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学生对 École Polytechnique Fédérale de Lausanne 提供的 Big Data Analysis with Scala and Spark 的评价和反馈

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2,595 个评分

课程概述

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://hua.dididi.sbs/learn/parprog1....

热门审阅

CC

Jun 7, 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!

AW

Dec 5, 2025

This course has a bit over-complicated practice assignments (where overcomplication is not related to the course), but the content itself is really good, communicative and 100% worth going through.

筛选依据：

276 - Big Data Analysis with Scala and Spark 的 300 个评论（共 511 个）

创建者 Msellek A

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Jan 26, 2019

Great course ! Thanks for the effort

创建者 Jose M N

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May 28, 2018

Great course. Thanks for everything.

创建者 cnu m

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Sep 13, 2017

Very nice explanation with examples.

创建者 Martin A

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May 3, 2017

Great course, good intro into Spark.

创建者 Manuel M C

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Mar 23, 2017

Great course, keep up the good work.

创建者 Neeraj V D

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Feb 27, 2018

limited content with dewp knowledge

创建者 Abhay D

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Nov 4, 2018

Wonderful course. Helped me a lot.

创建者 David M

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Sep 18, 2017

Concepts are very well explained..

创建者 Liu D

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Jul 25, 2017

Great speeches with great exercise

创建者 Fernando R

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Oct 28, 2017

it was a super interesting course

创建者 Alejandro R C

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Aug 13, 2017

Everything was easy to understand

创建者 Jinfu X

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Mar 12, 2017

Thanks! It's an excellent course.

创建者 Fedor C

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Aug 31, 2017

Very interesting course! Thanks!

创建者 Vasyl Y

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Jun 26, 2017

Cool course! Thanks for your job

创建者 Kyle L

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Jun 10, 2017

very good course, really enjoyed

创建者 Jong H S

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Aug 18, 2017

A wonderful and timely course.

创建者 Zhu X

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Jul 5, 2017

Great course, I learned a lot.

创建者 Salvo

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Apr 23, 2017

This course is very well done.

创建者 Jay

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Sep 20, 2017

cool teacher and cool course!

创建者 Atsuya K

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Oct 29, 2017

A good quick intro to Spark.

创建者 Jakub T m G

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Jun 27, 2017

good introduction into Spark

创建者 Benzakoun S

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May 8, 2017

excellent quality of content

创建者 Akash D

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Jul 26, 2021

Wonderfully designed course

创建者 bechir n

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Nov 21, 2020

It really helped me at Work