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

2,383 évaluations
494 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:

Meilleurs avis

7 juin 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!

28 nov. 2019

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.

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26 - 50 sur 477 Avis pour Big Data Analysis with Scala and Spark

par Ignacio A

17 avr. 2017

This course is a great introduction to Spark. The only thing I think could be improved is that each programming assignments has unit tests that drive students towards the final solution. I saw lots of people complaining in the forums about this slow and tedious back and forth of having the grader testing their code.

par Yury C

18 juil. 2019

This course was by far the best of 22 courses I've done on Coursera. Prof Miller has this rare ability of presenting material in concise and interesting way and yet going into nitty gritty aspects when needed (in another course on Spark technology, such intricacies weren't covered). Thanks a lot for this course!

par Ananda P V

31 août 2017

excellent introduction to Spark. I was always looking for some course which touches the underlying functional aspect of Spark then just showing syntactic values. Moreover this course also teaches how parallelism and distributed process works with Spark. You also get an idea why Spark is written in Scala.

par Doug C

7 août 2020

I thought it was very good, hands on. I think they need to add a lesson 3 homework to bridge the gap between the lectures. Week 4 lecture is really long. The HW4 is a bit tricky and requires alot of research and lack of any provided unit tests makes it alot of work to figure out what is wrong.

par Xiongchu W

5 août 2017

This course is indeed introductive to learn all the necessary stuffs about Spark. It is pretty good to tell much about shuffling. Because we should not only be familiar with how to operate on Spark, but we should really have a good understanding of what's going on underneath the hood. Thanks!

par Deepika S

19 juin 2020

It is a great course with excellent material.

There is a lot to try in this course, concepts that one has to try oneself which opens opportunities to learn.

Please go ahead with the course if you are starting to work on Scala and Spark. Iterations run great on a decent 8 GB 64 bit machine.

par Aldrin

10 juil. 2017

The information was explained really well for someone coming in with no spark and minimal scala knowledge. Due to this course I understood basic spark concepts well enough to begin understanding pipelines built on top of spark such as ADAM.

I would highly recommend this course to everyone.

par Edgar D

10 mars 2019

Favorite so far out of the Scala Specialization Course. It was executed really well, and taught really well, too. Kinda wish they would add more exercises to help us get more experience with some of the concepts, but that's something you can always just do by yourself either way.

par Emanuel E d S O

22 oct. 2017

Excelente curso. Já trabalhei com Spark, mas tive a oportunidade de aprender muitas coisas novas sobre ele. Achei muito interessante a abordagem sobre as novas estruturas de dados que chegaram nas novas versões (para mim, pelo menos, pois trabalhei com a versão 1.6). Recomendo.

par Markus B

9 avr. 2017

Great course overall. The feedback on failed tests and out of memory errors on the assignments can be improved to make it more user-friendly.

Would be great to see a more advanced version of this course that dives deeper into the machine learning features of Spark, etc.

par Jaseer A

23 déc. 2017

Really enjoyed this course. Unlike previous courses where I had to wrestle with algorithms and only learn the subject as a side effect, the assignments in this course directly addressed the subject. One of the best in this series except for the first course in scala.

par Mugren A

20 août 2020

Perfect. One of the most summarized course, to the point, and straight forward without any trouble. Special thanks to Prof. Heather for focusing on the optimization part and performance and easily explained the lazy transformation and how it could highly cost us.

par Gustavo H L d S

31 mai 2020

Such a great course! Prof. Miller gives a very good coverage about spark, it's perfect for beginners who never deal with his technology and advanced users who wants o refresh their knowledge about this subject. The didactic of teaching is also excellent!

par Šejla Č

20 mars 2019

Brilliant lecturer and slides! The only problem is assignments not being clear on the expected outputs. Sometimes it takes more time to figure out what exactly is asked than to find the solution. A few more test cases or detailed examples would help.

par Kevin L

2 avr. 2019

I loved this course - it was a great introduction to Spark. At the end, I wasn't (and am still not) clear on type-safe operations on Datasets, and now to write Tests to verify this.

These will be one of the targets of my upcoming research and study.

par AJ C

9 avr. 2017

This course is a nice guided way to get started with Apache Spark! I wish I took this course earlier when i was using Spark at my previous company. It would've come in handy. Plenty of great content and the course exercises supply good practice.

par Abhishek K

11 oct. 2020

The course has a great content. The assignments are a bit tough for beginners but if you keep on trying, you will get some great insights of the technology. Also has the best and unique use case scenarios which keep questioning your knowledge.

par Dario G

8 sept. 2017

Lovely presentation of Apache Spark fundamentals using Scala. I believe that this course gives you enough background to do just about anything you want (as long as you have some familiar with Scala and SQL, and are willing to dig deeper).

par ravisekhar_g

18 avr. 2020

This is the best content among the tutorials I've seen in Spark, the Prof. Heather maintains perfect balance between internals of spark and general usage. The examples given and assignments are realistic when compared word count problems.

par Dennis Y

6 juin 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.

par Bora K

1 sept. 2018

Teacher has excellent teaching skills. She takes enough time to go through to concepts. Before introducing a new technique she teaches why the new technique is needed and explains how it solves existing problems. Absolutely great course.

par 許致軒

16 avr. 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!

par Raduś N

23 mai 2017

Awesome teacher - very engaging. This is probably first time when I am watching lectures with pleasure. Also you can easily feel that course is fresh and specially made for this unlike previous ones from Scala speciality.

par Heyang W

18 août 2017

A walk through from the oldest RDD to newest Dataset API of spark, together with brief introduction on how spark work. Home work set up several scenario to use the different kinds of spark API to do basic data analysis.

par Mike D

6 avr. 2017

Great introduction course to Spark with excellent materials and hand-on programming assignments. Thanks for taking effort to get this class online. I have enjoyed it very much.

Kudos to Professor Miller, we love you :-)