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Вернуться к Big Data Analysis with Scala and Spark

Отзывы учащихся о курсе Big Data Analysis with Scala and Spark от партнера Федеральная политехническая школа Лозанны

4.7
звезд
Оценки: 2,431
Рецензии: 504

О курсе

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....

Лучшие рецензии

BP
28 нояб. 2019 г.

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
7 июня 2017 г.

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!

Фильтр по:

276–300 из 487 отзывов о курсе Big Data Analysis with Scala and Spark

автор: Fedor C

31 авг. 2017 г.

Very interesting course! Thanks!

автор: Vasyl Y

26 июня 2017 г.

Cool course! Thanks for your job

автор: Kyle L

10 июня 2017 г.

very good course, really enjoyed

автор: Alex S

5 мая 2018 г.

Super course, well done Heather

автор: Jong H S

18 авг. 2017 г.

A wonderful and timely course.

автор: Jon Z

5 июля 2017 г.

Great course, I learned a lot.

автор: Salvatore R

23 апр. 2017 г.

This course is very well done.

автор: Jay

21 сент. 2017 г.

cool teacher and cool course!

автор: Atsuya K

29 окт. 2017 г.

A good quick intro to Spark.

автор: Jakub T m G

27 июня 2017 г.

good introduction into Spark

автор: Benzakoun S

8 мая 2017 г.

excellent quality of content

автор: bechir n

21 нояб. 2020 г.

It really helped me at Work

автор: savitri v v

27 июля 2018 г.

Very good learning portal

автор: Jorge B C

1 мая 2017 г.

Very interesting course!!

автор: Peter S

2 апр. 2017 г.

Another fun Scala course!

автор: Zilvinas

27 мар. 2017 г.

Very fun and informative!

автор: Canh S L

25 мар. 2017 г.

really good, informative

автор: vijay k k

7 мая 2018 г.

Good course to learn it

автор: Hermann H

19 июля 2017 г.

Great material !!! ;-)

автор: vikas s

28 июля 2017 г.

awesome course content

автор: Deleted A

26 июня 2017 г.

Great course. Thanks!

автор: Marija N

5 июля 2019 г.

Absolutely fantastic!

автор: Subodh C

30 мар. 2019 г.

Thanks Prof. Miller !

автор: Nebiyou T

26 дек. 2017 г.

Very good instructor!

автор: Dinesh A G

2 апр. 2017 г.

good course on spark.