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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
}
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