Table of Contents

Goals

The main goal of this project is to have a thin consumer client design that can be easily adopted/reimplemented in non-Java languages. To achieve this we have decided to:

Move the group member management and offset management from the client side to the server side with a centralized coordination mechanism. By doing so we can completely remove ZK-dependency from the consumer clients. General design proposal can be found here, here and here.
Make the consumer client single-threaded with non-blocking API. Some discussions about this can be found here.

Besides this main goal we also want to add some new feature supports that we have seen while operating 0.8 and older versions. An in-comprehensive list below:

Manual partition assignment: instead of going through the centralized coordination process to get assigned consuming partitions, the consumers should be able to simply specify their target partitions and start consume right away without any group membership management.
Manual offset management: instead of using Kafka commit() call to manage the consumed offsets, consumers should be able to store/load their offsets outside Kafka clients and simply specify the starting offsets when consuming.

Note that pre-0.9, we support both of these use cases by providing a simple consumer and a zookeeper consumer (i.e. high-level consumer) interface, and users need to choose all-or-none for the functionalities; in 0.9 we will combine these two into one interface with more flexibility.

Consumer API

Here is the proposed consumer API interface:

Code Block

Consumer (Properties) {

  // Incrementally subscribe to a list of topics.
  // @throws SubscriptionNotValidException if the new subscription is not valid with existing subscriptions.
  void subscribe(String...) throws SubscriptionNotValidException;

  // Incrementally subscribe to a specified topic partition.
  // No group management will be invoked since assigned partitions have been specified.
  // @throws SubscriptionNotValidException if the new subscription is not valid with existing subscriptions.
  void subscribe(String, Int);

  // Incrementally subscribe to a specified topic partition starting at the given offset.
  // No group management will be invoked since assigned partitions have been specified.
  // @throws SubscriptionNotValidException if the new subscription is not valid with existing subscriptions.
  void subscribe(String, Int, Long);

  // Try to fetch messages from the topic/partitions it subscribed to. 
  // Return whatever messages are available to be fetched or empty after specified timeout.
  // @thorws InitOffsetNotKnownException if the starting offset for the assigned partitions is unknown.
  List<Record> poll(Long) throws InitOffsetNotKnownException;

  // Commit latest offsets for all partitions currently consuming from.
  // If the sync flag is set to true, commit call will be sync and blocking.
  // Otherwise the commit call will be async and best-effort.
  void commit(Boolean); 

  // Commit the specified offset for the specified partitions.
  // If the sync flag is set to true, commit call will be sync and blocking.
  // Otherwise the commit call will be async and best-effort.
  // @thorws InvalidPartitionsToCommitOffsetException if the group management has invoked, sync flag is true and the specified partitions do not belong to assigned ones.
  void commit(List[(String, Int, Long)], Boolean) throws InvalidPartitionsToCommitOffsetException;

  // Specify the fetch starting offset for the specified topic/partition.
  void position(List[(String, Int, Long)])

  // Get the currently consuming partitions.
  // Block wait if the current partitions are not known yet.
  List[(String, Int)] getPartitions();

  // Get the last committed offsets of the partitions currently consuming.
  // Block wait if the current partitions are not known yet.
  Map[(String, Int), Long] getOffsets() OffsetUnknownException;

  // Get the last committed offsets of the specified topic/partition.
  // @throws OffsetUnknownException if not offsets of the specified partitions have ever been committed.
  Long getOffset(String, Int) throws OffsetUnknownException;
  
  // --------- Call-back Below, not part of API ------------ //

  // Call-back function upon partition de-assignment.
  // Default implementation will commit offset depending on auto.commit config.
  void onPartitionDeassigned(List[(String, Int)]);

  // Call-back function upon partition re-assignment.
  // Default implementation will fetch starting offset depending on auto.commit config.
  void onPartitionAssigned(List[(String, Int)])
}

The Records returned by the poll() function will include metadata such as offset, partition, key and partition-key. This would also help removing the decompression/recompression in mirror maker (details can be found in KAFKA-1011).

Consumer Coordinator Overview

Each consumer group will be assigned a consumer coordinator responsible for its membership management and offset management. Each broker will host a consumer coordinator so that the management of consumer groups will be distributed across all brokers. We follow the in-built offset management design described here to assign coordinators based on the "offset" topic partition leadership. That is, an "offset" topic will be used to store the offsets sent from each consumer group, and the partition id is based on the consumer group names. The leader of the partition that a consumer group's offsets commit to will be the coordinator of that group.

