YARN-736. Add a multi-resource fair sharing metric. (sandyr via tucu)

git-svn-id: https://svn.apache.org/repos/asf/hadoop/common/branches/branch-2@1496154 13f79535-47bb-0310-9956-ffa450edef68

hadoop-yarn-project/CHANGES.txt

@@ -22,6 +22,8 @@ Release 2.2.0 - UNRELEASED
 
     YARN-866. Add test for class ResourceWeights. (ywskycn via tucu)
 
+    YARN-736. Add a multi-resource fair sharing metric. (sandyr via tucu)
+
   OPTIMIZATIONS
 
   BUG FIXES

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-common/src/main/java/org/apache/hadoop/yarn/util/resource/Resources.java

@@ -61,6 +61,39 @@ public class Resources {
     
   };
   
+  private static final Resource UNBOUNDED = new Resource() {
+
+    @Override
+    public int getMemory() {
+      return Integer.MAX_VALUE;
+    }
+
+    @Override
+    public void setMemory(int memory) {
+      throw new RuntimeException("NONE cannot be modified!");
+    }
+
+    @Override
+    public int getVirtualCores() {
+      return Integer.MAX_VALUE;
+    }
+
+    @Override
+    public void setVirtualCores(int cores) {
+      throw new RuntimeException("NONE cannot be modified!");
+    }
+
+    @Override
+    public int compareTo(Resource o) {
+      int diff = 0 - o.getMemory();
+      if (diff == 0) {
+        diff = 0 - o.getVirtualCores();
+      }
+      return diff;
+    }
+    
+  };
+
   public static Resource createResource(int memory) {
     return createResource(memory, (memory > 0) ? 1 : 0);
   }
@@ -76,6 +109,10 @@ public class Resources {
     return NONE;
   }
   
+  public static Resource unbounded() {
+    return UNBOUNDED;
+  }
+
   public static Resource clone(Resource res) {
     return createResource(res.getMemory(), res.getVirtualCores());
   }

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-resourcemanager/src/main/java/org/apache/hadoop/yarn/server/resourcemanager/scheduler/fair/AppSchedulable.java

@@ -109,7 +109,12 @@ public class AppSchedulable extends Schedulable {
 
   @Override
   public Resource getMinShare() {
-    return Resources.createResource(0);
+    return Resources.none();
+  }
+  
+  @Override
+  public Resource getMaxShare() {
+    return Resources.unbounded();
   }
 
   /**

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-resourcemanager/src/main/java/org/apache/hadoop/yarn/server/resourcemanager/scheduler/fair/FSQueue.java

@@ -94,6 +94,11 @@ public abstract class FSQueue extends Schedulable implements Queue {
     return queueMgr.getMinResources(getName());
   }
   
+  @Override
+  public Resource getMaxShare() {
+    return queueMgr.getMaxResources(getName());
+  }
+
   @Override
   public long getStartTime() {
     return 0;

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-resourcemanager/src/main/java/org/apache/hadoop/yarn/server/resourcemanager/scheduler/fair/FairScheduler.java

@@ -311,7 +311,7 @@ public class FairScheduler implements ResourceScheduler {
    * defined as being below half its fair share.
    */
   boolean isStarvedForFairShare(FSLeafQueue sched) {
-    Resource desiredFairShare = Resources.max(RESOURCE_CALCULATOR, clusterCapacity,
+    Resource desiredFairShare = Resources.min(RESOURCE_CALCULATOR, clusterCapacity,
         Resources.multiply(sched.getFairShare(), .5), sched.getDemand());
     return Resources.lessThan(RESOURCE_CALCULATOR, clusterCapacity,
         sched.getResourceUsage(), desiredFairShare);

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-resourcemanager/src/main/java/org/apache/hadoop/yarn/server/resourcemanager/scheduler/fair/Schedulable.java

@@ -79,6 +79,8 @@ public abstract class Schedulable {
   /** Minimum Resource share assigned to the schedulable. */
   public abstract Resource getMinShare();
 
+  /** Maximum Resource share assigned to the schedulable. */
+  public abstract Resource getMaxShare();
 
   /** Job/queue weight in fair sharing. */
   public abstract ResourceWeights getWeights();

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-resourcemanager/src/main/java/org/apache/hadoop/yarn/server/resourcemanager/scheduler/fair/policies/ComputeFairShares.java

