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https://issues.apache.org/jira/browse/LOG4J2-1080?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15065760#comment-15065760
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Remko Popma commented on LOG4J2-1080:
-------------------------------------
Question regarding AsyncAppender:
AsyncAppender has a {{blocking}} mode (true by default), in which the appender
will wait until there are free slots in the queue. If false, the event will be
written to the error appender if the queue is full.
For this Jira I'm adding an option to discard INFO/DEBUG/TRACE events if the
queue is 80+% full.
Should this option be applied only when blocking is true or also when blocking
is false?
Thoughts?
> Drop events when the RingBuffer is full
> ---------------------------------------
>
> Key: LOG4J2-1080
> URL: https://issues.apache.org/jira/browse/LOG4J2-1080
> Project: Log4j 2
> Issue Type: New Feature
> Reporter: tzachi
> Assignee: Remko Popma
> Fix For: 2.5.1
>
> Attachments: AsyncLogger.dropEvents.patch
>
>
> I am running into performance issue with an appender, in a certain scenario
> (attached at the bottom), that causes RingBuffer to reach its full capacity.
> When that happens I can see that my app throughput drops significantly.
> I think it will be really useful to be able to configure the RingBuffer
> handler to be able to drop events whenever the buffer reaches its capacity,
> instead of what seems currently as blocking, as I don't want the logging to
> affect the main application.
> ---------------------------------------------------------------------
> Here is the scenario that led me to this request:
> I am currently testing the log4j-flume-ng appender and running into some
> issues. It seems like whenever log4j appender fails to log an event it causes
> the disruptor ring buffer to get full which slows down the whole system.
> My setup looks more or less like that:
> process 1: Java app which uses log4j2 (with flume-ng’s Avro appender)
> process 2: local flume-ng which gets the logs on using an Avro source and
> process them
> Here are my findings:
> When Flume (process 2) is up and running, everything actually looks really
> good. The ring buffer capacity is almost always full and there are no
> performance issues. The problem starts when I shut down process 2 - I am
> trying to simulate a case in which this process crashes, as I do not want it
> to effect process 1. As soon as I shut down flume I start getting exceptions
> produced by log4j telling me they cannot append the log - so far it makes
> sense. The thing is, that at the same time I can see that the ring buffer
> starts to fill up. As long as it’s not totally full process’s 1 throughput
> stays the same. The problem gets serious as soon as the buffer reaches full
> capacity. When that happens the throughput drops in 80% and it does not seem
> to recover from this state. But, as soon as I restart process 2, things get
> back to normal pretty quick - the buffer gets emptied, and the throughput
> climbs back to what it was before. I assume that from some reason a fail to
> append makes the RingBuffer consumer thread significantly slower.
> Besides checking why the flume appender preform slower when an exception is
> thrown, I wish I could just discard the log events when the buffer gets full.
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