Since all the brokers cache the leadership for all the topic partitions, all brokers will know the coordinator for any given consumer groups. Upon receiving any requests from a consumer, the coordinator will only serve it if it is the assigned coordinator of the specified group this consumer belongs to; otherwise the request will be rejected.

For each consumer group, the coordinator stores the following information:

1) For each consumer group it currently serve, the group metadata containing:

Its subscribed topic list.
Group configs, including session timeout, etc.
Consumer metadata for each consumer in the group.
Current offsets for each consumed topic/partition.
Partition ownership metadata, including the consumer-assigned-partitions map, current group generation number, etc.

2) For each existing topic, a list of consumer groups that are currently subscribing to it.

In addition, for each consumer group the coordinator also maintains the group config and partition ownership metadata in ZK as a json object. This node will be updated upon rebalance completion and read upon coordinator failover (details below).

Consumer Startup (Subscription Change)

On consumer startup, it will usually first try to subscribe to a list of topics.

If it does not subscribe to any topics, then poll() will always return empty set; if it has subscribed to specific topic/partitions, then it does not need to communicate with the coordinator but just start fetching data (will talk about how to start fetching data below).

Only if it has changed its topic subscription (including from an empty set on startup), it will need to coordinate with the coordinators. If consumer has not connected to the coordinator, it will first try to find the current coordinator and setup the connection.

Another note is that in this proposal we do not require consumer's client id in the config but leave it as an optional config, when it is not specified a default id of will be used, and if group management is invoked the coordinator assign consumer ids upon them successfully joining the group.

Coordinator Discovery

The coordinator discovery is through the coordinator request, which can be answered by any alive brokers and whose response will contain the coordinator id based on consumer group.

-----------------------------------------------------------------------------------

Any Broker (alive) <-- (find_coordinator) -- Consumer 1

-- (response) -->

<-- (find_coordinator) -- Consumer 2

-- (response) -->

-----------------------------------------------------------------------------------

FindCoordinatorRequest

WARN: This is an obsolete design. The design that's implemented in Kafka 0.9.0 is described in this wiki.

Motivation

The motivation for moving to a new set of consumer client APIs with broker side co-ordination is laid out here.

Consumer API

The proposed consumer APIs are here. Several API usage examples are documented here.

Consumer HowTo

This wiki has design details on the new consumer. This level of detail may be too verbose for people who are just trying to write a non-java consumer client using the new protocol. This wiki provides a step by step guide for writing a non-java 0.9 client.

Group management protocol

Rebalancing is the process where a group of consumer instances (belonging to the same group) co-ordinate to own a mutually exclusive set of partitions of topics that the group is subscribed to. At the end of a successful rebalance operation for a consumer group, every partition for all subscribed topics will be owned by a single consumer instance within the group. The way rebalancing works is as follows. Every broker is elected as the coordinator for a subset of the consumer groups. The co-ordinator broker for a group is responsible for orchestrating a rebalance operation on consumer group membership changes or partition changes for the subscribed topics. It is also responsible for communicating the resulting partition ownership configuration to all consumers of the group undergoing a rebalance operation.

Consumer

On startup or on co-ordinator failover, the consumer sends a ConsumerMetadataRequest to any of the brokers in the bootstrap.brokers list. In the ConsumerMetadataResponse, it receives the location of the co-ordinator for it's group.
The consumer connects to the co-ordinator and sends a HeartbeatRequest. If an IllegalGeneration error code is returned in the HeartbeatResponse, it indicates that the co-ordinator has initiated a rebalance. The consumer then stops fetching data, commits offsets and sends a JoinGroupRequest to it's co-ordinator broker. In the JoinGroupResponse, it receives the list of topic partitions that it should own and the new generation id for it's group. At this time, group management is done and the consumer starts fetching data and (optionally) committing offsets for the list of partitions it owns.
If no error is returned in the HeartbeatResponse, the consumer continues fetching data, for the list of partitions it last owned, without interruption.