@@ -0,0 +1,172 @@
+/**
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.hadoop.yarn.server.resourcemanager.scheduler.fair.policies;
+
+import java.util.Collection;
+
+import org.apache.hadoop.yarn.api.records.Resource;
+import org.apache.hadoop.yarn.server.resourcemanager.resource.ResourceType;
+import org.apache.hadoop.yarn.server.resourcemanager.scheduler.fair.Schedulable;
+
+/**
+ * Contains logic for computing the fair shares. A {@link Schedulable}'s fair
+ * share is {@link Resource} it is entitled to, independent of the current
+ * demands and allocations on the cluster. A {@link Schedulable} whose resource
+ * consumption lies at or below its fair share will never have its containers
+ * preempted.
+ */
+public class ComputeFairShares {
+  
+  private static final int COMPUTE_FAIR_SHARES_ITERATIONS = 25;
+  
+  /**
+   * Given a set of Schedulables and a number of slots, compute their weighted
+   * fair shares. The min and max shares and of the Schedulables are assumed to
+   * be set beforehand. We compute the fairest possible allocation of shares to
+   * the Schedulables that respects their min and max shares.
+   * 
+   * To understand what this method does, we must first define what weighted
+   * fair sharing means in the presence of min and max shares. If there
+   * were no minimum or maximum shares, then weighted fair sharing would be
+   * achieved if the ratio of slotsAssigned / weight was equal for each
+   * Schedulable and all slots were assigned. Minimum and maximum shares add a
+   * further twist - Some Schedulables may have a min share higher than their
+   * assigned share or a max share lower than their assigned share.
+   * 
+   * To deal with these possibilities, we define an assignment of slots as being
+   * fair if there exists a ratio R such that: Schedulables S where S.minShare
+   * > R * S.weight are given share S.minShare - Schedulables S where S.maxShare
+   * < R * S.weight are given S.maxShare - All other Schedulables S are
+   * assigned share R * S.weight - The sum of all the shares is totalSlots.
+   * 
+   * We call R the weight-to-slots ratio because it converts a Schedulable's
+   * weight to the number of slots it is assigned.
+   * 
+   * We compute a fair allocation by finding a suitable weight-to-slot ratio R.
+   * To do this, we use binary search. Given a ratio R, we compute the number of
+   * slots that would be used in total with this ratio (the sum of the shares
+   * computed using the conditions above). If this number of slots is less than
+   * totalSlots, then R is too small and more slots could be assigned. If the
+   * number of slots is more than totalSlots, then R is too large.
+   * 
+   * We begin the binary search with a lower bound on R of 0 (which means that
+   * all Schedulables are only given their minShare) and an upper bound computed
+   * to be large enough that too many slots are given (by doubling R until we
+   * use more than totalResources resources). The helper method
+   * resourceUsedWithWeightToResourceRatio computes the total resources used with a
+   * given value of R.
+   * 
+   * The running time of this algorithm is linear in the number of Schedulables,
+   * because resourceUsedWithWeightToResourceRatio is linear-time and the number of
+   * iterations of binary search is a constant (dependent on desired precision).
+   */
+  public static void computeShares(
+      Collection<? extends Schedulable> schedulables, Resource totalResources,
+      ResourceType type) {
+    if (schedulables.isEmpty()) {
+      return;
+    }
+    // Find an upper bound on R that we can use in our binary search. We start
+    // at R = 1 and double it until we have either used all the resources or we
+    // have met all Schedulables' max shares.
+    int totalMaxShare = 0;
+    for (Schedulable sched : schedulables) {
+      int maxShare = getResourceValue(sched.getMaxShare(), type);
+      if (maxShare == Integer.MAX_VALUE) {
+        totalMaxShare = Integer.MAX_VALUE;
+        break;
+      } else {
+        totalMaxShare += maxShare;
+      }
+    }
+    int totalResource = Math.min(totalMaxShare,
+        getResourceValue(totalResources, type));
+    
+    double rMax = 1.0;
+    while (resourceUsedWithWeightToResourceRatio(rMax, schedulables, type)
+        < totalResource) {
+      rMax *= 2.0;
+    }
+    // Perform the binary search for up to COMPUTE_FAIR_SHARES_ITERATIONS steps
+    double left = 0;
+    double right = rMax;
+    for (int i = 0; i < COMPUTE_FAIR_SHARES_ITERATIONS; i++) {
+      double mid = (left + right) / 2.0;
+      if (resourceUsedWithWeightToResourceRatio(mid, schedulables, type) <
+          totalResource) {
+        left = mid;
+      } else {
+        right = mid;
+      }
+    }
+    // Set the fair shares based on the value of R we've converged to
+    for (Schedulable sched : schedulables) {
+      setResourceValue(computeShare(sched, right, type), sched.getFairShare(), type);
+    }
+  }
+
+  /**
+   * Compute the resources that would be used given a weight-to-resource ratio
+   * w2rRatio, for use in the computeFairShares algorithm as described in #
+   */
+  private static int resourceUsedWithWeightToResourceRatio(double w2rRatio,
+      Collection<? extends Schedulable> schedulables, ResourceType type) {
+    int resourcesTaken = 0;
+    for (Schedulable sched : schedulables) {
+      int share = computeShare(sched, w2rRatio, type);
+      resourcesTaken += share;
+    }
+    return resourcesTaken;
+  }
+
+  /**
+   * Compute the resources assigned to a Schedulable given a particular
+   * weight-to-resource ratio w2rRatio.
+   */
+  private static int computeShare(Schedulable sched, double w2rRatio,
+      ResourceType type) {
+    double share = sched.getWeights().getWeight(type) * w2rRatio;
+    share = Math.max(share, getResourceValue(sched.getMinShare(), type));
+    share = Math.min(share, getResourceValue(sched.getMaxShare(), type));
+    return (int) share;
+  }
+  
+  private static int getResourceValue(Resource resource, ResourceType type) {
+    switch (type) {
+    case MEMORY:
+      return resource.getMemory();
+    case CPU:
+      return resource.getVirtualCores();
+    default:
+      throw new IllegalArgumentException("Invalid resource");
+    }
+  }
+  
+  private static void setResourceValue(int val, Resource resource, ResourceType type) {
+    switch (type) {
+    case MEMORY:
+      resource.setMemory(val);
+      break;
+    case CPU:
+      resource.setVirtualCores(val);
+      break;
+    default:
+      throw new IllegalArgumentException("Invalid resource");
+    }
+  }
+}

