jiajunwang commented on a change in pull request #520: Refactor soft
constraints to simply the algorithm and fix potential issues.
URL: https://github.com/apache/helix/pull/520#discussion_r339248381
##########
File path:
helix-core/src/main/java/org/apache/helix/controller/rebalancer/waged/constraints/ConstraintBasedAlgorithm.java
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@@ -109,19 +109,22 @@ public OptimalAssignment calculate(ClusterModel
clusterModel) throws HelixRebala
return Optional.empty();
}
- Function<AssignableNode, Float> calculatePoints =
+ Function<AssignableNode, Double> calculatePoints =
(candidateNode) -> getAssignmentNormalizedScore(candidateNode,
replica, clusterContext);
return candidateNodes.stream().max(Comparator.comparing(calculatePoints));
}
- private float getAssignmentNormalizedScore(AssignableNode node,
AssignableReplica replica,
+ private double getAssignmentNormalizedScore(AssignableNode node,
AssignableReplica replica,
ClusterContext clusterContext) {
- float sum = 0;
+ double sum = 0;
for (Map.Entry<SoftConstraint, Float> softConstraintEntry :
_softConstraints.entrySet()) {
SoftConstraint softConstraint = softConstraintEntry.getKey();
float weight = softConstraintEntry.getValue();
- sum += weight * softConstraint.getAssignmentNormalizedScore(node,
replica, clusterContext);
+ if (weight != 0) {
Review comment:
For that statement, I am not so sure. For example, I have a cluster don't
care about top state assignment. So I set the weight of top state constraint to
be zero. Then Helix does not need to do that calculation.
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