Scheduler persists its state in the Mesos replicated log regardless of the in-memory engine. If you change the flag and restart scheduler all tasks are going to be re-inserted into MemTaskStore instead of DBTaskStore. No data will be lost.
On Thu, Jun 9, 2016 at 9:55 AM, Shyam Patel <sham.pate...@gmail.com> wrote: > Thanks Maxim, > > If we move to mem task store, restart of aurora would lose the data ? (btw, > I’m running aurora in a container) > > > >> On Jun 9, 2016, at 8:37 AM, Maxim Khutornenko <ma...@apache.org> wrote: >> >> There are plenty of factors that may contribute towards the behavior >> you're observing. Based on the logs though it appears you are using >> DBTaskStore (-use_beta_db_task_store=true)? If so, you may want to >> revert to the default in-mem task store >> (-use_beta_db_task_store=false) as DBTaskStore is known to perform >> subpar on large task counts. This is a known issue and we plan to >> invest into making it faster. >> >> On Thu, Jun 9, 2016 at 6:58 AM, Erb, Stephan >> <stephan....@blue-yonder.com> wrote: >>> I am no expert here, but I would assume that slow task store operations >>> could result from a slow replicated log. Have you tried keeping it on an >>> SSD? >>> (https://github.com/apache/aurora/blob/e89521f1eebd9a5301eb02e2ed6ffebdecd54c9a/docs/operations/configuration.md#-native_log_file_path) >>> >>> FWIW, there was a recent RB by Maxim to reduce Master load unter task >>> reconciliation: https://reviews.apache.org/r/47373/diff/2#index_header >>> ________________________________________ >>> From: Shyam Patel <sham.pate...@gmail.com> >>> Sent: Thursday, June 9, 2016 07:48 >>> To: dev@aurora.apache.org >>> Subject: Re: Aurora performance impact with hourly query runs >>> >>> Hi Bill, >>> >>> Cluster Set up : AWS >>> >>> 1 Mesos , 1 ZK , 1 Aurora instance : 4 CPU, 16G mem >>> >>> Aurora : Xmx 14G >>> >>> 100 nodes agent cluster : 40 CPU, 160G mem each >>> >>> 8000 Jobs, each with 2 instances. So, total ~16K containers >>> >>> >>> Thanks, >>> Sham >>> >>> >>> >>>> On Jun 8, 2016, at 9:18 PM, Bill Farner <wfar...@apache.org> wrote: >>>> >>>> Can you give some insight into the machine specs and JVM options used? >>>> >>>> Also, is it 8000 jobs or tasks? The terms are often mixed up, but will >>>> have a big difference here. >>>> >>>> On Wednesday, June 8, 2016, Shyam Patel <sham.pate...@gmail.com> wrote: >>>> >>>>> Hi, >>>>> >>>>> While running LnP testing, I’m spinning of 8K docker jobs. During the run, >>>>> I ran into issue where TaskStatUpdate and TaskReconciler queries taking >>>>> real long times. During the time, Aurora is pretty much freezing and at a >>>>> point dying. Also, tried the same run w/o the docker jobs and faced the >>>>> same issue. >>>>> >>>>> >>>>> Is there a way to keep the Aurora performance intact during the query runs >>>>> ? >>>>> >>>>> >>>>> >>>>> Here is snipped from log : >>>>> >>>>> >>>>> I0602 00:53:37.527 [TaskStatUpdaterService RUNNING, DbTaskStore:104] Query >>>>> took 1243517 ms: TaskQuery(owner:null, role:null, environment:null, >>>>> jobName:null, taskIds:null, statuses:[STARTING, THROTTLED, RUNNING, >>>>> DRAINING, ASSIGNED, KILLING, RESTARTING, PENDING, PREEMPTING], >>>>> instanceIds:null, slaveHosts:null, jobKeys:null, offset:0, limit:0) >>>>> >>>>> >>>>> I0602 00:56:54.180 [TaskReconciler-0, DbTaskStore:104] Query took 1380169 >>>>> ms: TaskQuery(owner:null, role:null, environment:null, jobName:null, >>>>> taskIds:null, statuses:[STARTING, RUNNING, DRAINING, ASSIGNED, KILLING, >>>>> RESTARTING, PREEMPTING], instanceIds:null, slaveHosts:null, jobKeys:null, >>>>> offset:0, limit:0) >>>>> >>>>> >>>>> >>>>> Appreciate any insights.. >>>>> >>>>> >>>>> Thanks, >>>>> Sham >>>>> >>>>> >
