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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


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.


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!

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276 - 300 de 506 revisiones para Big Data Analysis with Scala and Spark

por Martin A

3 de may. de 2017

Great course, good intro into Spark.

por Manuel M C

23 de mar. de 2017

Great course, keep up the good work.

por Neeraj V D

27 de feb. de 2018

limited content with dewp knowledge

por Abhay D

4 de nov. de 2018

Wonderful course. Helped me a lot.

por David M

18 de sep. de 2017

Concepts are very well explained..

por Liu D

26 de jul. de 2017

Great speeches with great exercise

por Fernando R

28 de oct. de 2017

it was a super interesting course

por Alejandro R C

13 de ago. de 2017

Everything was easy to understand

por Jinfu X

12 de mar. de 2017

Thanks! It's an excellent course.

por Fedor C

31 de ago. de 2017

Very interesting course! Thanks!

por Vasyl Y

26 de jun. de 2017

Cool course! Thanks for your job

por Kyle L

10 de jun. de 2017

very good course, really enjoyed

por Alex S

5 de may. de 2018

Super course, well done Heather

por Jong H S

18 de ago. de 2017

A wonderful and timely course.

por Jon Z

5 de jul. de 2017

Great course, I learned a lot.

por Salvo

23 de abr. de 2017

This course is very well done.

por Jay

21 de sep. de 2017

cool teacher and cool course!

por Atsuya K

29 de oct. de 2017

A good quick intro to Spark.

por Jakub T m G

27 de jun. de 2017

good introduction into Spark

por Benzakoun S

8 de may. de 2017

excellent quality of content

por Akash D

26 de jul. de 2021

Wonderfully designed course

por bechir n

21 de nov. de 2020

It really helped me at Work

por savitri v v

27 de jul. de 2018

Very good learning portal

por Jorge B C

1 de may. de 2017

Very interesting course!!

por Peter S

2 de abr. de 2017

Another fun Scala course!