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-resourcemanager/src/main/java/org/apache/hadoop/yarn/server/resourcemanager/scheduler/fair/policies/DominantResourceFairnessPolicy.java

@@ -64,13 +64,8 @@ public class DominantResourceFairnessPolicy extends SchedulingPolicy {
   @Override
   public void computeShares(Collection<? extends Schedulable> schedulables,
       Resource totalResources) {
-    
+    for (ResourceType type : ResourceType.values()) {
-    // TODO: For now, set all fair shares to 0, because, in the context of DRF,
+      ComputeFairShares.computeShares(schedulables, totalResources, type);
-    // it doesn't make sense to set a value for each resource.  YARN-736 should
-    // add in a sensible replacement.
-    
-    for (Schedulable schedulable : schedulables) {
-      schedulable.setFairShare(Resources.none());
     }
   }
   

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-resourcemanager/src/main/java/org/apache/hadoop/yarn/server/resourcemanager/scheduler/fair/policies/FairSharePolicy.java

@@ -116,120 +116,7 @@ public class FairSharePolicy extends SchedulingPolicy {
   @Override
   public void computeShares(Collection<? extends Schedulable> schedulables,
       Resource totalResources) {
-    computeFairShares(schedulables, totalResources);
+    ComputeFairShares.computeShares(schedulables, totalResources, ResourceType.MEMORY);
-  }
-
-  /**
-   * Number of iterations for the binary search in computeFairShares. This is
-   * equivalent to the number of bits of precision in the output. 25 iterations
-   * gives precision better than 0.1 slots in clusters with one million slots.
-   */
-  private static final int COMPUTE_FAIR_SHARES_ITERATIONS = 25;
-
-  /**
-   * Given a set of Schedulables and a number of slots, compute their weighted
-   * fair shares. The min shares and demands of the Schedulables are assumed to
-   * be set beforehand. We compute the fairest possible allocation of shares to
-   * the Schedulables that respects their min shares and demands.
-   * 
-   * To understand what this method does, we must first define what weighted
-   * fair sharing means in the presence of minimum shares and demands. If there
-   * were no minimum shares and every Schedulable had an infinite demand (i.e.
-   * could launch infinitely many tasks), then weighted fair sharing would be
-   * achieved if the ratio of slotsAssigned / weight was equal for each
-   * Schedulable and all slots were assigned. Minimum shares and demands add two
-   * further twists: - Some Schedulables may not have enough tasks to fill all
-   * their share. - Some Schedulables may have a min share higher than their
-   * assigned share.
-   * 
-   * To deal with these possibilities, we define an assignment of slots as being
-   * fair if there exists a ratio R such that: - Schedulables S where S.demand <
-   * R * S.weight are assigned share S.demand - Schedulables S where S.minShare
-   * > R * S.weight are given share S.minShare - All other Schedulables S are
-   * assigned share R * S.weight - The sum of all the shares is totalSlots.
-   * 
-   * We call R the weight-to-slots ratio because it converts a Schedulable's
-   * weight to the number of slots it is assigned.
-   * 
-   * We compute a fair allocation by finding a suitable weight-to-slot ratio R.
-   * To do this, we use binary search. Given a ratio R, we compute the number of
-   * slots that would be used in total with this ratio (the sum of the shares
-   * computed using the conditions above). If this number of slots is less than
-   * totalSlots, then R is too small and more slots could be assigned. If the
-   * number of slots is more than totalSlots, then R is too large.
-   * 
-   * We begin the binary search with a lower bound on R of 0 (which means that
-   * all Schedulables are only given their minShare) and an upper bound computed
-   * to be large enough that too many slots are given (by doubling R until we
-   * either use more than totalSlots slots or we fulfill all jobs' demands). The
