package balancer import ( cmap "github.com/orcaman/concurrent-map/v2" "github.com/seaweedfs/seaweedfs/weed/pb/mq_pb" "math/rand" ) func allocateTopicPartitions(brokers cmap.ConcurrentMap[string, *BrokerStats], partitionCount int32) (assignments []*mq_pb.BrokerPartitionAssignment) { // divide the ring into partitions rangeSize := MaxPartitionCount / partitionCount for i := int32(0); i < partitionCount; i++ { assignment := &mq_pb.BrokerPartitionAssignment{ Partition: &mq_pb.Partition{ RingSize: MaxPartitionCount, RangeStart: int32(i * rangeSize), RangeStop: int32((i + 1) * rangeSize), }, } if i == partitionCount-1 { assignment.Partition.RangeStop = MaxPartitionCount } assignments = append(assignments, assignment) } // pick the brokers pickedBrokers := pickBrokers(brokers, partitionCount) // assign the partitions to brokers for i, assignment := range assignments { assignment.LeaderBroker = pickedBrokers[i] } return } // for now: randomly pick brokers // TODO pick brokers based on the broker stats func pickBrokers(brokers cmap.ConcurrentMap[string, *BrokerStats], count int32) []string { candidates := make([]string, 0, brokers.Count()) for brokerStatsItem := range brokers.IterBuffered() { candidates = append(candidates, brokerStatsItem.Key) } pickedBrokers := make([]string, 0, count) for i := int32(0); i < count; i++ { p := rand.Int() % len(candidates) if p < 0 { p = -p } pickedBrokers = append(pickedBrokers, candidates[p]) } return pickedBrokers }