YARN-6307. Refactor FairShareComparator#compare (Contributed by Yufei Gu via Daniel Templeton)
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@ -56,24 +56,28 @@ public class FairSharePolicy extends SchedulingPolicy {
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}
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}
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/**
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/**
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* Compare Schedulables via weighted fair sharing. In addition, Schedulables
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* Compare Schedulables mainly via fair share usage to meet fairness.
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* below their min share get priority over those whose min share is met.
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* Specifically, it goes through following four steps.
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*
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*
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* Schedulables without resource demand get lower priority than
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* 1. Compare demands. Schedulables without resource demand get lower priority
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* ones who have demands.
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* than ones who have demands.
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*
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*
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* Schedulables below their min share are compared by how far below it they
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* 2. Compare min share usage. Schedulables below their min share are compared
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* are as a ratio. For example, if job A has 8 out of a min share of 10 tasks
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* by how far below it they are as a ratio. For example, if job A has 8 out
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* and job B has 50 out of a min share of 100, then job B is scheduled next,
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* of a min share of 10 tasks and job B has 50 out of a min share of 100,
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* because B is at 50% of its min share and A is at 80% of its min share.
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* then job B is scheduled next, because B is at 50% of its min share and A
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* is at 80% of its min share.
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*
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*
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* Schedulables above their min share are compared by (runningTasks / weight).
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* 3. Compare fair share usage. Schedulables above their min share are
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* compared by fair share usage by checking (resource usage / weight).
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* If all weights are equal, slots are given to the job with the fewest tasks;
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* If all weights are equal, slots are given to the job with the fewest tasks;
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* otherwise, jobs with more weight get proportionally more slots. If weight
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* otherwise, jobs with more weight get proportionally more slots. If weight
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* equals to 0, we can't compare Schedulables by (resource usage/weight).
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* equals to 0, we can't compare Schedulables by (resource usage/weight).
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* There are two situations: 1)All weights equal to 0, slots are given
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* There are two situations: 1)All weights equal to 0, slots are given
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* to one with less resource usage. 2)Only one of weight equals to 0, slots
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* to one with less resource usage. 2)Only one of weight equals to 0, slots
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* are given to the one with non-zero weight.
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* are given to the one with non-zero weight.
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*
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* 4. Break the tie by compare submit time and job name.
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*/
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*/
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private static class FairShareComparator implements Comparator<Schedulable>,
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private static class FairShareComparator implements Comparator<Schedulable>,
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Serializable {
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Serializable {
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@ -82,37 +86,88 @@ public class FairSharePolicy extends SchedulingPolicy {
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@Override
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@Override
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public int compare(Schedulable s1, Schedulable s2) {
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public int compare(Schedulable s1, Schedulable s2) {
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int res = compareDemand(s1, s2);
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// Pre-compute resource usages to avoid duplicate calculation
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Resource resourceUsage1 = s1.getResourceUsage();
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Resource resourceUsage2 = s2.getResourceUsage();
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if (res == 0) {
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res = compareMinShareUsage(s1, s2, resourceUsage1, resourceUsage2);
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}
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if (res == 0) {
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res = compareFairShareUsage(s1, s2, resourceUsage1, resourceUsage2);
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}
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// Break the tie by submit time
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if (res == 0) {
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res = (int) Math.signum(s1.getStartTime() - s2.getStartTime());
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}
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// Break the tie by job name
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if (res == 0) {
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res = s1.getName().compareTo(s2.getName());
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}
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return res;
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}
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private int compareDemand(Schedulable s1, Schedulable s2) {
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int res = 0;
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Resource demand1 = s1.getDemand();
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Resource demand1 = s1.getDemand();
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Resource demand2 = s2.getDemand();
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Resource demand2 = s2.getDemand();
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if (demand1.equals(Resources.none()) && Resources.greaterThan(
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if (demand1.equals(Resources.none()) && Resources.greaterThan(
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RESOURCE_CALCULATOR, null, demand2, Resources.none())) {
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RESOURCE_CALCULATOR, null, demand2, Resources.none())) {
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return 1;
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res = 1;
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} else if (demand2.equals(Resources.none()) && Resources.greaterThan(
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} else if (demand2.equals(Resources.none()) && Resources.greaterThan(
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RESOURCE_CALCULATOR, null, demand1, Resources.none())) {
