Hi, Thanks.
I see that the latency stabilizes over time. I ran word count topology with 3 worker nodes, latency stabilizes after 2 hours or so. Is there any other way I can measure the end to end latency of a topology other than "complete latency" of Storm UI? Best, Preethini On Mon, Jul 17, 2017 at 5:41 AM, Ambud Sharma <[email protected]> wrote: > If I may add, it is also explained by the potential surge of tuples when > topology starts which will eventually reach an equilibrium which the normal > latency of your topology components. > > On Jul 14, 2017 4:29 AM, "preethini v" <[email protected]> wrote: > >> Hi, >> >> I am running WordCountTopology with 3 worker nodes. The parallelism of >> spout, split and count is 5, 8 and 12 respectively. I have enabled acking >> to measure the complete latency of the topology. >> >> I am considering complete latency as a measure of end-to-end latency. >> >> The Complete latency is the time a tuple is emitted by a Spout until >> Spout.ack() is called. Thus, it is the time from tuple being emitted, >> the tuple processing time, the time it spends in the internal input/output >> buffers and until the ack for the tuple is received by the Spout. >> >> The stats from storm UI show that the complete latency for a topology >> keeps decreasing with time. >> >> 1. Is this normal? >> 2. If yes, What explains the continuous decreasing complete latency >> value? >> 3. Is complete latency a good measure of end-to-end latency of a topology? >> >> Thanks, >> Preethini >> >
