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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

4.7
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2,507 évaluations
516 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: https://www.coursera.org/learn/parprog1....

Meilleurs avis

BP
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.

CC
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!

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326 - 350 sur 499 Avis pour Big Data Analysis with Scala and Spark

par Moncef Z M

6 sept. 2020

Super cours !

par Rajesh K S

9 oct. 2018

Excellent Cou

par jose c a

5 mai 2018

Muy Bueno!!!!

par JULIAN A G V

1 févr. 2018

Great course!

par Jose E T

2 juin 2017

Great Course!

par Emiliyan T

9 avr. 2017

Magnificent !

par Light0617

14 avr. 2019

wonderful!!!

par Saiteja t

1 août 2018

Nice session

par Hengyu

6 avr. 2018

very helpful

par Rafael M

18 oct. 2017

Great Course

par Mihir S

27 sept. 2017

Good Course.

par Angel V

21 août 2017

very usefull

par Aleksey I

2 juin 2017

Good course.

par roman a

5 avr. 2020

good cource

par Kirill K

10 oct. 2017

A good one.

par William H

6 sept. 2017

Outstanding

par Ajedrez y T

13 juin 2020

Excelente

par Sanjeev R

26 août 2019

Excellent

par Ngoc-Bien N

4 avr. 2019

bon cours

par D S

17 janv. 2018

Excellent

par Mohamed K

30 oct. 2017

Perfect !

par Pengcheng L

5 juin 2017

Thanks :)

par Huajian M

4 avr. 2017

So great!

par 李帅

1 mai 2019

Perfect!

par IURII B

7 août 2017

Thanks !