Co-ordinator

In steady state, the co-ordinator tracks the health of each consumer in every group through it's failure detection protocol.
Upon election or startup, the co-ordinator reads the list of groups it manages and their membership information from zookeeper. If there is no previous group membership information, it does nothing until the first consumer in some group registers with it.
Until the co-ordinator finishes loading the group membership information for all groups that it is responsible for, it returns the CoordinatorStartupNotComplete error code in the responses of HearbeatRequests, OffsetCommitRequests and JoinGroupRequests. The consumer then retries the request after some backoff.
Upon election or startup, the co-ordinator also starts failure detection for all consumers in a group. Consumers that are marked dead by the co-ordinator's failure detection protocol are removed from the group and the co-ordinator triggers a rebalance operation for the consumer's group.
Rebalance is triggered by returning the IllegalGeneration error code in the HeartbeatResponse. Once all alive consumers re-register with the co-ordinator via JoinGroupRequests, it communicates the new partition ownership to each of the consumers in the JoinGroupResponse, thereby completing the rebalance operation.
The co-ordinator tracks the changes to topic partition changes for all topics that any consumer group has registered interest for. If it detects a new partition for any topic, it triggers a rebalance operation (as described in #5 above). It is currently not possible to reduce the number of partitions for a topic. The creation of new topics can also trigger a rebalance operation as consumers can register for topics before they are created.

Failure detection protocol

The consumer specifies a session timeout in the JoinGroupRequest that it sends to the co-ordinator in order to join a consumer group. When the consumer has successfully joined a group, the failure detection process starts on the consumer as well as the co-ordinator. The consumer initiates periodic heartbeats (HeartbeatRequest), every session.timeout.ms/heartbeat.frequency to the co-ordinator and waits for a response. If the co-ordinator does not receive a HeartbeatRequest from a consumer for session.timeout.ms, it marks the consumer dead. Similarly, if the consumer does not receive the HeartbeatResponse within session.timeout.ms, it assumes the co-ordinator is dead and starts the co-ordinator rediscovery process. The heartbeat.frequency is a consumer side config that determins the interval at which the consumer sends a heartbeat to the co-ordinator. The heartbeat.frequency puts a lower bound on the rebalance latency since the co-ordinator notifies a consumer regarding a rebalance operation through the heartbeat response. So, it is important to set it to a reasonably high value especially if the session.timeout.ms is relatively large. At the same time, care should be taken to not set the heartbeat.frequency too high since that would cause overhead due to request overload on the brokers. Here is the protocol in more detail -

After receiving a ConsumerMetadataResponse or a JoinGroupResponse, a consumer periodically sends a HeartbeatRequest to the coordinator every session.timeout.ms/heartbeat.frequency milliseconds.
Upon receiving the HeartbeatRequest, coordinator checks the generation number, the consumer id and the consumer group. If the consumer specifies an invalid or stale generation id, it send an IllegalGeneration error code in the HeartbeatResponse.
If the coordinator does not receive a HeartbeatRequest from a consumer at least once in session.timeout.ms, it marks the consumer dead and triggers a rebalance process for the group.
If the consumer does not receive a HeartbeatResponse from the coordinator after session.timeout.ms or finds the socket channel to the coordinator to be closed, it treats the coordinator as failed and triggers the co-ordinator re-discovery process.

Note that on coordinator failover, the consumers may discover the new coordinator before or after the new coordinator has finished the failover process including loading the consumer group metadata from ZK, etc. In the latter case, the new coordinator will just accept its heartbeat request as normal; in the former case, the new coordinator may reject its request, causing it to re-dicover the co-ordinator and re-connect again, which is fine. Also, if the consumer connects to the new coordinator too late, the co-ordinator may have marked the consumer dead and will be treat the consumer like a new consumer and trigger a rebalance.

State diagram

Consumer

Here is a description of the states -

Down - The consumer process is down

Startup up & discover co-ordinator - In this state, the consumer discovers the co-ordinator for it's group. The consumer sends a JoinGroupRequest (with no consumer id) once it discovers the co-ordinator. The JoinGroupRequest can receive InconsistentPartitioningStrategy error code if some consumers in the same group specify conflicting partition assignment strategies. It can receive an UnknownPartitioningStrategy error code if the friendly name of the strategy in the JoinGroupRequest is unknown to the brokers. In this case, the consumer is unable to join a group.

