If a queue is declared and there are currently less than 1000 queues in the cluster,
we perform an exact check/comparison and place the leader on the node with the least number of leaders.
If there is more than 1000 queues, a random node is picked, because that's a much faster operation than
counting leaders on all nodes and at this scale, we assume it doesn't really matter (random still provides a relatively
even distribution). The history of "balanced" is that "least-leaders" strategy that we used to have
didn't scale well - for example importing 10000 queues to a cluster would get very slow over time since for every new
queue, we had to count the exact number of queue leaders on each node. The "random" strategy on the other hand,
doesn't work well with a low number of queues (with just a handful of queues, the distribution can be very skewed).
Hence, we implemented a mixed "balanced" strategy, which provides the perfect distribution for a relatively small
number of queues and fairly even distribution for a large number of queues, while providing much better performance:
O(1) instead of O(N) for N > 1000.
If this is not the behaviour you see, please provide an executable test case.
If you think the docs are not clear enough - please PR a suggested edit.