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Avis et commentaires pour l'étudiant pour Big Data Analysis with Scala and Spark par École polytechnique fédérale de Lausanne

4.7
2,082 notes
418 avis

À propos du cours

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....

Meilleurs avis

CC

Jun 08, 2017

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!

CR

Apr 10, 2017

Great introduction to spark. Fun assignments. Since it was the first ever session, there were quite a few kinks with the assignments. But the discussion forums rescued me any time I was stuck.

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76 - 100 sur 402 Examens pour Big Data Analysis with Scala and Spark

par Jay

Sep 21, 2017

cool teacher and cool course!

par Georgi Y

Jul 07, 2017

Excellent course!

par Jevelson S

May 18, 2017

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

par Salvatore R

Apr 23, 2017

This course is very well done.

par Rafael M

Oct 18, 2017

Great Course

par Grzegorz G

Mar 21, 2017

Some of the assignments are a bit challenging, due to grading system I suppose, but in the end general impression about this course is very positive

par Zhu L

Aug 11, 2017

An introductory course to spark programming, lectures are well-balanced between theory and boier-plate codes, but programming assignments are mainly about teaching you the APIs. The problem-solving part is basically trivial, whereas most of the time were spent on searching for API documents and correcting compiler errors and runtime exceptions.

par samy k

Mar 21, 2017

Interesting and challenging course! Thank You!

par Marcus E

Apr 09, 2017

The course gave me insight into the world och big data batch processing and how Spark solves it. Heather does a great job with presenting the material in a thorough way with relevant theory and illustrative examples. The assignments are well balanced and forces you to apply all your new knowledge when solving them. I highly recommend this course!

par Fernando

Jun 06, 2018

Great course about Big Data analysis

It was my first exposure to Big Data frameworks and I learned a lot about the problems trying to be solved and the power of Spark.

par lu

Sep 17, 2017

A good introduction to Scala programming in Spark environment.

par Patrick

Jan 12, 2018

Been working with Spark since 0.9 and this was still worthwhile. Excellent course.

par Gao Y

Apr 04, 2017

Nice course. Big jump at the end. The assignment is well hinted.

par Kirill K

Oct 10, 2017

A good one.

par Lewis

Mar 29, 2017

It was short and sweet. However, I wish the assignments had more unit tests to fill gaps where the instructions weren't clear.

par Bennie K

Oct 15, 2017

Really clear and direct. Would love to see another course on the Advanced Spark topics such as Spark Streaming and Spark custom libraries

par Jose E T

Jun 02, 2017

Great Course!

par Alexandr M

Jun 24, 2017

This course gives basics of distributed computing by practical examples, several alternative approaches to the same problem are considered, this gives more insight and flexibility. Very interesting one!

par Florian W

Apr 01, 2017

It's a great course with lots of insight into spark. At first it's confusing - first rdds; then dataframes and later datasets. But this is by no means the instructors' fault. Heather greatly describes in detail what goes on under the hood and why dataframes are way faster than simple rdds and why we have to give up some of our beloved typesafety of scala-land to let catalyst do its magic. Datasets try to bring some of it back.

I really enjoyed coding the assignments. Took me ~2hrs each. The tasks were fun and like those you would find in the wild.

I already applied some of the skills I learned here at work and successfully implemented a simple recommendation engine that will go to production next week.

Highly recommend this course!

par Pengcheng L

Jun 05, 2017

Thanks :)

par Aleksey I

Jun 02, 2017

Good course.

par Hessam S M

Mar 25, 2018

Excellent course. I had some knowledge about Spark before but this course helped me to leverage my skills from pure theory to something practical. Now I have the confidence I can use spark to solve real life problems. This specialization as a whole is totally changing my career prospect. Thank you EPFL, Dr. Miller and Coursera for providing such opportunity for me.

par Gary Z

Apr 10, 2017

Best Spark Scala course! Clear explanation! Thanks Dr. Heather

par Mani P

Apr 09, 2017

Excellent material. Very good flow. Heather has an amazing way of walking through the flow and simplifying the concepts. Great assignments -- takes a bit longer than 3 hours.

par JULIAN A G V

Feb 02, 2018

Great course!