-   * helper method slotsUsedWithWeightToSlotRatio computes the total number of
-   * slots used with a given value of R.
-   * 
-   * The running time of this algorithm is linear in the number of Schedulables,
-   * because slotsUsedWithWeightToSlotRatio is linear-time and the number of
-   * iterations of binary search is a constant (dependent on desired precision).
-   */
-  public static void computeFairShares(
-      Collection<? extends Schedulable> schedulables, Resource totalResources) {
-    // Find an upper bound on R that we can use in our binary search. We start
-    // at R = 1 and double it until we have either used totalSlots slots or we
-    // have met all Schedulables' demands (if total demand < totalSlots).
-    Resource totalDemand = Resources.createResource(0);
-    for (Schedulable sched : schedulables) {
-      Resources.addTo(totalDemand, sched.getDemand());
-    }
-    Resource cap = Resources.min(RESOURCE_CALCULATOR, null, totalDemand,
-        totalResources);
-    double rMax = 1.0;
-    while (Resources.lessThan(RESOURCE_CALCULATOR, null,
-        resUsedWithWeightToResRatio(rMax, schedulables),
-        cap)) {
-      rMax *= 2.0;
-    }
-    // Perform the binary search for up to COMPUTE_FAIR_SHARES_ITERATIONS steps
-    double left = 0;
-    double right = rMax;
-    for (int i = 0; i < COMPUTE_FAIR_SHARES_ITERATIONS; i++) {
-      double mid = (left + right) / 2.0;
-      if (Resources.lessThan(RESOURCE_CALCULATOR, null,
-          resUsedWithWeightToResRatio(mid, schedulables),
-          cap)) {
-        left = mid;
-      } else {
-        right = mid;
-      }
-    }
-    // Set the fair shares based on the value of R we've converged to
-    for (Schedulable sched : schedulables) {
-      sched.setFairShare(computeShare(sched, right));
-    }
-  }
-
-  /**
-   * Compute the number of slots that would be used given a weight-to-slot ratio
-   * w2sRatio, for use in the computeFairShares algorithm as described in #
-   * {@link SchedulingAlgorithms#computeFairShares(Collection, double)}.
-   */
-  private static Resource resUsedWithWeightToResRatio(double w2sRatio,
-      Collection<? extends Schedulable> schedulables) {
-    Resource slotsTaken = Resources.createResource(0);
-    for (Schedulable sched : schedulables) {
-      Resource share = computeShare(sched, w2sRatio);
-      Resources.addTo(slotsTaken, share);
-    }
-    return slotsTaken;
-  }
-
-  /**
-   * Compute the resources assigned to a Schedulable given a particular
-   * res-to-slot ratio r2sRatio, for use in computeFairShares as described in #
-   * {@link SchedulingAlgorithms#computeFairShares(Collection, double)}.
-   */
-  private static Resource computeShare(Schedulable sched, double r2sRatio) {
-    double share = sched.getWeights().getWeight(ResourceType.MEMORY) * r2sRatio;
-    share = Math.max(share, sched.getMinShare().getMemory());
-    share = Math.min(share, sched.getDemand().getMemory());
-    return Resources.createResource((int) share);
   }
 
   @Override

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-resourcemanager/src/main/java/org/apache/hadoop/yarn/server/resourcemanager/scheduler/fair/policies/FifoPolicy.java

@@ -73,10 +73,15 @@ public class FifoPolicy extends SchedulingPolicy {
   @Override
   public void computeShares(Collection<? extends Schedulable> schedulables,
       Resource totalResources) {
-    for (Schedulable sched : schedulables) {
+    Schedulable earliest = null;
-      sched.setFairShare(Resources.createResource(0));
+    for (Schedulable schedulable : schedulables) {
+      if (earliest == null ||
+          schedulable.getStartTime() < earliest.getStartTime()) {
+        earliest = schedulable;
       }
     }
+    earliest.setFairShare(Resources.clone(totalResources));
+  }
 
   @Override
   public byte getApplicableDepth() {

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-resourcemanager/src/test/java/org/apache/hadoop/yarn/server/resourcemanager/scheduler/fair/FakeSchedulable.java

