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Posted to issues@spark.apache.org by "Calvin Pietersen (Jira)" <ji...@apache.org> on 2021/01/11 00:04:00 UTC
[jira] [Updated] (SPARK-34063) Major slowdown in spark streaming
after 6 days
[ https://issues.apache.org/jira/browse/SPARK-34063?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Calvin Pietersen updated SPARK-34063:
-------------------------------------
Description:
Spark streaming application runs at 60s batch intervals.
The application runs fine processing batches around 40s. After ~8600 batches (around 6 days), the application all of a sudden hits a wall and processing time jumps to 2-2.4 minutes, and eventually dies with exit code 137. This happens consistently every 6 days, regardless of data.
Looking at the application logs, it seems like when the issue begins, tasks are being completed by executors, however the driver is taking a while to acknowledge. I have taken numerous memory dumps of the driver (before it hits the 6 day wall) using *jcmd* and can see the *org.apache.spark.scheduler.AsyncEventQueue* is growing in size despite the fact that the application is able to keep up with batches. I have yet to take a snapshot of the application in the broken stage.
was:
Spark streaming application runs at 60s batch intervals.
The application runs fine processing batches around 40s. After ~8600 batches (around 6 days), the application all of a sudden hits a wall and processing time jumps to 2-2.4 minutes, and eventually dies with exit code 137. This happens consistently every 6 days, regardless of data.
Looking at the application logs, it seems like when the issue begins, tasks are being completed by executors, however the driver is taking a while to acknowledge. I have taken numerous memory dumps of the driver (before it hits the 6 day wall) using *jcmd* and can see the *org.apache.spark.scheduler.AsyncEventQueue* is growing in size despite the fact that the application is able to keep up with batches. I have yet to take a snapshot of the application in the broken stage.
> Major slowdown in spark streaming after 6 days
> ----------------------------------------------
>
> Key: SPARK-34063
> URL: https://issues.apache.org/jira/browse/SPARK-34063
> Project: Spark
> Issue Type: Bug
> Components: Scheduler, Spark Core
> Affects Versions: 3.0.0
> Reporter: Calvin Pietersen
> Priority: Major
> Attachments: normal-job, slow-job
>
>
> Spark streaming application runs at 60s batch intervals.
> The application runs fine processing batches around 40s. After ~8600 batches (around 6 days), the application all of a sudden hits a wall and processing time jumps to 2-2.4 minutes, and eventually dies with exit code 137. This happens consistently every 6 days, regardless of data.
> Looking at the application logs, it seems like when the issue begins, tasks are being completed by executors, however the driver is taking a while to acknowledge. I have taken numerous memory dumps of the driver (before it hits the 6 day wall) using *jcmd* and can see the *org.apache.spark.scheduler.AsyncEventQueue* is growing in size despite the fact that the application is able to keep up with batches. I have yet to take a snapshot of the application in the broken stage.
>
>
>
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