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Current state: "Under Discussion"
Discussion thread: here
JIRA: KAFKA-19577
Please keep the discussion on the mailing list rather than commenting on the wiki (wiki discussions get unwieldy fast).
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However, there are still special cases—such as internal testing or experimental features—where users may want to define a custom placement strategy. Therefore, we propose providing a mechanism that allows users to implement their own ReplicaPlacer.
Previously, KIP-660: Pluggable ReplicaPlacer proposed proposed making the ReplicaPlacer pluggable, but the proposal was rejected. The main concern was that an intelligent placement strategy might require a full view of the cluster, which could be prohibitively expensive in large deployments. Furthermore, such implementations could become overly complex and might introduce latency that impacts the controller thread, thus affecting system stability.
The issue of KAFKA-19507 shows a real-world need for solving custom replica assignment problems. It reinforces the point that different usage scenarios often come with unique assignment needs.
Nevertheless, we can make the classify ReplicaPlacer as an internal pluggable unstable component. This means the mechanism would not will be exposed to external users, but could be utilized without any guarantees of compatibility or long-term stability. The configuration is primarily intended for advanced users and can be useful in internal testing, special-purpose specialized scenarios, or controlled experiments. By allowing different implementations to be injected internally, we can make gain flexibility in the placement logic more flexible for testing purposes, without compromising while ensuring that the stability of the controller is not compromised.
Public Interfaces
New internal broker configuration:
- Class: ReplicationConfigs
- Name: replica.placer.class.name
- Type: string
- Default: StripedReplicaPlacer
- Valid Values: non-empty string
- DocDocument: The fully qualified class name of the ReplicaPlacer implementation. This class plugin is considered unstable, meaning the Kafka community does not provide guarantees of compatibility or long-term stability. It is used by the broker to determine the replica placement of replicas when topics or partitions are created. This configuration is intended for advanced use cases such as internal testing environments, experimental feature development, performance evaluation, or benchmarking. Custom implementations should be lightweight and efficient to avoid degrading controller performance or impacting overall cluster stability.
New public package:
- org.apache.kafka.metadata.placement
New public unstable classes in `org.apache.kafka.metadata.placement` package
- ReplicaPlacer
- PartitionAssignment
TopicAssignment
PlacementSpec
DefaultDirProvider
ClusterDescriber
UsableBroker
Proposed Changes
Add a new internal configuration: internal. replica.placer.class.name. This configuration allows users to define a custom ReplicaPlacer implementation.
| Code Block | ||
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public static final String INTERNAL_REPLICA_PLACER_CLASS_NAME = "replica.placer.class.name"; public static final String INTERNAL_REPLICA_PLACER_CLASS_NAME_DEFAULT = StripedReplicaPlacer.class.getName(); public static final String INTERNAL_REPLICA_PLACER_CLASS_NAME_DOC = "The fully qualified class name of the " + "ReplicaPlacer implementation. This class plugin is considered unstable, meaning the Kafka " + "community does not provide guarantees of compatibility or long-term stability. It is used " + "by the broker to determine thereplica placement of replicas when topics or partitions are created. This " + "configuration is intended for advanced use cases such as internal testing environments, " + "experimental feature development, performance evaluation, or benchmarking. Custom " + "implementations should be lightweight and efficient to avoid degrading controller performance" + " or impacting overall cluster stability."; |
The ReplicaPlacer interface has been updated to extend both Configurable and Closeable to support proper configuration and resource cleanup.
| Code Block | ||
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package org.apache.kafka.metadata.placement; /** * The interface which a Kafka replica placement policy must implement. */ @InterfaceStability.Unstable public interface ReplicaPlacer extends Configurable, Closeable { /** * Create a new replica placement. * * @param placement What we're trying to place. * @param cluster A description of the cluster we're trying to place in. * * @return A topic assignment. * * @throws InvalidReplicationFactorException If too many replicas were requested. */ TopicAssignment place( PlacementSpec placement, ClusterDescriber cluster ) throws InvalidReplicationFactorException; } |
The following classes should also be marked with @InterfaceStability.Unstable.
- ReplicaPlacer
- PartitionAssignment
TopicAssignment
PlacementSpec
DefaultDirProvider
ClusterDescriber
UsableBroker
Also move StripedReplicaPlacer into internal package `org.apache.kafka.metadata.placement.internal`, and add `package-info.java` into `org.apache.kafka.metadata.placement`
| Code Block | ||
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/**
* Provides Replica placer and related classes.
*/
package org.apache.kafka.metadata.placement; |
Compatibility, Deprecation, and Migration Plan
This KIP adds internal new config which doesn’t break compatibility.
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Add new test for new internal config internal.replica.placer.class.name
Rejected Alternatives
KIP-660: Pluggable ReplicaPlacer, but the proposal was ultimately rejected due to the following concerns:
Implementing an intelligent placement strategy may require access to the full cluster state, which could be prohibitively expensive in large deployments.
Such strategies could become overly complex and harder to maintain.
Slow or inefficient placement logic could block the controller thread, negatively impacting Kafka's overall stability.
Make replica.placer.class.name as an interanl config
- The advantage is that we are not required to maintain compatibility since it is not exposed to users.
- The downside is that most users would not be aware of the configuration at all.
- Making this configuration private will provide less opportunities to gather feedback from users.
Using Admin API for Post-Creation Reassignment
Users could create topics with default placement and then use kafka-reassign-partitions or Admin API to reassign partitions, but rejected due to the following concerns:
- Requires additional operational overhead and monitoring.
- Difficult to integrate with auto-topic creation scenarios.
Specifying Assignment During Topic Creation
Users could use Admin API's createTopics with explicit ReplicaAssignments when creating topics, but rejected due to the following concerns:
- Pushes complexity to client applications.
- Leads to inconsistent placement strategies across different clients.
- In internal scenarios where dynamic testing is required, manual assignment lacks flexibility.