Thanks much for notifying. Would you know the bug id ? I did refer to the change log of 0.9.3 but could not get hold of the bug id. Incidentally I too have raised a jira and would like to close it giving reference to the previously raised jira. Thanks. On 31 Oct 2014 21:49, "M.Tarkeshwar Rao" <[email protected]> wrote:
> Yes it is the bug which is raised by Denigel.fixed in 9.3.pls use it. Or > use zero mq in place of netty ur problem will be resolved. > On 27 Oct 2014 20:52, "Devang Shah" <[email protected]> wrote: > >> It seems to be a bug in storm unless someone confirms otherwise. >> >> How can I file a bug for storm ? >> On 25 Oct 2014 07:51, "Devang Shah" <[email protected]> wrote: >> >>> You are correct Taylor. Sorry missed to mention all the details. >>> >>> We have topology.spout.max.pending set to 1000 and we have not modified >>> the topology.message.timeouts.secs (default 30 secs). >>> >>> Another observation, >>> When I delibrately bring down the worker (kill -9) and when the worker >>> is brought up on the same port it was running previously on then the storm >>> starts failing all the messages despite it being successfully processed. If >>> the worker is brought up on different supervisor port then the issue >>> doesn't seem to occur. >>> >>> Eg steps, >>> 1. Worker running on 6703 supervisor slot(this worker runs a single >>> spout instance of our topology) and everything runs fine. Messages get >>> procesed and acks back to the message provider. If I let it run in this >>> state it can process any number of messages. >>> 2. I bring down the java process by kill -9 >>> 3. Supervisor brings up the worker on the same slot 6703 and also the >>> spout task instance on it. >>> 4. All the messages get processed fine but the ackers fail all the >>> messages the topology processed after the default 30 secs timeout. This >>> even happens when topology is idle and I push a single message into the >>> topology. So my guess is increasing the timeout will not help (though I >>> have not tried it). >>> 5.If the supervisor brings up the worker on a different slot say 6700 >>> then the issue doen't seem to occur. Probably a bug in storm. >>> >>> Steps to simulate the behaviour, >>> 1. Run topology(spout as single instance and multiple instances of >>> bolts) with multiple workers. >>> 2. Identify the slot on which the single spout instance is running and >>> kill it. >>> 3. See if the supervisor started the worker on the same port. If not >>> then repeat step 2 untill you get supervisor on the same slot as previous >>> one. >>> 4. Pump in a message into the topology. >>> 5. You will see message being processed successfully and also the ackers >>> failing the message. This can be verified by logging statements in the ack >>> and fail methods of the spout. >>> >>> Thanks and Regards, >>> Devang >>> On 25 Oct 2014 04:34, "P. Taylor Goetz" <[email protected]> wrote: >>> >>>> My guess is that you are getting timeouts. >>>> >>>> Do you have topology.spout.max.pending set? If so, what is the value. >>>> Have you overridden topology.message.timeout.secs (default is 30 >>>> seconds)? >>>> >>>> Look in Storm UI for the complete latency of the topology. Is it close >>>> to or greater than topology.message.timeout.secs? >>>> >>>> >>>> -Taylor >>>> >>>> >>>> On Oct 23, 2014, at 12:44 PM, Devang Shah <[email protected]> >>>> wrote: >>>> >>>> Hi Team, >>>> >>>> I am facing an issue with one of our failover tests. Storm fails all >>>> the messages post worker restarts. >>>> >>>> Steps done, >>>> 0. 1 spout, 3 bolts, 5 ackers >>>> 1. Pre-load tibems with 50k messages >>>> 2. Start the topology >>>> 3. Let it run for brief time and the kill the worker where the spout is >>>> executing (spout in our topology is a single instance) >>>> 4. The worker is brought up by the supervisor automatically >>>> >>>> Observation/query, >>>> When spout starts pumping in data again into the topology, storm starts >>>> failing the messages even though they are successfully processed (I have >>>> verified this as our last bolt pushes data to kafka and the incoming/kafka >>>> data njmber matches). I have checked the tuple anchoring and that seems to >>>> be fine as without the worker restarts the topology acks and processes >>>> messages fine. >>>> >>>> Any thing I should check again ? >>>> >>>> >>>>