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RESOURCE_CALCULATOR, null, demand1, Resources.none())) {
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return -1;
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res = -1;
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}
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return res;
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}
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}
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double minShareRatio1, minShareRatio2;
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private int compareMinShareUsage(Schedulable s1, Schedulable s2,
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double useToWeightRatio1, useToWeightRatio2;
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Resource resourceUsage1, Resource resourceUsage2) {
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double weight1, weight2;
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int res;
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//Do not repeat the getResourceUsage calculation
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Resource resourceUsage1 = s1.getResourceUsage();
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Resource resourceUsage2 = s2.getResourceUsage();
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Resource minShare1 = Resources.min(RESOURCE_CALCULATOR, null,
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Resource minShare1 = Resources.min(RESOURCE_CALCULATOR, null,
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s1.getMinShare(), demand1);
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s1.getMinShare(), s1.getDemand());
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Resource minShare2 = Resources.min(RESOURCE_CALCULATOR, null,
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Resource minShare2 = Resources.min(RESOURCE_CALCULATOR, null,
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s2.getMinShare(), demand2);
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s2.getMinShare(), s2.getDemand());
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boolean s1Needy = Resources.lessThan(RESOURCE_CALCULATOR, null,
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boolean s1Needy = Resources.lessThan(RESOURCE_CALCULATOR, null,
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resourceUsage1, minShare1);
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resourceUsage1, minShare1);
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boolean s2Needy = Resources.lessThan(RESOURCE_CALCULATOR, null,
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boolean s2Needy = Resources.lessThan(RESOURCE_CALCULATOR, null,
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resourceUsage2, minShare2);
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resourceUsage2, minShare2);
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minShareRatio1 = (double) resourceUsage1.getMemorySize()
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/ Resources.max(RESOURCE_CALCULATOR, null, minShare1, ONE).getMemorySize();
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minShareRatio2 = (double) resourceUsage2.getMemorySize()
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/ Resources.max(RESOURCE_CALCULATOR, null, minShare2, ONE).getMemorySize();
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weight1 = s1.getWeights().getWeight(ResourceType.MEMORY);
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if (s1Needy && !s2Needy) {
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weight2 = s2.getWeights().getWeight(ResourceType.MEMORY);
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res = -1;
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} else if (s2Needy && !s1Needy) {
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res = 1;
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} else if (s1Needy && s2Needy) {
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double minShareRatio1 = (double) resourceUsage1.getMemorySize() /
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Resources.max(RESOURCE_CALCULATOR, null, minShare1, ONE)
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.getMemorySize();
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double minShareRatio2 = (double) resourceUsage2.getMemorySize() /
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Resources.max(RESOURCE_CALCULATOR, null, minShare2, ONE)
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.getMemorySize();
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res = (int) Math.signum(minShareRatio1 - minShareRatio2);
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} else {
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res = 0;
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}
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return res;
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}
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/**
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* To simplify computation, use weights instead of fair shares to calculate
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* fair share usage.
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*/
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private int compareFairShareUsage(Schedulable s1, Schedulable s2,
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Resource resourceUsage1, Resource resourceUsage2) {
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double weight1 = s1.getWeights().getWeight(ResourceType.MEMORY);
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double weight2 = s2.getWeights().getWeight(ResourceType.MEMORY);
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double useToWeightRatio1;
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double useToWeightRatio2;
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if (weight1 > 0.0 && weight2 > 0.0) {
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if (weight1 > 0.0 && weight2 > 0.0) {
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useToWeightRatio1 = resourceUsage1.getMemorySize() / weight1;
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useToWeightRatio1 = resourceUsage1.getMemorySize() / weight1;
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useToWeightRatio2 = resourceUsage2.getMemorySize() / weight2;
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useToWeightRatio2 = resourceUsage2.getMemorySize() / weight2;
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@ -130,25 +185,7 @@ public class FairSharePolicy extends SchedulingPolicy {
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}
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}
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}
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}
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int res = 0;
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return (int) Math.signum(useToWeightRatio1 - useToWeightRatio2);
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if (s1Needy && !s2Needy)
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res = -1;
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else if (s2Needy && !s1Needy)
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res = 1;
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else if (s1Needy && s2Needy)
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res = (int) Math.signum(minShareRatio1 - minShareRatio2);
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else
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// Neither schedulable is needy
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res = (int) Math.signum(useToWeightRatio1 - useToWeightRatio2);
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if (res == 0) {
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// Apps are tied in fairness ratio. Break the tie by submit time and job
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// name to get a deterministic ordering, which is useful for unit tests.
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res = (int) Math.signum(s1.getStartTime() - s2.getStartTime());
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if (res == 0) {
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res = s1.getName().compareTo(s2.getName());
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}
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}
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return res;
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}
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}
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}
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}
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