Part of a group - In this state, the consumer is part of a group if it receives a JoinGroupResponse with no error code, a consumer id and the generation id for it's group. In this state, the consumer sends a HeartbeatRequest. Depending on the error code received, it either stays in this state or moves to Stopped Consumption or Rediscover co-ordinator.

Re-discover co-ord - In this state, the consumer does not stop consumption but tries to re-discover the co-ordinator by sending a ConsumerMetadataRequest and waiting for a response as long as it gets one with no error code.

Stopped consumption - In this state, the consumer stops consumption and commits offsets, until it joins the group again

Image Added

Co-ordinator

Following is a state diagram that describes the state changes on the co-ordinator for a particular group.

Here is a description of the states -

Down - The co-ordinator is dead or demoted

Catch up - In this state, the co-ordinator is elected but not ready to serve requests

Ready - In this state, the newly elected co-ordinator has finished loading the group metadata for all groups that it is responsible for

Prepare for rebalance - In this state, the co-ordinator sends the IllegalGeneration error in the HeartbeatResponse for all consumers in the group and waits for the consumers to send it a JoinGroupRequest

Rebalancing - In this state, the co-ordinator has received a JoinGroupRequest from the consumers in the current generation and it increments the group generation id, assigns consumer ids where required and does the partition assignment

Steady - In the steady state, the co-ordinator accepts OffsetCommitRequests and heartbeats from all consumers in every group

Image Added

Consumer id assignment

After startup, a consumer learns it's consumer id in the very first JoinGroupResponse it receives from the co-ordinator. From that point onwards, the consumer must include this consumer id in every HeartbeatRequest and OffsetCommitRequest it sends to the co-ordinator. If the co-ordinator receives a HeartbeatRequest or an OffsetCommitRequest with a consumer id that is different from the ones in the group, it sends an UnknownConsumer error code in the corresponding responses.
The co-ordinator assigns a consumer id to a consumer on a successful rebalance and sends it in the JoinGroupResponse. The consumer can choose to include this id in every subsequent JoinGroupRequest as well until it is shutdown or dies. The advantage of including the consumer id in subsequent JoinGroupRequests is a lower latency on rebalance operations. When a rebalance is triggered, the co-ordinator waits for all consumers in the previous generation to send it a JoinGroupRequest. The way it identifies a consumer is by it's consumer id. If the consumer chooses to send JoinGroupRequest with empty consumer id, the co-ordinator waits a full session.timeout.ms before it proceeds with the rest of the rebalance operation. It does this since there is no way to map the incoming JoinGroupRequest with a consumer in the absence of a consumer id. This puts a lower bound on the rebalance latency (session.timeout.ms). On the other hand, if the consumer sends it's consumer id on subsequent JoinGroupRequests, the co-ordinator can immediately identify the consumers and proceed with a rebalance once all the known consumers have sent a JoinGroupRequest.
The co-ordinator does consumer id assignment after it has received a JoinGroupRequest from all existing consumers in a group. At this point, it assigns a new id <group>-<uuid> to every consumer that did not have a consumer id in the JoinGroupRequest. The assumption is that such consumers are either newly started up or choose to not send the previously assigned consumer id.
If a consumer id is specified in the JoinGroupRequest but it does not match the ids in the current group membership, the co-ordinator sends an UnknownConsumer error code in the JoinGroupResponse and prevents the consumer from joining the group. This does not cause a rebalance operation for the rest of the consumers in the group, but also does not allow such a consumer to join an existing group.

Memory management

TBD

Request formats

For each consumer group, the coordinator stores the following information:

1) For each consumer group, the group metadata containing:

List of topics the group subscribes to
Group configs, including session timeout, etc.
Consumer metadata for each consumer in the group. Consumer metadata includes hostname and consumer id.
Current offsets for each consumed topic/partition.
Partition ownership metadata, including the consumer-assigned-partitions map.

2) For each existing topic, a list of consumer groups that are currently subscribing to it.

It is assumed that all the following requests and responses have the common header. So the fields mentioned exclude the ones in the header.

ConsumerMetadataRequest

Code Block
{ GroupId
Code Block
{ Version => String }

ConsumerMetadataResponse

Code Block
{int16 CorrelationId => int64 ClientId ErrorCode => Stringint16 GroupIdCoordinator => StringBroker }

JoinGroupRequest

FindCoordinatorResponse

Code Block
{ GroupId

...

=>

...

