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學生對 洛桑联邦理工学院 提供的 Big Data Analysis with Scala and Spark 的評價和反饋

2,079 個評分
418 個審閱


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:



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!


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.


51 - Big Data Analysis with Scala and Spark 的 75 個評論(共 402 個)

創建者 Jorge B C

May 02, 2017

Very interesting course!!

創建者 Jean-Francois T

Mar 27, 2017

Good material and induction to Spark, good complement of parallel computing in Scala

創建者 Mostafa J

Jun 13, 2017

Very challenging but I learned a lot.

Thanks a lot, Dr. Heather Miller!

創建者 Nebiyou T

Dec 26, 2017

Very good instructor!

創建者 Konstantin

May 29, 2017

Nice course, thanks!

創建者 Antonio A

Oct 20, 2017

Clear explanations, with emphasis done on the important/practical stuff. From zero to a general understanding on Spark and the available tools in 4 weeks.

創建者 Shashishekhar D

Jan 06, 2018

Simple, Easy to understand. The course has helped me a lot to understand the concepts.

創建者 Dennis Y

Jun 06, 2017

Thank the teacher, the course is very good, the teacher is also very nice. The first three weeks of feeling learned a lot of new knowledge, the last week may be each class time is relatively long. It would be better if you could split it.

創建者 Neeraj V D

Feb 27, 2018

limited content with dewp knowledge

創建者 Anna B

Mar 20, 2017

The course covers the important concepts and explains them in detail.

Homework tasks really make you think, revisit the lectures and read documentation, until you get it right, and that all deepens understanding of the material.

I also obtained some clues for the future: the lectures provided me with context, which helps formulate questions when searching for answers elsewhere.

創建者 Zhaokang P

Sep 18, 2017

this course help me form a basic understanding of Spark and how to use it to analyze large scale dataset. Besides fundamental knowledge of how to use, the lecturer also provide students with some deeper concept of how to optimize the performance of spark programming, which can be very useful in running code on large dataset.

創建者 jose c a

May 05, 2018

Muy Bueno!!!!

創建者 Dmitriy K

Mar 20, 2017

Thanks Heather! You did a great job with this course.

創建者 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.

創建者 samy k

Mar 21, 2017

Interesting and challenging course! Thank You!

創建者 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!

創建者 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.

創建者 Samuel L

Mar 23, 2017

Very well taught and insightful! Especially the combination of slides, and additionally drawn notes on that slides, I found very good.

創建者 Juan L R A

Jun 19, 2017

Very good course and good materials for learning

創建者 Oleg m

Apr 10, 2017

First weeks were overcomplicated with k-means and stuff not related to Spark itself.

In general - GREAT JOB !!! Thx for such kind courses

創建者 Tal G

Apr 08, 2017

Excellent teacher

創建者 Florian B

Nov 18, 2017

Super cours, merci beaucoup! EPFL always rocks.

創建者 Kushagra V

Jun 14, 2017

Very nicely taught. Liked these "long" lectures of 15-20 min where the instructor gradually builds the material around the topic. Most other courses online, especially Udacity has frustratingly short videos where more than half the time the student has to keep clicking to the next video. Material coverage is sufficiently wide as well and the curriculum is freshly designed which is very important in this field.

創建者 許致軒

Apr 16, 2017

Very Very Interesting and helpful!

The slides' layout is very clear and step by step for each important topic.

The motivation of why we need dataframe and dataset and what's their difference is explained with a logical and reasonable way!

創建者 lu

Sep 17, 2017

A good introduction to Scala programming in Spark environment.