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Volver a Big Data Analysis with Scala and Spark

Opiniones y comentarios de aprendices correspondientes a Big Data Analysis with Scala and Spark por parte de École Polytechnique Fédérale de Lausanne

2,548 calificaciones

Acerca del Curso

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:

Principales reseñas


7 de jun. de 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 de nov. de 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 de 506 revisiones para Big Data Analysis with Scala and Spark

por Z

27 de mar. de 2017

Very fun and informative!

por Canh S L

25 de mar. de 2017

really good, informative

por vijay k k

7 de may. de 2018

Good course to learn it

por Hermann H

19 de jul. de 2017

Great material !!! ;-)

por vikas s

28 de jul. de 2017

awesome course content

por Deleted A

26 de jun. de 2017

Great course. Thanks!

por Marija N

5 de jul. de 2019

Absolutely fantastic!

por Subodh C

30 de mar. de 2019

Thanks Prof. Miller !

por Nebiyou T

26 de dic. de 2017

Very good instructor!

por Dinesh A G

2 de abr. de 2017

good course on spark.

por jose r

24 de nov. de 2017

Great Course, thanks

por Konstantin

29 de may. de 2017

Nice course, thanks!

por abhinav

10 de dic. de 2017

Wonderful course!!!

por Luis M M S

21 de jun. de 2017

I loved this course

por prashant b

7 de abr. de 2017

very nicely taught

por Manish M D

16 de sep. de 2019

Excellent course.


1 de mar. de 2018

Simply brilliant.

por Rajesh G

2 de dic. de 2017

Excellent course!

por Georgi Y

7 de jul. de 2017

Excellent course!

por Taneli L

10 de abr. de 2017

Excellent course.

por Tal G

8 de abr. de 2017

Excellent teacher

por Fang Z

5 de abr. de 2017

Very good course.

por Prashant P

12 de may. de 2017

Awesome course !

por Jędrzej B

22 de may. de 2020

Nice and clear.

por Camila G W

16 de nov. de 2018

Amazing course!