped me a lot.

автор: ANKIT SINGH

Oct 25, 2018

Very good and knowledgeable course. It basically explains about spark core, dataframe, dataset and spark sql.

автор: Srinivas Sudhindra

Oct 24, 2018

The exercises were below the standard of previous courses. Also the instructions on exercises could have been better. Lost a lot of time figuring out as a new bee in Spark.

автор: Karim Mejri

Oct 15, 2018

Amazing course, i learned a lot even if i'm working with scala and spark