Presumably you'd want to mirror the stream to all nodes for when the primary node changes?
On Wed, 5 Jun 2019, 13:46 Bryan Bende, <[email protected]> wrote: > The processor is started on all nodes, but onTrigger method is only > executed on the primary node. > > This is something we've discussed trying to improve before, but the > real question is why are you sending data to the other nodes if you > don't expect the processor to execute there? > > On Wed, Jun 5, 2019 at 7:04 AM Erik-Jan <[email protected]> wrote: > > > > I figured it out after further testing. The processor runs on all nodes, > despite the explicit "run on primary node only" option that I selected. But > only on the primary node the queue is processed. On the other nodes the > queue gets filled until the max is reached after which the error message > starts appearing. What I missed before is that the message is coming from > the other, non-primary nodes. > > I'm not sure if this is intended behavior or if it is a bug though! For > me it's a bug since I really want this processor to run on the primary only. > > > > Op di 4 jun. 2019 16:34 schreef Erik-Jan <[email protected]>: > >> > >> Hi Bryan, > >> > >> Yes I have considerably increased the numbers in the controller > settings. > >> I don't mind getting my hands dirty, increasing the timeout is worth a > try. > >> > >> The errors seems to appear after quite a while. Usually I see these > messages the next morning so testing and experimenting with this error > takes a lot of time. > >> > >> Today I've been trying to reproduce this on a virtual machine with the > same OS, Nifi and Java versions but to no avail. The difference is that > this VM is not a cluster, has limited memory and cpu and still is able to > handle much more UDP data with the error appearing only a few times so far > after hours of running. It leads me to thinking there must be something in > the configuration of the cluster thats causing this. I will also try a > vanilla Nifi install on one of the nodes without clustering to see if my > configuration and cluster setup is somehow the cause. > >> > >> Op di 4 jun. 2019 om 16:14 schreef Bryan Bende <[email protected]>: > >>> > >>> Hi Erik, > >>> > >>> It sounds like you have tried most of the common tuning options that > >>> can be done. I would have expected batching + increasing concurrent > >>> tasks from 1 to 3-5 to be the biggest improvement. > >>> > >>> Have you increased the number of threads in your overall thread pool > >>> according to your hardware? (from the top right menu controller > >>> settings) > >>> > >>> I would be curious what happens if you did some tests increasing the > >>> timeout where it attempts to place the message in the queue from 100ms > >>> to 200ms and then maybe 500ms if it still happens. > >>> > >>> I know this requires a code change since that timeout is hard-coded, > >>> but it sounds like you already went down that path with trying a > >>> different queue :) > >>> > >>> -Bryan > >>> > >>> On Tue, Jun 4, 2019 at 4:28 AM Erik-Jan <[email protected]> wrote: > >>> > > >>> > Hi, > >>> > > >>> > I'm experimenting with a locally installed 3 node nifi cluster. This > cluster receives UDP packets on the primary node. > >>> > These nodes are pretty powerful, have a good network connection, > have lots of memory and SSD disks. I gave nifi 24G of java heap (xms and > xmx). > >>> > > >>> > I have configured a ListenUDP processor that listens on a UDP port > and it receives somewhere between 20000 to 50000 packets per 5 minutes. > It's "Max size of message queue" is large enough (1M), I gave it 5 > concurrent tasks, it's running on the primary node only. > >>> > > >>> > The problem: after running for a while, I get the following error: > "internal queue at maximum capacity, could not queue event." > >>> > > >>> > I have reviewed the source code and understand when this happens. It > happens when the processor tries to store an event in a java > LinkedBlockingQueue and that queue reached its maximum capacity. The > offer() method has a 100ms timeout in which it waits for space to free up > and then it fails and the event gets dropped. In the logs I see exactly 10 > of these error messages per second (10 x 100ms is 1 second). Despite these > errors, I still get a very good rate of events that get through to the next > processors. Actually, it seems pretty much all of the other events get > through since the message rate in ListenUDP and the followup processor are > very much alike. The followup processors can easily handle the load and > there are no full queues, congestions or anything like that. > >>> > > >>> > What I have tried so far: > >>> > > >>> > Increasing the "Max Size of Message Queue" setting helps, but only > delays the errors. They eventually return. > >>> > > >>> > Increasing heap space is a suggestion I read from a past post: I > think 24G is more than enough actually? Perhaps even too much? > >>> > > >>> > Increasing parallelism: concurrent tasks set to 5 or 10 does not > help. > >>> > > >>> > I modified the code to use an ArrayBlockingQueue instead of the > LinkedBlockingQueue, thinking it was some kind of garbage collection. This > didn't help. > >>> > > >>> > I increased "Receive Buffer Size", "Max Size of Socket Buffer" but > to no avail. > >>> > > >>> > I tried batching. This helps a bit, like increasing the "Max Size of > Message Queue" it only seems to delay the eventual error messages though. > >>> > > >>> > I reproduced this on my local workstation. I installed nifi, did no > OS tuning at all, set the heap size to 4GB. I generate 1.3M UDP packets per > 5 minutes (the max I can reach with a simple python script). With "Max Size > of Message Queue" set to only 100, soon the error appears. In the ListenUDP > processor I see 1.34M events out, on the followup processor I see 1.34M > events incoming. The error is not as frequent as on the cluster though, > only a few every couple of minutes while the data rate is much higher and > the queue much smaller. I'm a bit desperate and hope anyone can help me > out. Why am I getting this error on a relatively quiet cluster with not > that much load? > >>> > > >>> > Best regards, > >>> > Erik-Jan van Baaren >
