tzachi created LOG4J2-1080:
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Summary: 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
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.
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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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