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From "tzachi (JIRA)" <j...@apache.org>
Subject [jira] [Comment Edited] (LOG4J2-1080) Drop events when the RingBuffer is full
Date Mon, 27 Jul 2015 22:21:04 GMT

    [ https://issues.apache.org/jira/browse/LOG4J2-1080?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14643510#comment-14643510

tzachi edited comment on LOG4J2-1080 at 7/27/15 10:20 PM:

Hey, I just wonder if there is anything else needed for this ticket? I can add documentation
but first I want to get approval for the patch concept. Thanks!

was (Author: tezra):
Hey, I just wonder if there is anything else needed for this ticket? Thanks!

> 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
>         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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