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From Vasiliki Kalavri <vasilikikala...@gmail.com>
Subject Re: Creating a representative streaming workload
Date Mon, 16 Nov 2015 19:06:52 GMT
Hi,

thanks Nick and Ovidiu for the links!

Just to clarify, we're not looking into creating a generic streaming
benchmark. We have quite limited time and resources for this project. What
we want is to decide on a set of 3-4 _common_ streaming applications. To
give you an idea, for the batch workload, we will pick something like a
grep, one relational application, a graph algorithm, and an ML algorithm.

Cheers,
-Vasia.

On 16 November 2015 at 19:25, Ovidiu-Cristian MARCU <
ovidiu-cristian.marcu@inria.fr> wrote:

> Regarding Flink vs Spark / Storm you can check here:
> http://www.sparkbigdata.com/102-spark-blog-slim-baltagi/14-results-of-a-benchmark-between-apache-flink-and-apache-spark
>
> Best regards,
> Ovidiu
>
> On 16 Nov 2015, at 15:21, Vasiliki Kalavri <vasilikikalavri@gmail.com>
> wrote:
>
> Hello squirrels,
>
> with some colleagues and students here at KTH, we have started 2 projects
> to evaluate (1) performance and (2) behavior in the presence of memory
> interference in cloud environments, for Flink and other systems. We want to
> provide our students with a workload of representative applications for
> testing.
>
> While for batch applications, it is quite clear to us what classes of
> applications are widely used and how to create a workload of different
> types of applications, we are not quite sure about the streaming workload.
>
> That's why, we'd like your opinions! If you're using Flink streaming in
> your company or your project, we'd love your input even more :-)
>
> What kind of applications would you consider as "representative" of a
> streaming workload? Have you run any experiments to evaluate Flink versus
> Spark, Storm etc.? If yes, would you mind sharing your code with us?
>
> We will of course be happy to share our results with everyone after we
> have completed our study.
>
> Thanks a lot!
> -Vasia.
>
>
>

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