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https://issues.apache.org/jira/browse/OOZIE-3181?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Oleksandr Kalinin updated OOZIE-3181:
-------------------------------------
Description:
User submitting high frequency LAST_ONLY coordinator job for past time
(intentionally or by mistake) triggers enormous materialization loop for that
job and potentially OOM condition even with high heap settings.
Simplest example is:
coordStarts=2017-02-12T09:00Z
coordEnds=2019-02-12T09:00Z
coordFrequency=*/1 * * * *
<execution>LAST_ONLY</execution>
Since throttling parameters are ignored on LAST_ONLY past actions, this
triggers non throttled materialization of more than 500K actions lying in the
past which causes severe memory pressure and eventual GC overhead lockout.
At the same time by definition all past actions will be skipped anyway, thus it
seems that the only value in materializing them is ability to view SKIPPED
status later. Is it really worth the risk?
Note : additional severity of this problem is that it's not trivial to recover
it on ZK-coordinated clusters. Write lock will persist which will prevent kill
command from taking desired effect, and that lock will persist also after
restart. To recover, write lock has to be manually removed.
Looking at materialization loop code, I believe there is potential for
algorithm improvement to prevent this issue.
was:
User submitting high frequency LAST_ONLY coordinator job for past time
(intentionally or by mistake) triggers enormous materialization loop for that
job and potentially OOM condition even with high heap settings.
Simplest example is:
coordStarts=2017-02-12T09:00Z
coordEnds=2019-02-12T09:00Z
coordFrequency=*/1 * * * *
<execution>LAST_ONLY</execution>
Since throttling parameters are ignored on LAST_ONLY jobs, this triggers non
throttled materialization of more than 500K actions lying in the past which
causes severe memory pressure and eventual GC overhead lockout.
At the same time by definition all past actions will be skipped anyway, thus it
seems that the only value in materializing them is ability to view SKIPPED
status later. Is it really worth the risk?
Note : additional severity of this problem is that it's not trivial to recover
it on ZK-coordinated clusters. Write lock will persist which will prevent kill
command from taking desired effect, and that lock will persist also after
restart. To recover, write lock has to be manually removed.
Looking at materialization loop code, I believe there is potential for
algorithm improvement to prevent this issue.
> High frequency LAST_ONLY coord. job with many past time actions kills Oozie
> server
> ----------------------------------------------------------------------------------
>
> Key: OOZIE-3181
> URL: https://issues.apache.org/jira/browse/OOZIE-3181
> Project: Oozie
> Issue Type: Bug
> Affects Versions: 4.3.0
> Reporter: Oleksandr Kalinin
> Priority: Major
>
> User submitting high frequency LAST_ONLY coordinator job for past time
> (intentionally or by mistake) triggers enormous materialization loop for that
> job and potentially OOM condition even with high heap settings.
> Simplest example is:
> coordStarts=2017-02-12T09:00Z
> coordEnds=2019-02-12T09:00Z
> coordFrequency=*/1 * * * *
> <execution>LAST_ONLY</execution>
> Since throttling parameters are ignored on LAST_ONLY past actions, this
> triggers non throttled materialization of more than 500K actions lying in the
> past which causes severe memory pressure and eventual GC overhead lockout.
> At the same time by definition all past actions will be skipped anyway, thus
> it seems that the only value in materializing them is ability to view SKIPPED
> status later. Is it really worth the risk?
> Note : additional severity of this problem is that it's not trivial to
> recover it on ZK-coordinated clusters. Write lock will persist which will
> prevent kill command from taking desired effect, and that lock will persist
> also after restart. To recover, write lock has to be manually removed.
> Looking at materialization loop code, I believe there is potential for
> algorithm improvement to prevent this issue.
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