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.
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!
автор: Gongqi L•
Very good course, but it needs more details and examples.
Good course ! But does need more programming assignments
автор: Mohammad T•
such a beautiful course design for a bigData devlopers
автор: Kota M•
It is a good course, but the lecturer speaks too fast.
автор: Anuj A•
Needs more detailing for datasets and dataframe apis
автор: Wolfgang G•
Very well-lead introductory, a bit lengthy at times.
автор: Manuel W•
Would be better to have more and shorter exercises.
автор: Ruslan A•
lectures don't correlate to practical assigment :(
автор: David G•
Great course, but can be great idea have the ppts
автор: Yuan R•
Great course that is very practical for the job.
автор: Guillermo G H•
Great approach to learn about Spark in practice
автор: Michaël M P•
Talk about how to set Scala version in Eclipse
Great! But I want to know more about dataset!
автор: VeeraVenkataSatyanarayana M•
Basics are covered in an effective way.
автор: Pavel O•
Good final course for Scala learners.
автор: Lucas F•
Great lectures and great content!
автор: Роман В•
I would like to learn some more.
автор: Hoon P•
Learned Spark APIs, internals.
автор: Alberto P d P•
Very good and concise course.
автор: Stéphane L•
автор: Srinivasu N•
автор: Devaraja K R•
автор: Jim N•
I understand that creating such a course is a tremendous amount of work. Let me congratulation the developers for all their hard work. I learned a lot. I'm glad I good the course, and I'm speechless that I finally finished it with a passing albeit imperfect score. This was the maiden voyage and it has some problems that should probably be corrected. That's my opinion.
There were generally two sets of challenges with each assignment exercise (1) undemanding the scala/big-data component, and (2) understand what's being asked. Sometimes the comment in the code are wrong or misleading. In particular in the 2nd set of exercises. The functions are very poorly specified, and there are no unit tests. there should be one or the other. Without a specification the user cannot write his own tests. In addition the 2nd exercise is intended to be do-able, but not efficiently until the user views week 3's videos. Because of this the text output is EXTREMELY verbose, making it impossible to read the error messages and understand them. When the user finally submits the assignment it fails and the grader gives misleading error messages. A failing unit test should at the very least explain what the test was, what the measured value was, and what was expected. This is especially true when the user is forbidden from looking at the actual testing code. An additional problem with exercise 2, is that the student is asked to calculate a particular percentage, but it is not explained what this is a percentage OF and there are several ways to interpret it. I didn't realize until wasting 2 weeks that there was an alternate interpretation which I could try.
In the 3rd exercise some of the comments in the code are wrong/misleading. Particularly with regard to classifiedColumns. comment #3 should read:* 3. other activities (leisure). These are the columns starting with “t02”, “t04”, “t06”, “t07”, “t08”, “t09”, “t10”, “t12”, “t13”, “t14”, “t15”, “t16” and “t18” BUT EXCLUDING those which are not part of the previous groups only. Otherwise the sentence is at best grammatically incorrect, and at worst misleading.
Another significant issue with this "Bit Data" course is that it assumes a user understands data base and can construct sql queries. Well, such background is not a prerequisite, but the student needs such information to successfully finish the exercises. I can understand the temptation by the course developers to include a section on SQLspark, as this is a very powerful set of spark libraries, but I believe it is beyond the prerequisites. I could not have finished the course if I hadn't had an SQL/data-base expert in the same office, who I could pose questions to.
I hope you find my comments useful.
автор: Giovanni F•
The actual lectures are very very good: substantial; clear and linear; very good graphics; adequate peace; good combination of clear slides and hands use to highlighting.
The main weak part of this course is the technical setup to do the exercises. It's a rather complex preparation, to be done following instructions which are largely outdated. Therefore lots of googling, looking the forum, trial and error: it took a lot of time for a painful experience I've learnt nearly nothing from. And the considerable complexity of setting up the local infrastructure only grants a limited and basic spark configuration (with no real scale out beyond the number of cpu's), therefore it's no beneficial in any way.
It would be much more instructive if the exercise could be worked out on an existing could Spark installation, where one could also have a sense of how the Spark capabilities can scale out.
Lastly, the splitting of material by weeks: for weeks 1,2 and 4 the exercises appeared as being assigned twice. Unclear why that is. I ignore and somehow the duplication and somehow got the certificate.
A second week point (though less pronounced) applies only if you follow this course w/o following the course others in the speciality: the required knowledge of Scala. I had never done Scala before and found that in the course description the importance of knowing the language is downplayed. It's true that some OO prior experience, common sense and patience one can get a lot out of this course, using inference and intuition (and google) about Scala.
автор: Harold O•
This is a really excellent course. It deals with difficult content clearly, thoroughly and at a good pace. I would now be happy to use Spark in my work and feel I have a strong base to go on to further study. The exercises are well conceived covering fairly realistic use cases and are of about the right complexity. BUT, the feedback from the automatic grading really lets it down.
The auto grading tests are at too high a granularity, each test tests too many things. They give cryptic errors such as '<some random element> is empty'. You have no idea why the element is empty as the students are given a different dataset to the one tested on. Moreover, the failed tests are invariably nothing to do with learnt course content, but trivial rounding/formatting errors. The forums are a lifesaver, but I still spent a good two weekends working on bugs once I'd got the assignments 70% right. I would not recommend to a completist!
All the same, thanks to Heather for the wonderful work she's done putting it together and the excellent lectures she gives.