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From Jörn Franke <jornfra...@gmail.com>
Subject Re: Using Flink in an university course
Date Mon, 04 Mar 2019 12:44:02 GMT
It would help to understand the current issues that you have with this approach? I used a similar
approach (not with Flink, but a similar big data technology) some years ago

> Am 04.03.2019 um 11:32 schrieb Wouter Zorgdrager <W.D.Zorgdrager@tudelft.nl>:
> Hi all,
> I'm working on a setup to use Apache Flink in an assignment for a Big Data (bachelor)
university course and I'm interested in your view on this. To sketch the situation:
> -  > 200 students follow this course
> - students have to write some (simple) Flink applications using the DataStream API; the
focus is on writing the transformation code
> - students need to write Scala code
> - we provide a dataset and a template (Scala class) with function signatures and detailed
description per application.
> e.g.: def assignment_one(input: DataStream[Event]): DataStream[(String, Int)] = ???
> - we provide some setup code like parsing of data and setting up the streaming environment
> - assignments need to be auto-graded, based on correct results
> In last years course edition we approached this by a custom Docker container. This container
first compiled the students code, run all the Flink applications against a different dataset
and then verified the output against our solutions. This was turned into a grade and reported
back to the student. Although this was a working approach, I think we can do better.
> I'm wondering if any of you have experience with using Apache Flink in a university course
(or have seen this somewhere) as well as assessing Flink code.
> Thanks a lot!
> Kind regards,
> Wouter Zorgdrager

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