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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: 2,468
•
Рецензии: 509

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

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!

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.

Фильтр по:

401–425 из 492 отзывов о курсе Big Data Analysis with Scala and Spark

автор: Alberto A

•
29 июня 2017 г.

Good stuff, well presented, but the instructor takes no risks to explain more complex details.

автор: aknin k

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25 дек. 2019 г.

Bien mais j'aurais aimé avoir plus d'exercices pour s'entrainer sur les dataframes / datasets

автор: Chuishi

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8 янв. 2018 г.

Very good course! Contents are very useful. The lectures are intuitive, thorough and clear.

автор: Sjoerd T

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8 апр. 2017 г.

Took a bit long before the course actually started, but when it did, it was a great course!

автор: Sridhar K

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7 сент. 2018 г.

Really i get a wonderful experience and it gives the platform to increase my knowledge.

автор: Federico A G C

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30 июня 2018 г.

The instructor is great as well as the material. The exercises are a little off topic

автор: Khalid S

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25 мар. 2018 г.

The course didn't flow as smoothly as I would have liked but I still recommend it.

автор: Piotr G

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5 июля 2017 г.

Great content, however some materials are not clear and videos had a few problems.

автор: Aaron

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10 дек. 2019 г.

A good course to know about how spark works but not how to use it, I like this!

автор: Иван М

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8 апр. 2017 г.

Nice course, could use little fixes. Sometimes practice goes ahead of theory

автор: Kristoffer V

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3 июля 2019 г.

Sometimes the labs included techniques not fully covered by the lectures.

автор: Faisal A

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29 июня 2020 г.

Assignments could be made a little better. The lecture content is great.

автор: Anuj M

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21 июня 2020 г.

Great course, trainer is simply amazing with the delivery and teachings

автор: Deepak D

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23 нояб. 2018 г.

Not specify & given instruction regarding how to submit the solution

автор: Pedro M

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29 апр. 2017 г.

Very interesting course about Spark, it covers a lot of key concepts!

автор: Vahid S

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27 июня 2020 г.

I think programming assignments could be better but still OK.

автор: Francis T

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16 апр. 2017 г.

I really liked the content regarding Dataframes and Datasets.

автор: Emmanouil G

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1 апр. 2017 г.

Assignment Instructions need improvement in terms of clarity.

автор: Gongqi L

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9 апр. 2017 г.

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

автор: kaushik

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9 апр. 2017 г.

Good course ! But does need more programming assignments

автор: Mohammad T

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24 авг. 2019 г.

such a beautiful course design for a bigData devlopers

автор: Kota M

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5 апр. 2018 г.

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

автор: Anuj A

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22 окт. 2020 г.

Needs more detailing for datasets and dataframe apis

автор: Wolfgang G

•
30 авг. 2017 г.

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

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