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https://issues.apache.org/jira/browse/SPARK-33635?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17246430#comment-17246430
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David Wyles commented on SPARK-33635:
-------------------------------------
Having performed my tests I can conclude that the kafka client versions behave
reasonable identically.
I ran my test on a local partition, a single thread reading just one partition
of the same data.
But the curious thing was that It would max out around 660,000 rows per second
which is much more in line with the row rate provided by Spark 3.0.0/1 (of
632,000 per second)
So that leads to believe that 2.4.5 was not single threaded (per partition), as
the time and numbers I measured before were from the driver - so they are
correct.
Not once on any of the reads directly from kafka on this test system did I get
anywhere near the 1.1 mil rows/second.
I no longer believe this is a true regression in performance, I now think that
2.4.5 was "cheating".
Should you wish to close this as not a bug, then I'm happy for that to happen -
but I would like your thoughts on how 2.4.5 was cheating.
> Performance regression in Kafka read
> ------------------------------------
>
> Key: SPARK-33635
> URL: https://issues.apache.org/jira/browse/SPARK-33635
> Project: Spark
> Issue Type: Bug
> Components: Structured Streaming
> Affects Versions: 3.0.0, 3.0.1
> Environment: A simple 5 node system. A simple data row of csv data in
> kafka, evenly distributed between the partitions.
> Open JDK 1.8.0.252
> Spark in stand alone - 5 nodes, 10 workers (2 worker per node, each locked to
> a distinct NUMA group)
> kafka (v 2.3.1) cluster - 5 nodes (1 broker per node).
> Centos 7.7.1908
> 1 topic, 10 partiions, 1 hour queue life
> (this is just one of clusters we have, I have tested on all of them and
> theyall exhibit the same performance degredation)
> Reporter: David Wyles
> Priority: Major
>
> I have observed a slowdown in the reading of data from kafka on all of our
> systems when migrating from spark 2.4.5 to Spark 3.0.0 (and Spark 3.0.1)
> I have created a sample project to isolate the problem as much as possible,
> with just a read all data from a kafka topic (see
> [https://github.com/codegorillauk/spark-kafka-read] ).
> With 2.4.5, across multiple runs,
> I get a stable read rate of 1,120,000 (1.12 mill) rows per second
> With 3.0.0 or 3.0.1, across multiple runs,
> I get a stable read rate of 632,000 (0.632 mil) rows per second
> The represents a *44% loss in performance*. Which is, a lot.
> I have been working though the spark-sql-kafka-0-10 code base, but change for
> spark 3 have been ongoing for over a year and its difficult to pin point an
> exact change or reason for the degradation.
> I am happy to help fix this problem, but will need some assitance as I am
> unfamiliar with the spark-sql-kafka-0-10 project.
>
> A sample of the data my test reads (note: its not parsing csv - this is just
> test data)
>
> 1606921800000,001e0610e532,lightsense,tsl250rd,intensity,21853,53.262,acceleration_z,651,ep,290,commit,913,pressure,138,pm1,799,uv_intensity,823,idletime,-372,count,-72,ir_intensity,185,concentration,-61,flags,-532,tx,694.36,ep_heatsink,-556.92,acceleration_x,-221.40,fw,910.53,sample_flow_rate,-959.60,uptime,-515.15,pm10,-768.03,powersupply,214.72,magnetic_field_y,-616.04,alphasense,606.73,AoT_Chicago,053,Racine
> Ave & 18th St Chicago IL,41.857959,-87.65642700000002,AoT Chicago (S)
> [C],2017/12/15 00:00:00,
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