gt;
>
> --------------
> From:Felipe Gutierrez
> Send Time:2020 Mar. 7 (Sat.) 18:49
> To:Arvid Heise
> Cc:Zhijiang ; user
> Subject:Re: Backpressure and 99th percentile latency
>
> Hi,
> I implemented my own histogra
Time:2020 Mar. 7 (Sat.) 18:49
To:Arvid Heise
Cc:Zhijiang ; user
Subject:Re: Backpressure and 99th percentile latency
Hi,
I implemented my own histogram metric on my operator to measure the
latency. The latency is following the throughput at the same pace now.
The figures are attached.
Best,
Felipe
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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
Hi,
I am a bit confused about the topic of tracking latency in Flink [1]. It
says if I use the latency track I am measuring the Flink’s network stack
but application code latencies also can influence it. For instance, if I am
using the metrics.latency.granularity: operator (default) and
setLatency
