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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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426 - 450 de 506 revisiones para Big Data Analysis with Scala and Spark

por Francis T

16 de abr. de 2017

I really liked the content regarding Dataframes and Datasets.

por Emmanouil G

1 de abr. de 2017

Assignment Instructions need improvement in terms of clarity.

por Gongqi L

9 de abr. de 2017

Very good course, but it needs more details and examples.

por kaushik

9 de abr. de 2017

Good course ! But does need more programming assignments

por Mohammad T

24 de ago. de 2019

such a beautiful course design for a bigData devlopers

por Kota M

5 de abr. de 2018

It is a good course, but the lecturer speaks too fast.

por Anuj A

22 de oct. de 2020

Needs more detailing for datasets and dataframe apis

por Wolfgang G

30 de ago. de 2017

Very well-lead introductory, a bit lengthy at times.

por Manuel W

18 de abr. de 2017

Would be better to have more and shorter exercises.

por Ruslan A

23 de ago. de 2017

lectures don't correlate to practical assigment :(

por David G

25 de ago. de 2017

Great course, but can be great idea have the ppts

por Yuan R

20 de ene. de 2018

Great course that is very practical for the job.

por Guillermo G H

30 de jun. de 2017

Great approach to learn about Spark in practice

por Michaël M P

5 de feb. de 2019

Talk about how to set Scala version in Eclipse

por 林鼎棋

29 de may. de 2017

Great! But I want to know more about dataset!

por VeeraVenkataSatyanarayana M

4 de jun. de 2017

Basics are covered in an effective way.

por Pavel O

12 de ago. de 2017

Good final course for Scala learners.

por Lucas F

15 de may. de 2017

Great lectures and great content!

por Роман В

24 de jun. de 2018

I would like to learn some more.

por Park H

18 de abr. de 2017

Learned Spark APIs, internals.

por Alberto P d P

12 de may. de 2017

Very good and concise course.

por Dibash B

1 de jul. de 2022

nice spark indepth knowledge

por Javier L B

7 de dic. de 2021

Good course.

por Stéphane L

13 de oct. de 2017

Very useful