Folks,
I've been trying to tackle the measurement of an irregular statistic on an
embedded platform: embedded JVM garbage collection. During any given "interval"
for collectd, I may have no GC activity or I might have a dozen instances where
the JVM performed garbage collection. I have a file wherein the GC numbers are
stored (time of occurrence, JVM heap before, JVM heap after, time required to
garbage-collect), so I can write a read plugin to simply read the file. It
should be easy enough to keep track of the last time it ran, so I can know
exactly when/where to index in that file so I can start the file read at the
right point (and read to the end). But the fact that I may have multiple values
in any one interval is throwing me off.
So if I have a set of N data points (including timestamp), can I simply iterate
through a list, calling plugin_dispatch_values( &vl ) where I've not only set
up the "standard" vl data elements but also the vl.time element also, with the
appropriate timestamp?
E.G. (very psedocode-ish) :
// Iterate through the N values for heap during this interval
for iter=0; iter<N; iter++
{
gcdata = dataArray[iter];
vl.values = gcdata.heap;
vl.time = gcdata.timestamp;
sstrncpy( ... host, plugin, type, type_instance, etc ...);
plugin_dispatch_values(&vl);
}
Other obvious alternatives would be (1) to write the plugin so it would average
all values of interest and just report ONE set of data (and perhaps a metric
for the number of GCs that occurred during that interval); or (2) to only
report the most RECENT set of data, or (3) to have the read plugin interval
much shorter than how fast I expect the GC to run. But if it's possible, I'd
rather get all of the instances recorded. Have any folks had to deal with such
irregular values before?
Thanks,
Dave
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