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https://issues.apache.org/jira/browse/SPARK-33635?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17246643#comment-17246643
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Gabor Somogyi commented on SPARK-33635:
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{quote}I no longer believe this is a true regression in performance, I now 
think that 2.4.5 was "cheating".
{quote}
If you mean by cheating Spark uses one consumer from multiple threads then the 
answer is no. Kafka consumer is strictly forbidden to use from multiple threads.
 If such thing happens then Kafka realizes it and exception will be throws 
which will stop the query immediately.

> Performance regression in Kafka read
> ------------------------------------
>
>                 Key: SPARK-33635
>                 URL: https://issues.apache.org/jira/browse/SPARK-33635
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    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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