If you want the gauge to only represent recent activity then you will
need to use a timer of sorts to reset the gauge after N time (something
larger than the reporter interval) unless it was changed in the meantime
(e.g., by also recording a timestamp within SimpleGauge)
On 1/13/2021 9:33 AM,
This approach has an issue. Even for those periods when there is no
activity, still the latest gauge value is used for calculations and this
generates graphs which are not correct representation of the situation.
On Tue, Jan 12, 2021 at 7:01 PM Manish G
wrote:
> Prometheus provides avg_over_time
Prometheus provides avg_over_time for a range vector. That seems to be
better suited for this usecase.
On Tue, Jan 12, 2021 at 6:53 PM Chesnay Schepler wrote:
> The cumulative time probably isn't that useful to detect changes in the
> behavior of the application.
>
> On 1/12/2021 12:30 PM, Chesn
The cumulative time probably isn't that useful to detect changes in the
behavior of the application.
On 1/12/2021 12:30 PM, Chesnay Schepler wrote:
I mean the difference itself, not cumulative.
On 1/12/2021 12:08 PM, Manish G wrote:
Can you elaborate the second approach more?
Currently I am e
I mean the difference itself, not cumulative.
On 1/12/2021 12:08 PM, Manish G wrote:
Can you elaborate the second approach more?
Currently I am exposing the difference itself. OR do you mean the
cumulative difference?ie I maintain a member variable, say timeSoFar,
and update it with time consu
Can you elaborate the second approach more?
Currently I am exposing the difference itself. OR do you mean the
cumulative difference?ie I maintain a member variable, say timeSoFar, and
update it with time consumed by each method call and then expose it.
Something like this:
timeSoFar += timeConsume
That approach will generally not work for jobs that run for a long time,
because it will be nigh impossible for anomalies to affect the average.
You want to look into exponential moving averages.
Alternatively, just expose the diff as an absolute value and calculate
the average in prometheus.
OK, got it.
So I would need to accumulate the time value over the calls as well as
number of times it is called...and then calculate average(accumulated time/
number of times called) and then set calculated value into gauge as above.
On Tue, Jan 12, 2021 at 4:12 PM Chesnay Schepler wrote:
> A ga
A gauge just returns a value, and Flink exposes it as is. As such you
need to calculate the average over time yourself, taking 2 time
measurements (before and after the processing of each).
On 1/12/2021 11:31 AM, Manish G wrote:
startTime is set at start of function:
long startTime = System.c
startTime is set at start of function:
long startTime = System.currentTimeMillis();
On Tue, Jan 12, 2021 at 3:59 PM Manish G
wrote:
> My code is:
>
> public class SimpleGauge implements Gauge {
>
> private T mValue;
>
> @Override
> public T getValue() {
> return mValue;
>
My code is:
public class SimpleGauge implements Gauge {
private T mValue;
@Override
public T getValue() {
return mValue;
}
public void setValue(T value){
mValue = value;
}
}
And in flatmap function:
float endTime = (System.currentTimeMillis() - startTim
Sure, that might work. Be aware though that time measurements are,
compared to the logic within a function, usually rather expensive and
may impact performance.
On 1/12/2021 10:57 AM, Manish G wrote:
Hi All,
I have implemented a flatmap function and I want to collect metrics
for average time
Hi All,
I have implemented a flatmap function and I want to collect metrics for
average time for this function which I plan to monitor via prometheus.
What would be good approach for it? I have added a gauge to the
method(extending Gauge interface from flink API). Would it work for my
needs?
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