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學生對 洛桑联邦理工学院 提供的 Big Data Analysis with Scala and Spark 的評價和反饋

2,363 個評分
487 條評論


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:



Nov 29, 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.


Jun 08, 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!


401 - Big Data Analysis with Scala and Spark 的 425 個評論(共 471 個)

創建者 Pedro M

Apr 29, 2017

Very interesting course about Spark, it covers a lot of key concepts!

創建者 vahid s

Jun 27, 2020

I think programming assignments could be better but still OK.

創建者 Francis T

Apr 16, 2017

I really liked the content regarding Dataframes and Datasets.

創建者 Emmanouil G

Apr 01, 2017

Assignment Instructions need improvement in terms of clarity.

創建者 Gongqi L

Apr 10, 2017

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

創建者 kaushik

Apr 09, 2017

Good course ! But does need more programming assignments

創建者 Mohammad T

Aug 24, 2019

such a beautiful course design for a bigData devlopers

創建者 Kota M

Apr 05, 2018

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

創建者 Anuj A

Oct 22, 2020

Needs more detailing for datasets and dataframe apis

創建者 Wolfgang G

Aug 30, 2017

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

創建者 Manuel W

Apr 18, 2017

Would be better to have more and shorter exercises.

創建者 Ruslan A

Aug 23, 2017

lectures don't correlate to practical assigment :(

創建者 David G

Aug 25, 2017

Great course, but can be great idea have the ppts

創建者 Yuan R

Jan 20, 2018

Great course that is very practical for the job.

創建者 Guillermo G H

Jun 30, 2017

Great approach to learn about Spark in practice

創建者 Michaël M P

Feb 05, 2019

Talk about how to set Scala version in Eclipse

創建者 林鼎棋

May 30, 2017

Great! But I want to know more about dataset!

創建者 VeeraVenkataSatyanarayana M

Jun 04, 2017

Basics are covered in an effective way.

創建者 Pavel O

Aug 12, 2017

Good final course for Scala learners.

創建者 Lucas F

May 15, 2017

Great lectures and great content!

創建者 Роман В

Jun 24, 2018

I would like to learn some more.

創建者 Hoon P

Apr 19, 2017

Learned Spark APIs, internals.

創建者 Alberto P d P

May 12, 2017

Very good and concise course.

創建者 Stéphane L

Oct 13, 2017

Very useful