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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

4.7
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2,538 個評分
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519 條評論

課程概述

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://www.coursera.org/learn/parprog1....

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BP

2019年11月28日

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.

CC

2017年6月7日

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!

篩選依據：

426 - Big Data Analysis with Scala and Spark 的 450 個評論（共 504 個）

創建者 Emmanouil G

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2017年4月1日

Assignment Instructions need improvement in terms of clarity.

創建者 Gongqi L

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2017年4月9日

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

創建者 kaushik

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2017年4月9日

Good course ! But does need more programming assignments

創建者 Mohammad T

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2019年8月24日

such a beautiful course design for a bigData devlopers

創建者 Kota M

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2018年4月5日

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

創建者 Anuj A

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2020年10月22日

Needs more detailing for datasets and dataframe apis

創建者 Wolfgang G

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2017年8月30日

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

創建者 Manuel W

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2017年4月18日

Would be better to have more and shorter exercises.

創建者 Ruslan A

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2017年8月23日

lectures don't correlate to practical assigment :(

創建者 David G

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2017年8月25日

Great course, but can be great idea have the ppts

創建者 Yuan R

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2018年1月20日

Great course that is very practical for the job.

創建者 Guillermo G H

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2017年6月30日

Great approach to learn about Spark in practice

創建者 Michaël M P

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2019年2月5日

Talk about how to set Scala version in Eclipse

創建者 林鼎棋

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2017年5月29日

Great! But I want to know more about dataset!

創建者 VeeraVenkataSatyanarayana M

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2017年6月4日

Basics are covered in an effective way.

創建者 Pavel O

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2017年8月12日

Good final course for Scala learners.

創建者 Lucas F

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2017年5月15日

Great lectures and great content!

創建者 Роман В

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2018年6月24日

I would like to learn some more.

創建者 Hoon P

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2017年4月18日

Learned Spark APIs, internals.

創建者 Alberto P d P

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2017年5月12日

Very good and concise course.

創建者 Javier L B

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2021年12月7日

Good course.

創建者 Stéphane L

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2017年10月13日

Very useful

創建者 Srinivasu N

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2020年5月15日

good

創建者 Devaraja K R

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2018年11月14日

Good

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