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Posted to issues@spark.apache.org by "David Wyles (Jira)" <ji...@apache.org> on 2020/12/02 17:03:00 UTC
[jira] [Updated] (SPARK-33635) Performance regression in Kafka read
[ https://issues.apache.org/jira/browse/SPARK-33635?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
David Wyles updated SPARK-33635:
--------------------------------
Description:
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,
was:
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 (1.2 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,
> 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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