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 >