String
  SessionTimeout         	  => int32

...

Topics                 	  =>

...

[String]
  ConsumerId

...

=>

...

 String 
  PartitionAssignmentStrategy => String
 }

JoinGroupResponse

Code Block
{ ErrorCode => int16 GroupGenerationId => int32 ConsumerId => String PartitionsToOwn => [TopicName [Partition]] } TopicName => String Partition => int32

HeartbeatRequest

Code Block
{ GroupId => String GroupGenerationId => int32 ConsumerId => String }

HeartbeatResponse

Code Block
{ ErrorCode => int16 }

OffsetCommitRequest (v1)

Code Block

OffsetCommitRequest => ConsumerGroup GroupGenerationId ConsumerId [TopicName [Partition Offset TimeStamp Metadata]]
  ConsumerGroup => string
  GroupGenerationId => int32
  ConsumerId => String
  TopicName => string
  Partition => int32
  Offset => int64
  TimeStamp => int64
  Metadata => string

Configs

Server side configs

This list is still in progress

max.session.timeout - The session timeout for any group should not be higher than this value to reduce overhead on the brokers. If it does, the broker sends a SessionTimeoutTooHigh error code in the JoinGroupResponse

partition.assignment.strategies - Comma separated list of properties that map the strategy's friendly name to the class that implements the strategy. This is used for any strategy implemented by the user and released to the Kafka cluster. By default, Kafka will include a set of strategies that can be used by the consumer. The consumer specifies a partitioning strategy in the JoinGroupRequest. It must use the friendly name of the strategy or it will receive an UnknownPartitionAssignmentStrategyException

Client side configs

The client side configs can be found here

Wildcard Subscription

With wildcard subscription (for example, whitelist and blacklist), the consumers are responsible to discover matching topics through topic metadata request. That is, its topic metadata request will contain an empty topic list, whose response then will return the partition info of all topics, it will then filter the topics that match its wildcard expression, and then update the subscription list using the subscribe() API. Again, if the subscription list has changed from the previous value, it will trigger rebalance for the consumer group by sending the JoinGroupRequest during the next poll().

Interesting scenarios to consider

Co-ordinator failover or connection loss to the co-ordinator

On co-ordinator failover, the controller elects a new leader for a subset of the consumer groups affected due to the co-ordinator failure. As part of becoming the leader for a subset of the offset topic partitions, the co-ordinator reads metadata for each group that it is responsible for, from zookeeper. The metadata includes the group's consumer ids, the generation id and the subscribed list of topics. Until the co-ordinator has read all metadata from zookeeper, it returns the CoordinatorStartupNotComplete error code in HeartbeatResponse. It is illegal for a consumer to send a JoinGroupRequest during this time, so the error code returned to such a consumer is different (probably IllegalProtocolState).
If a consumer sends a ConsumerMetadataRequest to a broker before the broker has received the updated group metadata through the UpdateMetadataRequest from the controlller, the ConsumerMetadataResponse will return stale information about the co-ordinator. The consumer will receive NotCoordinatorForGroup error code on the heartbeat/commit offset responses. On receiving the NotCoordinatorForGroup error code, the consumer backs off and resends the ConsumerMetadataRequest.
The consumer does not stop fetching data during the co-ordinator failover and re-discovery process.

Partition changes for subscribed topics

The co-ordinator for a group detects changes to the number of partitions for the subscribed list of topics.
The co-ordinator then marks the group ready for rebalance and sends the IllegalGeneration error code in the HeartbeatResponse. The consumer then stops fetching data, commits offsets and sends a JoinGroupRequest to the co-ordinator.
The co-ordinator waits for all consumers to send it the JoinGroupRequest for the group. Once it receives all expected JoinGroupRequests, it increments the group's generation id in zookeeper, computes the new partition assignment and returns the updated assignment and the new generation id in the JoinGroupResponse. Note that the generation id is incremented even if the group membership does not change.
On receiving the JoinGroupResponse, the consumer stores the new generation id and consumer id locally and starts fetching data for the returned set of partitions. The subsequent requests sent by the consumer to the co-ordinator will use the new generation id and consumer id returned by the last JoinGroupResponse.

