pjl1070048431 opened a new pull request, #19297:
URL: https://github.com/apache/kafka/pull/19297
## Motivation
Kafka clusters typically require rebalancing of topic replicas after
horizontal scaling to evenly distribute the load across new and existing
brokers. The current rebalancing approach does not consider the existing
replica distribution, often resulting in excessive and unnecessary replica
movements. These unnecessary movements increase rebalance duration, consume
significant bandwidth and CPU resources, and potentially disrupt ongoing
production and consumption operations. Thus, a replica rebalancing strategy
that minimizes movements while achieving an even distribution of replicas is
necessary.
## Goals
The new replica rebalancing strategy aims to achieve the following
objectives:
1. **Minimal Movement**: Minimize the number of replica relocations during
rebalancing.
2. **Replica Balancing**: Ensure that replicas are evenly distributed across
brokers.
3. **Anti-Affinity Support**: Support rack-aware allocation when enabled.
4. **Leader Balancing**: Distribute leader replicas evenly across brokers.
5. **ISR Order Optimization**: Optimize adjacency relationships to prevent
failover traffic concentration in case of broker failures.
## Proposed Changes
### Rack-Level Replica Distribution
The following rules ensure balanced replica allocation at the rack level:
1. **When** `**rackCount = replicationFactor**`:
- Each rack receives exactly `partitionCount` replicas.
2. **When** `**rackCount > replicationFactor**`:
- If weighted allocation `(rackBrokers/totalBrokers × totalReplicas) ≥
partitionCount`: each rack receives exactly `partitionCount` replicas.
- If weighted allocation `< partitionCount`: distribute remaining
replicas using a weighted remainder allocation.
### Node-Level Replica Distribution
1. If the number of replicas assigned to a rack is not a multiple of the
number of nodes in that rack, some nodes will host one additional replica
compared to others.
2. **When** `**rackCount = replicationFactor**`:
- If all racks have an equal number of nodes, each node will host an
equal number of replicas.
- If rack sizes vary, nodes in larger racks will host fewer replicas on
average.
3. **When** `**rackCount > replicationFactor**`:
- If no rack has a significantly higher node weight, replicas will be
evenly distributed.
- If a rack has disproportionately high node weight, those nodes will
receive fewer replicas.
### Anti-Affinity Support
When anti-affinity is enabled, the rebalance algorithm ensures that replicas
of the same partition do not colocate on the same rack. Brokers without rack
configuration are excluded from anti-affinity checks.
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