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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

2,567 évaluations

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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276 - 300 sur 507 Avis pour Big Data Analysis with Scala and Spark

par Jose M N

28 mai 2018

Great course. Thanks for everything.

par Srinivasa R M

13 sept. 2017

Very nice explanation with examples.

par Martin A

3 mai 2017

Great course, good intro into Spark.

par Manuel M C

23 mars 2017

Great course, keep up the good work.

par Neeraj V D

27 févr. 2018

limited content with dewp knowledge

par Abhay D

4 nov. 2018

Wonderful course. Helped me a lot.

par David M

18 sept. 2017

Concepts are very well explained..

par Liu D

26 juil. 2017

Great speeches with great exercise

par Fernando R

28 oct. 2017

it was a super interesting course

par Alejandro R C

13 août 2017

Everything was easy to understand

par Jinfu X

12 mars 2017

Thanks! It's an excellent course.

par Fedor C

31 août 2017

Very interesting course! Thanks!

par Vasyl Y

26 juin 2017

Cool course! Thanks for your job

par Kyle L

10 juin 2017

very good course, really enjoyed

par Alex S

5 mai 2018

Super course, well done Heather

par Jong H S

18 août 2017

A wonderful and timely course.

par Zhu X

5 juil. 2017

Great course, I learned a lot.

par Salvo

23 avr. 2017

This course is very well done.

par Jay

21 sept. 2017

cool teacher and cool course!

par Atsuya K

29 oct. 2017

A good quick intro to Spark.

par Jakub T m G

27 juin 2017

good introduction into Spark

par Benzakoun S

8 mai 2017

excellent quality of content

par Akash D

26 juil. 2021

Wonderfully designed course

par bechir n

21 nov. 2020

It really helped me at Work

par savitri v v

27 juil. 2018

Very good learning portal