Offset commits during rebalance

If a consumer receives an IllegalGeneration error code, it stops fetching and commits existing offsets before sending a JoinGroupRequest to the co-ordinator.
The co-ordinator checks the generation id in the OffsetCommitRequest and rejects it if the generation id in the request is higher than the generation id on the co-ordinator. This indicates a bug in the consumer code.
The co-ordinator does not allow offset commit requests with generation ids older than the current group generation id in zookeeper either. This constraint is not a problem during a rebalance since until all consumers have sent a JoinGroupRequest, the co-ordinator does not increment the group's generation id. And from that point until the point the co-ordinator sends a JoinGroupResponse, it does not expect to receive any OffsetCommitRequests from any of the consumers in the group in the current generation. So the generation id on every OffsetCommitRequest sent by the consumer should always match the current generation id on the co-ordinator.
Another case worth discussing is when a consumer goes through a soft failure e.g. a long GC pause during a rebalance. If a consumer pauses for more than session.timeout.ms, the co-ordinator will not receive a JoinGroupRequest from such a consumer within session.timeout.ms. The co-ordinator marks the consumer dead and completes the rebalance operation by including the consumers that sent the JoinGroupRequest in the new generation.

Heartbeats during rebalance

Consumer periodically sends a HeartbeatRequest to the coordinator every session.timeout.ms/hearbeat.frequency milliseconds. If the consumer receives the IllegalGeneration error code in the HeartbeatResponse, it stops fetching, commits offsets and sends a JoinGroupRequest to the co-ordinator. Until the consumer receives a JoinGroupResponse, it does not send any more HearbeatRequests to the co-ordinator.
A higher heartbeat.frequency ensures lower latency on a rebalance operation since the co-ordinator notifies a consumer of the need to rebalance only on a HeartbeatResponse.
The co-ordinator pauses failure detection for a consumer that has sent a JoinGroupRequest until a JoinGroupResponse is sent out. It restarts the hearbeat timer once the JoinGroupResponse is sent out and marks a consumer dead if it does not receive a HeartbeatRequest from that time for another session.timeout.ms milliseconds. The reason the co-ordinator stops depending on heartbeats to detect failures during a rebalance is due to a design decision on the broker's socket server - Kafka only allows the broker to read and process one outstanding request per client. This is done to make it simpler to reason about ordering. This prevents the consumer and broker from processing a heartbeat request at the same time as a join group request for the same client. Marking failures based on JoinGroupRequest prevents the co-ordinator from marking a consumer dead during a rebalance operation. Note that this does not prevent the rebalance operation from finishing if a consumer goes through a soft failure during a rebalance operation. If the consumer pauses before it sends a JoinGroupRequest, the co-ordinator will mark it dead during the rebalance and complete the rebalance operation by including the rest of the consumers in the new generation. If a consumer pauses after it sends a JoinGroupRequest, the co-ordinator will send it the JoinGroupResponse assuming the rebalance completed successfully and will restart it's heartbeat timer. If the consumer resumes before session.timeout.ms, consumption starts normally. If the consumer pauses for session.timeout.ms after that, then it is marked dead by the co-ordinator and it will trigger a rebalance operation.
The co-ordinator returns the new generation id and consumer id only in the JoinGroupResponse. Once the consumer receives a JoinGroupResponse, it sends the next HeartbeatRequest with the new generation id and consumer id.

Co-ordinator failure during rebalance

A rebalance operation goes through several phases -

Co-ordinator receives notification of a rebalance - either a zookeeper watch fires for a topic/partition change or a new consumer registers or an existing consumer dies.
Co-ordinator initiates a rebalance operation by sending an IllegalGeneration error code in the HeartbeatResponse
Consumers send a JoinGroupRequest
Co-ordinator increments the group's generation id in zookeeper and writes the new partition ownership in zookeeper
Co-ordinator sends a JoinGroupResponse

Co-ordinator can fail at any of the above phases during a rebalance operation. This section discusses how the failover handles each of these scenarios.

