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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
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Оценки: 2,383
Рецензии: 494

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:

126–150 из 477 отзывов о курсе Big Data Analysis with Scala and Spark

автор: Sreeraj R P

6 янв. 2019 г.

Very good course for a great start in Spark. Require some initial knowledge and coding experience in Scala.

автор: Rocky J

8 мая 2017 г.

Great subject, well explained with solid weekly assignments make this course a stellar learning experience.

автор: Andrey M

10 янв. 2019 г.

Thank you for the great introduction in to the Spark, What it is and What are the most commonly used APIs.

автор: Daniele M

22 июня 2019 г.

Great Introduction to spark. Programming assignments helped me to improve my skills. Thank you very much.

автор: Rajesh B

16 июля 2019 г.

Very nice explanation, trainer has good knowledge, course materials are good, video quality is too good.

автор: Kolja M

25 мар. 2018 г.

Very nice in depth learnings. The teacher is very good and keeps the lessons short but still meaningful.

автор: Zdeněk H

22 июля 2017 г.

Thanks to this course I think that I have finally understood partitioning and everything about Datasets.

автор: bezzineradhia@gmail.com

15 сент. 2020 г.

Excellent cours! par contre je n'arrive pas à obtenir mon certificat. Est cela toujours possible? Merci

автор: Marco B

16 мар. 2018 г.

Excellent course!

Well-developed lectures and good-structured modules

With hands-on programming examples

автор: Jijo T

13 апр. 2017 г.

It was well worth the wait! The instructor was good. Assignments were challenging as well as hands on!

автор: Shashank B

15 окт. 2017 г.

It is an excellent course with good clear explanation of theoretical concepts and practical examples.

автор: Francois S

6 сент. 2020 г.

Very good in depth explanation of spark. Recommended for those who want to further understand spark.

автор: 本达 续

4 авг. 2017 г.

A very natural application of functional programming to real world distributed computation problems.

автор: Nishant T

28 мар. 2017 г.

Brilliant intro to Spark. I really like the enthusiasm with which Heather explains the key concepts.

автор: Alexander Z Q

27 авг. 2017 г.

Course with excellent content, methodology and teacher. It was an extraordinary learning experience

автор: Roberto S

4 июля 2017 г.

Quite advanced; links seamlessly with the previous courses in the specialization. Very rewarding.

автор: Ashish D

10 нояб. 2020 г.

An optimum level of detail in content, coupled with reasonably involved programming assignments

автор: Bogdan T

25 февр. 2020 г.

The amount of information delivered and the way it was explained is simply amazing. Thank you!

автор: Shiyan C

6 мар. 2018 г.

Wish we could have an in-depth spark class that cover spark streaming and structure streaming.

автор: Animesh K

17 мар. 2017 г.

Really Awesome course. The instructor is great. Looking forward to more courses from Heather.

автор: Jiri K

7 апр. 2017 г.

Awesome! Perhaps couple of tests would be handy, just a few to have something to start with.

автор: Thomas Z

10 февр. 2018 г.

Good course. Can recommend it for everyone who wants to get into the field of data-science.

автор: CAI X

16 июля 2017 г.

Well explained and demoed . Good introduction to spark, the most useful big data framework!

автор: Vishnu P

15 мая 2018 г.

The best course. Good lectures with best examples. Thanks a lot for this wonderful course.

автор: Vlad N

3 апр. 2017 г.

Nice topics regarding using partitions for Spark and encoders!! Really interesting course