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學生對 洛桑联邦理工学院 提供的 Big Data Analysis with Scala and Spark 的評價和反饋

4.7
2,083 個評分
418 個審閱

課程概述

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....

熱門審閱

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!

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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226 - Big Data Analysis with Scala and Spark 的 250 個評論(共 402 個)

創建者 Zdeněk H

Jul 22, 2017

Thanks to this course I think that I have finally understood partitioning and everything about Datasets.

創建者 Seongsan K

Mar 09, 2018

It was really useful material. It would be really nice if there are more assignments to polish the materials we learn, but I am really satisfied with the course.

創建者 Manoj K

Aug 27, 2017

This course make me to fall in love with SPARK framework :)

創建者 Xiongchu W

Aug 05, 2017

This course is indeed introductive to learn all the necessary stuffs about Spark. It is pretty good to tell much about shuffling. Because we should not only be familiar with how to operate on Spark, but we should really have a good understanding of what's going on underneath the hood. Thanks!

創建者 Benzakoun S

May 08, 2017

excellent quality of content

創建者 Vasyl Y

Jun 26, 2017

Cool course! Thanks for your job

創建者 Jinfu X

Mar 13, 2017

Thanks! It's an excellent course.

創建者 本达 续

Aug 04, 2017

A very natural application of functional programming to real world distributed computation problems.

創建者 Parker G

Apr 10, 2017

Great course! The powerpoint/slides/pdfs are a GREAT resource

創建者 CAI X

Jul 16, 2017

Well explained and demoed . Good introduction to spark, the most useful big data framework!

創建者 Walter E Z

Apr 02, 2017

Great introduction to Spark and it's data structures. The course is easy to follow, and lecturer is entertaining and really engaged.

Thanks, I really had fun !

創建者 jose r

Nov 24, 2017

Great Course, thanks

創建者 Prashant P

May 12, 2017

Awesome course !

創建者 Imran K

Apr 08, 2017

As always, Coursera delivered another top quality courses on Spark with Scala. I have learned a lot of details, understood the underlying working principles of Spark in the last few days. Thanks to Dr. Miller for such a great course. I hope in the future versions of this course the overall presentations will be more smooth and typo-free.

創建者 Shae S

Mar 23, 2017

I learned so much from this course! It was amazing how Dr. Miller used concepts that were meticulously built up in the earlier courses, such as evaluation strategy, functional collections, reactive programming, and associativity, to describe the core of Spark in only four units. As someone coming from more of a statistics background, I started this specialization only to learn Spark, so I wasn't always sure how relevant learning the more theoretical underpinnings of Scala would be. It turns out that it was pretty essential, while also just making me a better programmer. Looking forward to the capstone!

創建者 Jorge B C

May 02, 2017

Very interesting course!!

創建者 Jean-Francois T

Mar 27, 2017

Good material and induction to Spark, good complement of parallel computing in Scala

創建者 Mostafa J

Jun 13, 2017

Very challenging but I learned a lot.

Thanks a lot, Dr. Heather Miller!

創建者 Nebiyou T

Dec 26, 2017

Very good instructor!

創建者 Konstantin

May 29, 2017

Nice course, thanks!

創建者 Antonio A

Oct 20, 2017

Clear explanations, with emphasis done on the important/practical stuff. From zero to a general understanding on Spark and the available tools in 4 weeks.

創建者 Kovalenko S

Jul 17, 2017

Курс очень понравился, спасибо большое за ваш труд!

創建者 Walter D

Jan 01, 2018

Great course to get going with Apache Spark. Would recommend to someone who has java or scala experience already and wants to learn about distributed processing.

創建者 Cliff R

Jul 22, 2018

Gives a good grounding in the fundamentals of Spark

創建者 manuel B L

Jul 22, 2018

Muy bueno, Excelente. Todos los conocimientos obtenidos me serán de mucha ayuda en mi camino hacia el mundo de Big Data