@@ -28,40 +28,49 @@ import org.apache.hadoop.yarn.util.resource.Resources;
  * Dummy implementation of Schedulable for unit testing.
  */
 public class FakeSchedulable extends Schedulable {
-  private Resource demand;
   private Resource usage;
   private Resource minShare;
+  private Resource maxShare;
   private ResourceWeights weights;
   private Priority priority;
   private long startTime;
   
   public FakeSchedulable() {
-    this(0, 0, 1, 0, 0, 0);
+    this(0, Integer.MAX_VALUE, 1, 0, 0, 0);
   }
   
-  public FakeSchedulable(int demand) {
+  public FakeSchedulable(int minShare) {
-    this(demand, 0, 1, 0, 0, 0);
+    this(minShare, Integer.MAX_VALUE, 1, 0, 0, 0);
   }
   
-  public FakeSchedulable(int demand, int minShare) {
+  public FakeSchedulable(int minShare, int maxShare) {
-    this(demand, minShare, 1, 0, 0, 0);
+    this(minShare, maxShare, 1, 0, 0, 0);
   }
   
-  public FakeSchedulable(int demand, int minShare, double memoryWeight) {
+  public FakeSchedulable(int minShare, double memoryWeight) {
-    this(demand, minShare, memoryWeight, 0, 0, 0);
+    this(minShare, Integer.MAX_VALUE, memoryWeight, 0, 0, 0);
   }
   
-  public FakeSchedulable(int demand, int minShare, double weight, int fairShare, int usage,
+  public FakeSchedulable(int minShare, int maxShare, double memoryWeight) {
+    this(minShare, maxShare, memoryWeight, 0, 0, 0);
+  }
+  
+  public FakeSchedulable(int minShare, int maxShare, double weight, int fairShare, int usage,
       long startTime) {
-    this(Resources.createResource(demand), Resources.createResource(minShare),
+    this(Resources.createResource(minShare, 0), Resources.createResource(maxShare, 0),
-        new ResourceWeights((float)weight), Resources.createResource(fairShare),
+        new ResourceWeights((float)weight), Resources.createResource(fairShare, 0),
-        Resources.createResource(usage), startTime);
+        Resources.createResource(usage, 0), startTime);
   }
   
-  public FakeSchedulable(Resource demand, Resource minShare, ResourceWeights weight,
+  public FakeSchedulable(Resource minShare, ResourceWeights weights) {
-      Resource fairShare, Resource usage, long startTime) {
+    this(minShare, Resources.createResource(Integer.MAX_VALUE, Integer.MAX_VALUE),
-    this.demand = demand;
+        weights, Resources.createResource(0, 0), Resources.createResource(0, 0), 0);
+  }
+  
+  public FakeSchedulable(Resource minShare, Resource maxShare,
+      ResourceWeights weight, Resource fairShare, Resource usage, long startTime) {
     this.minShare = minShare;
+    this.maxShare = maxShare;
     this.weights = weight;
     setFairShare(fairShare);
     this.usage = usage;
@@ -76,7 +85,7 @@ public class FakeSchedulable extends Schedulable {
 
   @Override
   public Resource getDemand() {
-    return demand;
+    return null;
   }
 
   @Override
@@ -109,6 +118,11 @@ public class FakeSchedulable extends Schedulable {
     return minShare;
   }
   
+  @Override
+  public Resource getMaxShare() {
+    return maxShare;
+  }
+
   @Override
   public void updateDemand() {}
 }

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-resourcemanager/src/test/java/org/apache/hadoop/yarn/server/resourcemanager/scheduler/fair/TestComputeFairShares.java

@@ -23,8 +23,10 @@ import java.util.List;
 
 import junit.framework.Assert;
 
-import org.apache.hadoop.yarn.server.resourcemanager.scheduler.fair.policies.FairSharePolicy;
 import org.apache.hadoop.yarn.util.resource.Resources;
+import org.apache.hadoop.yarn.server.resourcemanager.resource.ResourceType;
+import org.apache.hadoop.yarn.server.resourcemanager.resource.ResourceWeights;
+import org.apache.hadoop.yarn.server.resourcemanager.scheduler.fair.policies.ComputeFairShares;
 import org.junit.Before;
 import org.junit.Test;
 
@@ -33,12 +35,10 @@ import org.junit.Test;
  */
 public class TestComputeFairShares {
   private List<Schedulable> scheds;
-  private SchedulingPolicy schedulingMode;
   
   @Before
   public void setUp() throws Exception {
     scheds = new ArrayList<Schedulable>();
-    schedulingMode = new FairSharePolicy();
   }
   
