Latest spark yahoo benchmark

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Latest spark yahoo benchmark

nragon
databricks.com/blog/2017/06/06/simple-super-fast-streaming-engine-apache-spark.html

Should flink users be worry about this huge difference?
End of microbatch with 65M benchmark.
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Re: Latest spark yahoo benchmark

Matthias J. Sax-2
From my understanding, the benchmark was done using Structured Streaming
that is still based on micro batching.

There are not throughput numbers for the new "Continuous Processing"
model Spark want to introduce. Only some latency numbers. Also note,
that the new "Continuous Processing" will not give exactly-once
semantics but only at-least-once (at least initially). Thus, there is
some tradeoff to make using "Continuous Processing" once it's available.


-Matthias


On 06/18/2017 03:51 PM, nragon wrote:

> databricks.com/blog/2017/06/06/simple-super-fast-streaming-engine-apache-spark.html
>
> Should flink users be worry about this huge difference?
> End of microbatch with 65M benchmark.
>
>
>
> --
> View this message in context: http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/Latest-spark-yahoo-benchmark-tp13820.html
> Sent from the Apache Flink User Mailing List archive. mailing list archive at Nabble.com.
>


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Re: Latest spark yahoo benchmark

Stephan Ewen
In reply to this post by nragon
@nragon - I think this is a classical "benchmarketing" post. A few thoughts on that 

  - Everyone can tune their system to be best. We ran Flink with even higher throughput than that: https://image.slidesharecdn.com/benchmark-mapr-160407212254/95/extending-the-yahoo-streaming-benchmark-mapr-benchmarks-36-638.jpg?cb=1460064274


  - The benchmark is testing a complete toy case, with a few KBs of state. It says little about most interesting use cases with larger state.


  - The Flink system runs the benchmark with a low latency engine that is also capable of exactly once guarantees. A thing that does not exist the other compared systems.


==> Test your personal application in Flink and Spark, with respect to performance, robustness to load spikes and backpressure, ability to operate/migrate/update, etc. I am pretty sure you will find that Flink has a lot of very powerful unique aspects to it for streaming applications.



On Mon, Jun 19, 2017 at 12:51 AM, nragon <[hidden email]> wrote:
databricks.com/blog/2017/06/06/simple-super-fast-streaming-engine-apache-spark.html

Should flink users be worry about this huge difference?
End of microbatch with 65M benchmark.



--
View this message in context: http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/Latest-spark-yahoo-benchmark-tp13820.html
Sent from the Apache Flink User Mailing List archive. mailing list archive at Nabble.com.

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Re: Latest spark yahoo benchmark

nragon
Yes, indeed.
That's why we choose Flink instead all the others.
This post was just pure curiosity to see spark trying to migrate into a pure streaming engine.
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