Chevron Left
Big Data Analysis with Scala and Spark に戻る

スイス連邦工科大学ローザンヌ校(École Polytechnique Fédérale de Lausanne) による Big Data Analysis with Scala and Spark の受講者のレビューおよびフィードバック

4.6
2,565件の評価

コースについて

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....

人気のレビュー

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!

フィルター:

Big Data Analysis with Scala and Spark: 451 - 475 / 507 レビュー

by Javier L B

2021年12月7日

by Stéphane L

2017年10月13日

by Srinivasu N

2020年5月15日

by Devaraja K R

2018年11月14日

by Jim N

2017年4月12日

by Giovanni F

2021年2月20日

by Harold O

2017年4月16日

by Tom C

2017年4月5日

by Alexei M

2017年4月19日

by Sam Z

2017年5月3日

by Horia R

2017年4月5日

by Allen S

2017年7月11日

by Rob S

2018年10月15日

by Luis V

2017年9月30日

by Jeff B

2017年7月5日

by Vesa P

2017年7月2日

by Waqas A

2020年11月15日

by Lance F

2017年3月27日

by Aaron S

2017年6月4日

by Rafael G

2017年3月31日

by Korbinian K

2017年10月10日

by Andre H

2017年8月5日

by Jeni

2019年11月29日

by Alexandre V

2017年11月25日

by Daniel Z

2020年3月14日