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Retour à Big Data Analysis with Scala and Spark

Avis et commentaires pour d'étudiants pour Big Data Analysis with Scala and Spark par École polytechnique fédérale de Lausanne

2,539 évaluations
519 avis

À propos du 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:

Meilleurs avis


7 juin 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!


28 nov. 2019

Excellent overview of Spark, including exercises that solidify what you learn during the lectures. The development environment setup tutorials were also very helpful, as I had not yet worked with sbt.

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301 - 325 sur 504 Avis pour Big Data Analysis with Scala and Spark

par Canh S L

25 mars 2017

really good, informative

par vijay k k

7 mai 2018

Good course to learn it

par Hermann H

19 juil. 2017

Great material !!! ;-)

par vikas s

28 juil. 2017

awesome course content

par Deleted A

26 juin 2017

Great course. Thanks!

par Marija N

5 juil. 2019

Absolutely fantastic!

par Subodh C

30 mars 2019

Thanks Prof. Miller !

par Nebiyou T

26 déc. 2017

Very good instructor!

par Dinesh A G

2 avr. 2017

good course on spark.

par jose r

24 nov. 2017

Great Course, thanks

par Konstantin

29 mai 2017

Nice course, thanks!

par abhinav

10 déc. 2017

Wonderful course!!!

par Luis M M S

21 juin 2017

I loved this course

par prashant b

7 avr. 2017

very nicely taught

par Manish M D

16 sept. 2019

Excellent course.


1 mars 2018

Simply brilliant.

par Rajesh G

2 déc. 2017

Excellent course!

par Georgi Y

7 juil. 2017

Excellent course!

par Taneli L

10 avr. 2017

Excellent course.

par Tal G

8 avr. 2017

Excellent teacher

par Fang Z

5 avr. 2017

Very good course.

par Prashant P

12 mai 2017

Awesome course !

par Jędrzej B

22 mai 2020

Nice and clear.

par Camila G W

16 nov. 2018

Amazing course!

par Andrii P

9 avr. 2017

Just awesome :)