   /** 
@@ -47,13 +47,13 @@ public class TestComputeFairShares {
    */
   @Test
   public void testEqualSharing() {
-    scheds.add(new FakeSchedulable(100));
+    scheds.add(new FakeSchedulable());
-    scheds.add(new FakeSchedulable(50));
+    scheds.add(new FakeSchedulable());
-    scheds.add(new FakeSchedulable(30));
+    scheds.add(new FakeSchedulable());
-    scheds.add(new FakeSchedulable(20));
+    scheds.add(new FakeSchedulable());
-    schedulingMode.computeShares(scheds,
+    ComputeFairShares.computeShares(scheds,
-        Resources.createResource(40));
+        Resources.createResource(40), ResourceType.MEMORY);
-    verifyShares(10, 10, 10, 10);
+    verifyMemoryShares(10, 10, 10, 10);
   }
   
   /**
@@ -64,16 +64,17 @@ public class TestComputeFairShares {
    * so it only gets 11 slots. Pools 1 and 2 split the rest and get 13 each. 
    */
   @Test
-  public void testLowDemands() {
+  public void testLowMaxShares() {
-    scheds.add(new FakeSchedulable(100));
+    scheds.add(new FakeSchedulable(0, 100));
-    scheds.add(new FakeSchedulable(50));
+    scheds.add(new FakeSchedulable(0, 50));
-    scheds.add(new FakeSchedulable(11));
+    scheds.add(new FakeSchedulable(0, 11));
-    scheds.add(new FakeSchedulable(3));
+    scheds.add(new FakeSchedulable(0, 3));
-    schedulingMode.computeShares(scheds,
+    ComputeFairShares.computeShares(scheds,
-        Resources.createResource(40));
+        Resources.createResource(40), ResourceType.MEMORY);
-    verifyShares(13, 13, 11, 3);
+    verifyMemoryShares(13, 13, 11, 3);
   }
 
+    
   /**
    * In this test, some pools have minimum shares set. Pool 1 has a min share
    * of 20 so it gets 20 slots. Pool 2 also has a min share of 20, but its
@@ -84,13 +85,13 @@ public class TestComputeFairShares {
    */
   @Test
   public void testMinShares() {
-    scheds.add(new FakeSchedulable(100, 20));
+    scheds.add(new FakeSchedulable(20));
-    scheds.add(new FakeSchedulable(10, 20));
+    scheds.add(new FakeSchedulable(18));
-    scheds.add(new FakeSchedulable(10, 0));
+    scheds.add(new FakeSchedulable(0));
-    scheds.add(new FakeSchedulable(3, 2));
+    scheds.add(new FakeSchedulable(2));
-    schedulingMode.computeShares(scheds,
+    ComputeFairShares.computeShares(scheds,
-        Resources.createResource(40));
+        Resources.createResource(40), ResourceType.MEMORY);
-    verifyShares(20, 10, 7, 3);
+    verifyMemoryShares(20, 18, 0, 2);
   }
   
   /**
@@ -99,13 +100,13 @@ public class TestComputeFairShares {
    */
   @Test
   public void testWeightedSharing() {
-    scheds.add(new FakeSchedulable(100, 0, 2.0));
+    scheds.add(new FakeSchedulable(0, 2.0));
-    scheds.add(new FakeSchedulable(50,  0, 1.0));
+    scheds.add(new FakeSchedulable(0, 1.0));
-    scheds.add(new FakeSchedulable(30,  0, 1.0));
+    scheds.add(new FakeSchedulable(0, 1.0));
-    scheds.add(new FakeSchedulable(20,  0, 0.5));
+    scheds.add(new FakeSchedulable(0, 0.5));
-    schedulingMode.computeShares(scheds,
+    ComputeFairShares.computeShares(scheds,
-        Resources.createResource(45));
+        Resources.createResource(45), ResourceType.MEMORY);
-    verifyShares(20, 10, 10, 5);
+    verifyMemoryShares(20, 10, 10, 5);
   }
   
   /**
@@ -116,16 +117,17 @@ public class TestComputeFairShares {
    * the 24 slots left into a 1:0.5 ratio, getting 16 and 8 slots respectively.
    */
   @Test
-  public void testWeightedSharingWithLowDemands() {
+  public void testWeightedSharingWithMaxShares() {
-    scheds.add(new FakeSchedulable(10, 0, 2.0));
+    scheds.add(new FakeSchedulable(0, 10, 2.0));
-    scheds.add(new FakeSchedulable(11, 0, 1.0));
+    scheds.add(new FakeSchedulable(0, 11, 1.0));
-    scheds.add(new FakeSchedulable(30, 0, 1.0));
+    scheds.add(new FakeSchedulable(0, 30, 1.0));
-    scheds.add(new FakeSchedulable(20, 0, 0.5));
+    scheds.add(new FakeSchedulable(0, 20, 0.5));
-    schedulingMode.computeShares(scheds,
+    ComputeFairShares.computeShares(scheds,
-        Resources.createResource(45));
+        Resources.createResource(45), ResourceType.MEMORY);
-    verifyShares(10, 11, 16, 8);
+    verifyMemoryShares(10, 11, 16, 8);
   }
 
