Hi Nathan, thanks for your response.

I hit the Send button and realized I should have looked at the sleep precision.

Anyway, my Linux already had the high precision clocks enabled. 
I fixed my problem by using a ScheduledExecutorService instead of Thread.sleep. Now I am getting 1ms precision!



On Feb 24, 2015, at 4:13 PM, Nathan Leung <ncleung@gmail.com> wrote:

firstly, sleep is imprecise, if you say "sleep(1)" this means "sleep for at least 1 millisecond".

next, I would check to see if high resolution timers are supported and enabled on your system (see for example http://linux.die.net/man/7/time).

If you are running Linux and don't have high resolution timers enabled your sleep resolution is limited to the duration of a "jiffy", which on most modern systems is 1ms.  This means that if you sleep(1), it will on average sleep 1.5ms, which yields just over 660 tuples / s, roughly matching your observation.

On Tue, Feb 24, 2015 at 3:37 PM, Wilson Akio Higashino <virsox@gmail.com> wrote:
Dear all,

I have a simple topology composed of a spout followed by three bolts, and I want to measure the processing latency as a function of the tuple incoming rate.

To execute this test, I created a Spout that from time to time "create" a new tuple and emit it to the topology. In order to control the generation rate, I simply sleep for a configurable period. The code follows the general idea present in some of the "storm-starter" topologies:

   public void nextTuple() {

        // Create test tuple and emit

For "slow" rates the spout can generate tuples with good accuracy. For example, if I sleep for 10 milliseconds, the rate should be around 100 tuples/second - and I get around 92 tuples/second.
However, if I increase the rate, the error becomes very large (for example, for 1 millisecond sleep, I get only 650 tuples/second instead of the theoretical 1000 tuples/second).

In addition:

- Everything is running on a single Worker.

- Generally, there are no tuples waiting on any of the receiving / sending queues.

- The code generating the tuple is not a bottleneck, because when I remove the Utils.sleep line I get a generation rate of over 10,000 tuples / second. This result also shows me that the topology can handle larger rates without problems.

I understand that the way I am programming the "nextTuple" method only guarantees an upper bound on the generation rate, but I would like to have better control over it.

My questions are:

- Is there anything on Storm internals that justify this behaviour? I thought it could be related to the "SpoutWaitStrategy" associated with the Spout, but I switched to other strategies and didn't have any effect.

- Any ideas / thoughts on how I could better control the tuple generation rate other than using this sleep / awake pattern? 

I appreciate your help.