Theoretical global-knowledge algorithm for smart kafka partition rebalancing

rebalance.pseudocode

brokers = [1,2,...]

# ensure exactly 3 replicas per partition
for p in partitions
  if len(p) > 3; p = p[0...2]
  if len(p) < 3; p += (brokers - p).sample(3 - len(p))

weights = {}
for p in partitions
  for b in p
    weights[b]++

while max(weight) - min(weight) > 3 # any proof 3 is always possible?
  let p = (find partition whose list contains the max-weight broker but not the min-weight broker)
  p.replace(max-weight-broker, min-weight-broker)

weights = {}
for p in partitions
  weights[p.leader]++

while max(weight) - min(weight) > 1 # any proof 1 is always possible?
  let p = (find partition led by max-weight broker also replicated on min-weight broker)
  p = [min-weight, max-weight, the-other-one]