+
   /**
    * Weighted fair sharing test with min shares. As in the min share test above,
    * pool 1 has a min share greater than its demand so it only gets its demand.
@@ -135,13 +137,13 @@ public class TestComputeFairShares {
    */
   @Test
   public void testWeightedSharingWithMinShares() {
-    scheds.add(new FakeSchedulable(10, 20, 2.0));
+    scheds.add(new FakeSchedulable(20, 2.0));
-    scheds.add(new FakeSchedulable(11, 0, 1.0));
+    scheds.add(new FakeSchedulable(0, 1.0));
-    scheds.add(new FakeSchedulable(30, 5, 1.0));
+    scheds.add(new FakeSchedulable(5, 1.0));
-    scheds.add(new FakeSchedulable(20, 15, 0.5));
+    scheds.add(new FakeSchedulable(15, 0.5));
-    schedulingMode.computeShares(scheds,
+    ComputeFairShares.computeShares(scheds,
-        Resources.createResource(45));
+        Resources.createResource(45), ResourceType.MEMORY);
-    verifyShares(10, 10, 10, 15);
+    verifyMemoryShares(20, 5, 5, 15);
   }
 
   /**
@@ -151,28 +153,13 @@ public class TestComputeFairShares {
   @Test
   public void testLargeShares() {
     int million = 1000 * 1000;
-    scheds.add(new FakeSchedulable(100 * million));
+    scheds.add(new FakeSchedulable());
-    scheds.add(new FakeSchedulable(50 * million));
+    scheds.add(new FakeSchedulable());
-    scheds.add(new FakeSchedulable(30 * million));
+    scheds.add(new FakeSchedulable());
-    scheds.add(new FakeSchedulable(20 * million));
+    scheds.add(new FakeSchedulable());
-    schedulingMode
+    ComputeFairShares.computeShares(scheds,
-        .computeShares(scheds,
+        Resources.createResource(40 * million), ResourceType.MEMORY);
-        Resources.createResource(40 * million));
+    verifyMemoryShares(10 * million, 10 * million, 10 * million, 10 * million);
-    verifyShares(10 * million, 10 * million, 10 * million, 10 * million);
-  }
-
-  /**
-   * Test that having a pool with 0 demand doesn't confuse the algorithm.
-   */
-  @Test
-  public void testZeroDemand() {
-    scheds.add(new FakeSchedulable(100));
-    scheds.add(new FakeSchedulable(50));
-    scheds.add(new FakeSchedulable(30));
-    scheds.add(new FakeSchedulable(0));
-    schedulingMode.computeShares(scheds,
-        Resources.createResource(30));
-    verifyShares(10, 10, 10, 0);
   }
   
   /**
@@ -180,18 +167,46 @@ public class TestComputeFairShares {
    */
   @Test
   public void testEmptyList() {
-    schedulingMode.computeShares(scheds,
+    ComputeFairShares.computeShares(scheds,
-        Resources.createResource(40));
+        Resources.createResource(40), ResourceType.MEMORY);
-    verifyShares();
+    verifyMemoryShares();
+  }
+  
+  /**
+   * Test that CPU works as well as memory
+   */
+  @Test
+  public void testCPU() {
+    scheds.add(new FakeSchedulable(Resources.createResource(0, 20),
+        new ResourceWeights(2.0f)));
+    scheds.add(new FakeSchedulable(Resources.createResource(0, 0),
+        new ResourceWeights(1.0f)));
+    scheds.add(new FakeSchedulable(Resources.createResource(0, 5),
+        new ResourceWeights(1.0f)));
+    scheds.add(new FakeSchedulable(Resources.createResource(0, 15),
+        new ResourceWeights(0.5f)));
+    ComputeFairShares.computeShares(scheds,
+        Resources.createResource(0, 45), ResourceType.CPU);
+    verifyCPUShares(20, 5, 5, 15);
   }
   
