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!
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.
автор: Saiteja t•
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автор: Kirill K•
A good one.
автор: William H•
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автор: Bianca T•
Taking into consideration that this was the first edition of the course, I can say that it has been a nice journey. I am glad about the fact that Heather managed to expose a bit of the Spark internals and not only talk about querying data and how easily this can be made by using Spark (as most of the Spark oriented courses consist of).
In addition to this, I could listen to Heather all day long - she's a great presenter and has wonderful teaching skills.
However, the homework has outlined some neglected aspects of the course:
- vague description or requirements
- not strongly related to the presented content (the lectures outlined partitioning mechanism, but the homework 2 did not require it...)
- not so meaningful feedback, except for some tests failing/passing - I would have expected something like you did ok, but your job took longer than expected; check out this and that
Overall, it's been a highly expected course and it was nice to get a broader outlook on Spark. I hope that there will be more courses (and more detailed) related to Spark ecosystem in the near future.
автор: Anton M•
Really enjoyed most part of the course, it was a fun ride with Spark !
Explanations of lector was crystal clear and I liked all assignments (except last one)
There are some cons though:
-> Week 3 contains no assignment, I would prefer to have one really dedicated to "Partition and Shuffling" subject
-> Spark SQL explanations about untyped were too much shady. It somehow feels like this API goes totally orthogonal to everything functional we have had so far. It's like running in Java but using C with JNI... Well, after all, it's a drawback of API, not course itself, but still having bit of aftertaste of fighting with Scala type system trying to glue SQL... meh
-> there are many missed opportunities to have proper Coursera quiz during lectures
автор: Robin B•
Very good introduction to RDDs and DataFrames/Dataset along with valuable insight into performance considerations.
I'd done some prior work with Hadoop/Pig in the past and more recently with Spark (mainly DataFrames/GraphFrames) - this was really useful to round out my understanding of RDDs and optimisation.
The assignment guidance in the code comments could be more complete to save having to refer back to the site (and maybe reference specific video lectures with the hints). Though it's good that the assignment exercises aren't tutorial-grade, as that makes the experience more transferable to real projects.