Indeed, it is a bit tricky to understand the relation between
floatingBuffersUsage, exclusiveBuffersUsage. I am reading again that
table on (https://flink.apache.org/2019/07/23/flink-network-stack-2.html)
but I guess I can rely on the latency metric that I implemented on my
operator (not the defaul
Thanks for the feedback Felipe!
Regarding with your below concern:
> Although I think it is better to use outPoolUsage and inPoolUsage according
> to [1]. However, in your opinion is it better (faster to see) to use
> inputQueueLength and
> outputQueueLength or outPoolUsage and inPoolUsage to m
Thanks for the clarified answer @Zhijiang, I am gonna monitor
inputQueueLength and outputQueueLength to check some relation with
backpressure. Although I think it is better to use outPoolUsage and
inPoolUsage according to [1].
However, in your opinion is it better (faster to see) to use
inputQueueL
Hi Felipe,
latency under backpressure has to be carefully interpreted. Latency's
semantics actually require that the data source is read in a timely manner;
that is, there is no bottleneck in your pipeline where data is piling up.
Thus, to measure latency in experiments you must ensure that the c
Hi Felipe,
Try to answer your below questions.
> I understand that I am tracking latency every 10 seconds for each physical
> instance operator. Is that right?
Generally right. The latency marker is emitted from source and flow through all
the intermediate operators until sink. This interval c