   /**
    * Check that a given list of shares have been assigned to this.scheds.
    */
-  private void verifyShares(double... shares) {
+  private void verifyMemoryShares(int... shares) {
     Assert.assertEquals(scheds.size(), shares.length);
     for (int i = 0; i < shares.length; i++) {
-      Assert.assertEquals(shares[i], scheds.get(i).getFairShare().getMemory(), 0.01);
+      Assert.assertEquals(shares[i], scheds.get(i).getFairShare().getMemory());
+    }
+  }
+  
+  /**
+   * Check that a given list of shares have been assigned to this.scheds.
+   */
+  private void verifyCPUShares(int... shares) {
+    Assert.assertEquals(scheds.size(), shares.length);
+    for (int i = 0; i < shares.length; i++) {
+      Assert.assertEquals(shares[i], scheds.get(i).getFairShare().getVirtualCores());
     }
   }
 }

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-resourcemanager/src/test/java/org/apache/hadoop/yarn/server/resourcemanager/scheduler/fair/TestFairScheduler.java

@@ -375,10 +375,9 @@ public class TestFairScheduler {
     Collection<FSLeafQueue> queues = scheduler.getQueueManager().getLeafQueues();
     assertEquals(3, queues.size());
     
+    // Divided three ways - betwen the two queues and the default queue
     for (FSLeafQueue p : queues) {
-      if (!p.getName().equals("root.default")) {
+      assertEquals(3414, p.getFairShare().getMemory());
-        assertEquals(5120, p.getFairShare().getMemory());
-      }
     }
   }
   
@@ -393,7 +392,7 @@ public class TestFairScheduler {
     scheduler.handle(nodeEvent1);
 
     // Have two queues which want entire cluster capacity
-    createSchedulingRequest(10 * 1024, "queue1", "user1");
+    createSchedulingRequest(10 * 1024, "default", "user1");
     createSchedulingRequest(10 * 1024, "parent.queue2", "user1");
     createSchedulingRequest(10 * 1024, "parent.queue3", "user1");
 
@@ -401,9 +400,9 @@ public class TestFairScheduler {
 
     QueueManager queueManager = scheduler.getQueueManager();
     Collection<FSLeafQueue> queues = queueManager.getLeafQueues();
-    assertEquals(4, queues.size());
+    assertEquals(3, queues.size());
     
-    FSLeafQueue queue1 = queueManager.getLeafQueue("queue1");
+    FSLeafQueue queue1 = queueManager.getLeafQueue("default");
     FSLeafQueue queue2 = queueManager.getLeafQueue("parent.queue2");
     FSLeafQueue queue3 = queueManager.getLeafQueue("parent.queue3");
     assertEquals(capacity / 2, queue1.getFairShare().getMemory());

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-resourcemanager/src/test/java/org/apache/hadoop/yarn/server/resourcemanager/scheduler/fair/policies/TestDominantResourceFairnessPolicy.java

@@ -64,8 +64,9 @@ public class TestDominantResourceFairnessPolicy {
       ResourceWeights weights, int minMemShare, int minCpuShare) {
     Resource usage = BuilderUtils.newResource(memUsage, cpuUsage);
     Resource minShare = BuilderUtils.newResource(minMemShare, minCpuShare);
-    return new FakeSchedulable(Resources.none(), minShare, weights,
+    return new FakeSchedulable(minShare,
-        Resources.none(), usage, 0l);
+        Resources.createResource(Integer.MAX_VALUE, Integer.MAX_VALUE),
+        weights, Resources.none(), usage, 0l);
   }
   
   @Test

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-site/src/site/apt/FairScheduler.apt.vm

@@ -257,3 +257,39 @@ Allocation file format
 ---
 
   Note that for backwards compatibility with the original FairScheduler, "queue" elements can instead be named as "pool" elements.
+  
+* {Administration}
+
+  The fair scheduler provides support for administration at runtime through two mechanisms:
+
+ * It is possible to modify minimum shares, limits, weights, preemption timeouts
+   and queue scheduling policies at runtime by editing the allocation file. The
+   scheduler will reload this file 10-15 seconds after it sees that it was
+   modified.
+
+ * Current applications, queues, and fair shares can be examined through the
+   ResourceManager's web interface, at
+   http://<ResourceManager URL>/cluster/scheduler.
+
+  The following fields can be seen for each queue on the web interface:
+  
+ * Used Resources - The sum of resources allocated to containers within the queue. 
+
+ * Num Active Applications - The number of applications in the queue that have
+   received at least one container.
+ 
+ * Num Pending Applications - The number of applications in the queue that have
+   not yet received any containers.
+
+ * Min Resources - The configured minimum resources that are guaranteed to the queue.
+  	
+ * Max Resources - The configured maximum resources that are allowed to the queue.
+ 
+ * Fair Share - The queue's fair share of resources.  Queues may be allocated
+   resources beyond their fair share when other queues aren't using them.  A
+   queue whose resource consumption lies at or below its fair share will never
+   have its containers preempted.  
+
+  In addition to the information that the ResourceManager normally displays
+  about each application, the web interface includes the application's fair share.
+