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

4.7
звезд
Оценки: 2,485
Рецензии: 513

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 496 отзывов о курсе Big Data Analysis with Scala and Spark

автор: Gregory E

10 мар. 2018 г.

Good course, shows a lot of useful and unobvious things about Spark. But not always has well described assignments

автор: Adrian D

22 дек. 2020 г.

The course is explained very well but the assignments are a bit ambiguous. The requirements can be a bit clearer.

автор: Vlad F

14 мар. 2018 г.

I learned a great deal about the Spark API. I recommend it to anybody eager to self educate after working hours.

автор: Aleksander K

2 апр. 2017 г.

This class is great! Highly recomended! It helped me to understand and perform better at my daily working tasks!

автор: Jevelson S

17 мая 2017 г.

This course is awesome. I got a pretty good idea of spark. In fact this course helped me understand scala well.

автор: Wei-Ting C

13 сент. 2017 г.

This is my first completed course on Coursera! It's good for understanding Apache Spark's RDD and its usage.

автор: Roman Z

14 апр. 2017 г.

I like the course tempo very much. It kept me away from doing anything else while listening to the lectures.

автор: Tomasz J

8 апр. 2017 г.

Great, short course, which gives great insight into Spark and ad-hoc data processing on Hadoop-ish clusters.

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: Denis A 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