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feat: implement calc group score for duplicate to assign replicas evenly 

Signed-off-by: ipsum-0320 <trueman.0320@zju.edu.cn>

feat: implement calc group score for duplicate to assign replicas evenly

Signed-off-by: ipsum-0320 <trueman.0320@zju.edu.cn>

feat: calc group score for duplicate to assign replicas evenly

Signed-off-by: ipsum-0320 <trueman.0320@zju.edu.cn>
This commit is contained in:
ipsum-0320 2024-10-28 17:54:02 +08:00
parent ff6075c801
commit 9e349e60a8
1 changed files with 85 additions and 1 deletions
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86
pkg/scheduler/core/spreadconstraint/group_clusters.go
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@ -135,17 +135,101 @@ func groupClustersIgnoringTopology(
// Thus, when sorting by Group Score, targetReplica will be considered first, and if the Weights are the same, then Score will be considered.
const weightUnit int64 = 1000
func (info *GroupClustersInfo) calcGroupScoreForDuplicate(
clusters []ClusterDetailInfo,
rbSpec *workv1alpha2.ResourceBindingSpec) int64 {
targetReplica := int64(rbSpec.Replicas)
var validClusters int64
// validClusters is the number of clusters that have available replicas.
var sumValidScore int64
for _, cluster := range clusters {
if cluster.AvailableReplicas >= targetReplica {
validClusters++
sumValidScore += cluster.Score
}
}
// Here is an example, the rbSpec.Replicas == 50.
// There is the Group 1, it has five clusters as follows.
// ----------------------------------------------------------------------
// | clusterName | member1 | member2 | member3 | member4 | member5 |
// |---------------------------------------------------------------------
// | score | 100 | 100 | 100 | 100 | 100 |
// |------------------------------------------------|---------|---------|
// |AvailableReplicas | 60 | 70 | 40 | 30 | 10 |
// |------------------------------------------------|---------|---------|
// There is the Group 2, it has four clusters as follows.
// ------------------------------------------------------------
// | clusterName | member1 | member2 | member3 | member4 |
// |-----------------------------------------------------------
// | score | 0 | 0 | 0 | 0 |
// |------------------------------------------------|---------|
// |AvailableReplicas | 60 | 60 | 60 | 60 |
// |------------------------------------------------|---------|
// According to our expectations, Group 2 is a more ideal choice than Group 1,
// as the number of clusters in Group 2 that meet the Replica requirements
// for available copies is greater. Although the average Cluster.Score in Group 1 is higher,
// under the Duplicate replica allocation strategy,
// we prioritize whether the number of available replicas in each Cluster
// meets the Replica requirements. Based on our algorithm, the score for Group 2
// is also higher than that of Group 1.
// Group1's Score = 2 * 1000 + 100 = 2100
// Group2's Score = 4 * 1000 + 0 = 4000
// There is another example, the rbSpec.Replicas == 50.
// There is the Group 1, it has five clusters as follows.
// ----------------------------------------------------------------------
// | clusterName | member1 | member2 | member3 | member4 | member5 |
// |---------------------------------------------------------------------
// | score | 100 | 100 | 100 | 100 | 100 |
// |------------------------------------------------|---------|---------|
// |AvailableReplicas | 60 | 70 | 10 | 10 | 5 |
// |------------------------------------------------|---------|---------|
// There is the Group 2, it has four clusters as follows.
// ------------------------------------------------------------
// | clusterName | member1 | member2 | member3 | member4 |
// |-----------------------------------------------------------
// | score | 0 | 0 | 0 | 0 |
// |------------------------------------------------|---------|
// |AvailableReplicas | 100 | 100 | 10 | 10 |
// |------------------------------------------------|---------|
// According to our expectations, Group 1 is a more ideal choice than Group 2.
// Although the number of clusters meeting the Replica requirements for available
// copies is the same in both Group 1 and Group 2, the average Cluster.Score in Group 1 is higher.
// Therefore, Group 1 is the better choice. Based on our algorithm,
// the score for Group 1 is also higher than that of Group 2.
// Group1's Score = 2 * 1000 + 100 = 2100
// Group2's Score = 2 * 1000 + 0 = 2000
// the priority of validClusters is higher than sumValidScore.
weightedValidClusters := validClusters * weightUnit
return weightedValidClusters + sumValidScore/validClusters
}
func (info *GroupClustersInfo) calcGroupScore(
clusters []ClusterDetailInfo,
rbSpec *workv1alpha2.ResourceBindingSpec,
minGroups int) int64 {
if rbSpec.Placement == nil || rbSpec.Placement.ReplicaSchedulingType() == policyv1alpha1.ReplicaSchedulingTypeDuplicated {
// if the replica scheduling type is duplicated, the score is calculated by calcGroupScoreForDuplicate.
return info.calcGroupScoreForDuplicate(clusters, rbSpec)
}
// if the replica scheduling type is divided, the score is calculated by followed.
float64MinGroups := float64(minGroups)
targetReplica := int64(math.Ceil(float64(rbSpec.Replicas) / float64MinGroups))
// get the minGroups of Cluster.
var clusterMinGroups int
if rbSpec.Placement != nil && rbSpec.Placement.SpreadConstraints != nil {
if rbSpec.Placement.SpreadConstraints != nil {
for _, sc := range rbSpec.Placement.SpreadConstraints {
if sc.SpreadByField == policyv1alpha1.SpreadByFieldCluster {
clusterMinGroups = sc.MinGroups