你好： 收到的图片无法打开，是否有其他方式进行沟通或者形式的反馈及解答方式
发件人: 王峰 <[email protected]> 答复: "[email protected]" <[email protected]> 日期: 2021年11月24日 星期三 17:58 收件人: "[email protected]" <[email protected]> 主题: Re:Re: Re: The host load is too high, the same workflow appears parallel, and the data doubles please see this! [cid:3c53b3d1$1$17d51613615$Coremail$wangchao_732$163.com] [cid:23fd9693$2$17d5161a084$Coremail$wangchao_732$163.com] 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. >>
