Hi Jesmine, thank you for your reply. I'v solve the problem. 1. i have already change the user limit to 2, so each can use all the resource 2. the test label is exclusive.
the problem is caused by the parameter - yarn.resourcemanager. monitor.capacity.preemption.total_preemption_per_round there is only 8vcore each queue and the total_preemption_per_round is 0.1. i guess under that setting each round we can only preempt 8*0.1 <1 vcore, which is less than one container. So the preemption didn't happen. In another experiment, i increased the vcore of each queue to 20 and increased the total_preemption_per_round, the preemption happened as expected. 2017-03-21 11:23 GMT+08:00 Jesmine Zhang <[email protected]>: > We have also tested preemption with Node Labels enabled based on 2.8, and > it works fine for us. > Some questions for you: > 1. For step 4. It doesn't look like your job A was running on test > partition. There is no way a single job can use up to the queue's maximum > capacity of 100% due to the user limit. User limit is the same as queue's > capacity by default setting, which is 50% in your case. So job A could just > consume as many as half of the resources on test Partition. You might want > to check if your job indeed ran on test partition. You can look it at RM UI > application page. You need to specify node label expression explicitly when > submitting a job if the target queue doesn't have default node label > expression configured, otherwise it goes to Default partition. > 2. Is the "test" partition exclusive or non-exclusive? It looks like it is > non-exclusive. > > On Mon, Mar 20, 2017 at 5:28 PM, 胡子千 <[email protected]> wrote: > >> Hi， >> I'm a user of Hadoop YARN and these days i'm testing Node LABEL function >> on YARN 2.8.0 with capacity scheduler. I found that the preemption didn't >> work on queues with label. Here is the details: >> 1. I set *test* label to 2 nodes in our cluster. >> 2. I set *test1*, *test2* queues under root which can only access *test* >> label. And each queue's accessible-node-labels >> .test.capacity=50, accessible-node-labels.test.maximum-capacity=100 >> 3. enable the preemption policy: yarn.resourcemanager. >> scheduler.monitor.enable=true >> 4. submit a spark task (named A) to queue *test1*, which asks for 16 >> executors and will use all resource of *test* partition. >> 5. submit a spark test (named B) to queue *test2*. I assumes that >> because of the under-satisfied of test2 and over-satisfied of test1, the >> preemption will happen and each queue will use 50% resource of partition >> test finally. In fact, the preempting didn't happen and the task B stay in >> accepted state. when task A finished, task b started to run. >> 6. submit same task to different queues in default partition and the >> preemption happens as we expected。 >> >> I found that a patch YARN-2498 about preemption have merged to 2.8.0 and >> i think with this patch YARN supports preemption on labeled partitions. So >> is there any configure need to set or I made some mistake when i use this >> function? Or did I misunderstand patch YARN-2498 and in fact 2.8.0 don't >> support preemption on labeled partitions? >> >> Looking forward your reply, thank you. >> >> -- >> >> Best regards! >> >> Ziqian HU 胡子千 >> Department of Computer Science, School of EECS, Peking University >> >> > > > -- > Ying > > Best Regards > -- Best regards! Ziqian HU 胡子千 Department of Computer Science, School of EECS, Peking University
