YARN-9797. LeafQueue#activateApplications should use resourceCalculator#fitsIn. Contributed by Bilwa S T.
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@ -832,8 +832,7 @@ public class LeafQueue extends AbstractCSQueue {
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+ " AM node-partition name " + partitionName);
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}
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if (!Resources.lessThanOrEqual(resourceCalculator, lastClusterResource,
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amIfStarted, amLimit)) {
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if (!resourceCalculator.fitsIn(amIfStarted, amLimit)) {
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if (getNumActiveApplications() < 1 || (Resources.lessThanOrEqual(
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resourceCalculator, lastClusterResource,
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queueUsage.getAMUsed(partitionName), Resources.none()))) {
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@ -865,8 +864,7 @@ public class LeafQueue extends AbstractCSQueue {
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application.getAMResource(partitionName),
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user.getConsumedAMResources(partitionName));
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if (!Resources.lessThanOrEqual(resourceCalculator, lastClusterResource,
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userAmIfStarted, userAMLimit)) {
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if (!resourceCalculator.fitsIn(userAmIfStarted, userAMLimit)) {
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if (getNumActiveApplications() < 1 || (Resources.lessThanOrEqual(
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resourceCalculator, lastClusterResource,
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queueUsage.getAMUsed(partitionName), Resources.none()))) {
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@ -39,6 +39,7 @@ import org.apache.hadoop.yarn.api.records.ContainerId;
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import org.apache.hadoop.yarn.api.records.NodeId;
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import org.apache.hadoop.yarn.api.records.Priority;
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import org.apache.hadoop.yarn.api.records.Resource;
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import org.apache.hadoop.yarn.api.records.ResourceInformation;
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import org.apache.hadoop.yarn.api.records.ResourceRequest;
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import org.apache.hadoop.yarn.conf.YarnConfiguration;
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import org.apache.hadoop.yarn.factories.RecordFactory;
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@ -49,6 +50,7 @@ import org.apache.hadoop.yarn.server.resourcemanager.MockRM;
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import org.apache.hadoop.yarn.server.resourcemanager.RMContext;
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import org.apache.hadoop.yarn.server.resourcemanager.nodelabels.NullRMNodeLabelsManager;
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import org.apache.hadoop.yarn.server.resourcemanager.nodelabels.RMNodeLabelsManager;
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import org.apache.hadoop.yarn.server.resourcemanager.resource.TestResourceProfiles;
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import org.apache.hadoop.yarn.server.resourcemanager.rmapp.RMApp;
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import org.apache.hadoop.yarn.server.resourcemanager.rmapp.attempt.RMAppAttempt;
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import org.apache.hadoop.yarn.server.resourcemanager.scheduler.ResourceLimits;
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@ -59,7 +61,9 @@ import org.apache.hadoop.yarn.server.resourcemanager.scheduler.capacity.preempti
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import org.apache.hadoop.yarn.server.resourcemanager.scheduler.common.fica.FiCaSchedulerApp;
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import org.apache.hadoop.yarn.server.resourcemanager.scheduler.common.fica.FiCaSchedulerNode;
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import org.apache.hadoop.yarn.util.resource.DefaultResourceCalculator;
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import org.apache.hadoop.yarn.util.resource.DominantResourceCalculator;
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import org.apache.hadoop.yarn.util.resource.ResourceCalculator;
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import org.apache.hadoop.yarn.util.resource.ResourceUtils;
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import org.apache.hadoop.yarn.util.resource.Resources;
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import org.junit.Assert;
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import org.junit.Before;
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@ -750,4 +754,85 @@ public class TestApplicationLimitsByPartition {
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}
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/**
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* {@link LeafQueue#activateApplications()} should validate values of all
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* resourceTypes before activating application.
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*
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* @throws Exception
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*/
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@Test
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public void testAMLimitByAllResources() throws Exception {
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CapacitySchedulerConfiguration csconf =
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new CapacitySchedulerConfiguration();
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csconf.setResourceComparator(DominantResourceCalculator.class);
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String queueName = "a1";
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csconf.setQueues(CapacitySchedulerConfiguration.ROOT,
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new String[] {queueName});
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csconf.setCapacity("root." + queueName, 100);
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ResourceInformation res0 = ResourceInformation.newInstance("memory-mb",
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ResourceInformation.MEMORY_MB.getUnits(), GB, Long.MAX_VALUE);
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ResourceInformation res1 = ResourceInformation.newInstance("vcores",
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ResourceInformation.VCORES.getUnits(), 1, Integer.MAX_VALUE);
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ResourceInformation res2 = ResourceInformation.newInstance("gpu",
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ResourceInformation.GPUS.getUnits(), 0, Integer.MAX_VALUE);
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Map<String, ResourceInformation> riMap = new HashMap<>();
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riMap.put(ResourceInformation.MEMORY_URI, res0);
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riMap.put(ResourceInformation.VCORES_URI, res1);
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riMap.put(ResourceInformation.GPU_URI, res2);
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ResourceUtils.initializeResourcesFromResourceInformationMap(riMap);
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YarnConfiguration config = new YarnConfiguration(csconf);
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config.setClass(YarnConfiguration.RM_SCHEDULER, CapacityScheduler.class,
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ResourceScheduler.class);
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config.setBoolean(TestResourceProfiles.TEST_CONF_RESET_RESOURCE_TYPES,
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false);
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MockRM rm = new MockRM(config);
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rm.start();
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Map<String, Long> res = new HashMap<>();
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res.put("gpu", 0L);
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Resource clusterResource = Resource.newInstance(16 * GB, 64, res);
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// Cluster Resource - 16GB, 64vcores
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// AMLimit 16384 x .1 mb , 64 x .1 vcore
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// Effective AM limit after normalized to minimum resource 2048,7
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rm.registerNode("127.0.0.1:1234", clusterResource);
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String userName = "user_0";
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ResourceScheduler scheduler = rm.getRMContext().getScheduler();
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LeafQueue queueA = (LeafQueue) ((CapacityScheduler) scheduler)
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.getQueue(queueName);
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Resource amResource = Resource.newInstance(GB, 1);
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rm.submitApp(amResource, "app-1", userName, null, queueName);
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rm.submitApp(amResource, "app-2", userName, null, queueName);
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// app-3 should not be activated as amLimit will be reached
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// for memory
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rm.submitApp(amResource, "app-3", userName, null, queueName);
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Assert.assertEquals("PendingApplications should be 1", 1,
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queueA.getNumPendingApplications());
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Assert.assertEquals("Active applications should be 2", 2,
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queueA.getNumActiveApplications());
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// AMLimit is 2048,7
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Assert.assertEquals(2048,
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queueA.getQueueResourceUsage().getAMLimit().getMemorySize());
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Assert.assertEquals(7,
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queueA.getQueueResourceUsage().getAMLimit().getVirtualCores());
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// Used AM Resource is 2048,2
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Assert.assertEquals(2048,
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queueA.getQueueResourceUsage().getAMUsed().getMemorySize());
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Assert.assertEquals(2,
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queueA.getQueueResourceUsage().getAMUsed().getVirtualCores());
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rm.close();
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}
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}
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