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From Ceki Gülcü <c...@qos.ch>
Subject Re: Measuring logging performance impact (including string concatenation)
Date Tue, 23 Feb 2010 17:16:22 GMT
Hello James,

There is no perfect way to measure the overhead of parameter
constructions, but 200 nanosecond is a reasonable lower bound. So, if
you call a disabled logger 1'000'000 times you will see an overhead of
at least 200 milliseconds. Nothing to call home about. However, the
toString() methods of certain objects can be very costly so the impact
of parameter construction can be much higher than 200 nanos.

BTW, SLF4J handles this use case very nicely. Note that slf4-api.jar
is 23K in size and slf4j-jdk14.jar (which logs to java.util.logging)
is only 8K. If you were using the SLF4J API, you could instruct SLF4J
to delegate to java.util.logging via slf4j-jdk14.jar, solving the
overhead problem at the cost of additional 31K to download during
applet start up.

Moreover, if you were using SLF4J throughout your application, the
rest of your application could share code with the applet as both
the application and the applet would be using the same logging API. Your
application of course could continue to delegate logging to log4j as
you do currently.


http://logback.qos.ch: The reliable, generic, fast and flexible logging framework.

On 23/02/2010 5:53 PM, James A. N. Stauffer wrote:
> Our applications have extensive use of logging (most commons-logging
> over log4j, and j.u.l).  We use j.u.l for code that runs in an applet
> so we don't incur the cost of an extra jar download.  Since we don't
> have access to message formats, we incur the cost the log message
> string concatenation even when the level is turned off.  We could wrap
> every log call in a level check but that makes the code more messy.
> Is there a good way to measure the performance impact (i.e. % of CPU
> time) used for logging statements (include the string concatenation
> for the log message)?

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