mailing list can't see the picture, you can submit an issue on github
Best Regards --------------- Apache DolphinScheduler PMC Chair LidongDai [email protected] Linkedin: https://www.linkedin.com/in/dailidong Twitter: @WorkflowEasy <https://twitter.com/WorkflowEasy> --------------- On Wed, Nov 24, 2021 at 5:58 PM 王峰 <[email protected]> wrote: > please see this! > > > > > > > At 2021-11-24 13:58:03, "Lidong Dai" <[email protected]> wrote: > >I think you can check the runtime log to find some warn/error message in > >master server and worker server when you received the hung up alarm. > > > > > >Best Regards > > > > > > > >--------------- > >Apache DolphinScheduler PMC Chair > >LidongDai > >[email protected] > >Linkedin: https://www.linkedin.com/in/dailidong > >Twitter: @WorkflowEasy <https://twitter.com/WorkflowEasy> > >--------------- > > > > > >On Mon, Nov 22, 2021 at 10:54 AM 王峰 <[email protected]> wrote: > > > >> 3 nodes, 2master/worker are all on the same machine, there is no downtime, > >> but the server service has hung up the alarm. I guess that insufficient > >> machine resources have affected the operation of the server, and fault > >> tolerance has occurred. The actual task after the error identification is > >> returned It did not stop, and a new task instance was started on the new > >> server. > >> > >> > >> > >> > >> > >> > >> > >> > >> > >> > >> > >> > >> > >> > >> > >> > >> > >> At 2021-11-21 18:41:49, "Lidong Dai" <[email protected]> wrote: > >> >hi, > >> >can you describe the question clearly? the host load means the Master > >> >or the Worker server? is there any server down? > >> > > >> >Best Regards > >> > > >> > > >> > > >> >--------------- > >> >Apache DolphinScheduler PMC Chair > >> >LidongDai > >> >[email protected] > >> >Linkedin: https://www.linkedin.com/in/dailidong > >> >Twitter: @WorkflowEasy > >> >--------------- > >> > > >> >On Sun, Nov 21, 2021 at 3:59 PM 王峰 <[email protected]> wrote: > >> >> > >> >> doplhinscheduler 1.3.3 cluster > >> >> > >> >> > >> >> > >> >> > >> >> There is such a scenario, because the host load is too high, master > >> fault tolerance may occur in the middle, and the same workflow instance is > >> run twice (two tasks are parallel in time), which causes the data to > >> double. > >> > > > > >
