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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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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

CH

Nov 16, 2017

although spark part is taught nicely, it also takes a lot of time to understand the sql part and remember a lot of sql operations as a zero background man in sql

NG

Mar 27, 2017

goot as introduction about spark and big data. Small notice: it is incorrect to compare performance hadoop and spark. As I understand, spark was expected to be compacred with MapReduce.

筛选依据：

301 - Big Data Analysis with Scala and Spark 的 325 个评论（共 511 个）

创建者 savitri v v

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Jul 26, 2018

Very good learning portal

创建者 Jorge B C

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May 1, 2017

Very interesting course!!

创建者 Peter S

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Apr 2, 2017

Another fun Scala course!

创建者 Z

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Mar 27, 2017

Very fun and informative!

创建者 Canh S L

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Mar 25, 2017

really good, informative

创建者 vijay k k

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May 7, 2018

Good course to learn it

创建者 Hermann H

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Jul 19, 2017

Great material !!! ;-)

创建者 vikas s

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Jul 28, 2017

awesome course content

创建者 Deleted A

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Jun 26, 2017

Great course. Thanks!

创建者 Marija N

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Jul 5, 2019

Absolutely fantastic!

创建者 Subodh C

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Mar 29, 2019

Thanks Prof. Miller !

创建者 Nebiyou T

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Dec 26, 2017

Very good instructor!

创建者 Dinesh G

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Apr 2, 2017

good course on spark.

创建者 jose r

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Nov 24, 2017

Great Course, thanks

创建者 Konstantin

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May 29, 2017

Nice course, thanks!

创建者 Luis M M S

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Feb 17, 2023

I loved this course

创建者 abhinav

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Dec 10, 2017

Wonderful course!!!

创建者 prashant b

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Apr 7, 2017

very nicely taught

创建者 Manish M D

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Sep 15, 2019

Excellent course.

创建者 DAVID J A

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Mar 1, 2018

Simply brilliant.

创建者 Rajesh G

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Dec 1, 2017

Excellent course!

创建者 Georgi Y

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Jul 6, 2017

Excellent course!

创建者 Taneli L

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Apr 9, 2017

Excellent course.

创建者 Tal G

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Apr 8, 2017

Excellent teacher

创建者 Fang Z

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Apr 5, 2017

Very good course.