If the co-ordinator fails at step #1 after receiving a notification but not getting a chance to act on it, the new co-ordinator has to be able to detect the need for a rebalance operation on completing the failover. As part of failover, the co-ordinator reads a group's metadata from zookeeper, including the list of topics the group has subscribed to and the previous partition ownership decision. If the # of topics or # of partitions for the subscribed topics are different from the ones in the previous partition ownership decision, the new co-ordinator detects the need for a rebalance and initiates one for the group. Similarly if the consumers that connect to the new co-ordinator are different from the ones in the group's generation metadata in zookeeper, it initiates a rebalance for the group.
If the co-ordinator fails at step #2, it might send a HeartbeatResponse with the error code to some consumers but not all. Similar to failure #1 above, the co-ordinator will detect the need for rebalance after failover and initiate a rebalance again. If a rebalance was initiated due to a consumer failure and the consumer recovers before the co-ordinator failover completes, the co-ordinator will not initiate a rebalance. However, if any consumer (with an empty or unknown consumer id) sends it a JoinGroupRequest, it will initiate a rebalance for the entire group.
If a co-ordinator fails at step #3, it might receive JoinGroupRequests from only a subset of consumers in the group. After failover, the co-ordinator might receive a HeartbeatRequest from all alive consumers OR JoinGroupRequests from some. Similar to #1, it will trigger a rebalance for the group.
If a co-ordinator fails at step #4, it might fail after writing the new generation id and group membership in zookeeper. The generation id and membership information is written in one atomic zookeeper write operation. After failover, the consumer will send HeartbeatRequests to the new co-ordinator with an older generation id. The co-ordinator triggers a rebalance by returning an IllegalGeneration error code in the response that causes the consumer to send it a JoinGroupRequest. Note that this is the reason why it is worth sending both the generation id as well as the consumer id in the HeartbeatRequest and OffsetCommitRequest
If a co-ordinator fails at step #5, it might send the JoinGroupResponse to only a subset of the consumers in a group. A consumer that received a JoinGroupResponse will detect the failed co-ordinator while sending a heartbeat or committing offsets. At this point, it will discover the new co-ordinator and send it a heartbeat with the new generation id. The co-ordinator will send it a HeartbeatResponse with no error code at this point. A consumer that did not receive a JoinGroupResponse will discover the new co-ordinator and send it a JoinGroupRequest. This will cause the co-ordinator to trigger a rebalance for the group.

Slow consumers

Slow consumers can be removed from the group by the co-ordinator if it does not receive a heartbeat request for session.timeout.ms. Typically, consumers can be slow if their message processing is slower than session.timeout.ms, causing the interval between poll() invocations to be longer than session.timeout.ms. Since a heartbeat is only sent during the poll() invocation, this can cause the co-ordinator to mark a slow consumer dead. Here is how the co-ordinator handles a slow consumer -

If the co-ordinator does not receive a heartbeat for session.timeout.ms, it marks the consumer dead and breaks the socket connection to it.
At the same time, it triggers a rebalance by sending the IllegalGeneration error code in the HeartbeatResponse to the rest of the consumers in the group.
If the slow consumer sends a HeartbeatRequest before the co-ordinator receives a HeartbeatRequest from any of the rest of the consumers, it cancels the rebalance attempt and sends the HeartbeatResponses with no error code
If not, the co-ordinator proceeds with the rebalance and sends the slow consumer the IllegalGeneration error code as well.
Since the co-ordinator only waits for JoinGroupRequest from the "alive" consumers, it calls the rebalance complete once it receives join requests from the other consumers. If the slow consumer also happens to send a JoinGroupRequest, the co-ordinator includes it in the current generation if it has not already sent a JoinGroupResponse excluding this slow consumer.
If the co-ordinator has already sent a JoinGroupResponse, it let's the current rebalance round complete before triggering another rebalance attempt right after.
If the current round takes long, the slow consumer's JoinGroupResponse times out and it re-discovers the co-ordinator and resends the JoinGroupRequest to the co-ordinator.

Consumer (re)Join-Group

Upon successfully connects to the coordinator, the consumer will either try to (re-)join the group if 1) it has not own any partitions, or 2) its subscription has changed, or 3) its heartbeat responses has received an error. Otherwise it will just keep heartbeating with the coordinator (we will talk about this later). The consumer will try to join the group by doing the following:

1) Drop any fetched data, stop sending any fetch requests to brokers.

2) Release any assigned partition ownership by calling onPartitionDeassigned function.

3) Send a join group request to the coordinator and block waiting on the response.

Upon receiving a join group request, the coordinator will trigger a rebalance on the group this consumer belongs to.

When the rebalance finishes, it will send the response back to the consumer with the newly assigned partitions, the new consumer id along with the generation number back to the consumer.

------------------------------------------------------------------------------------

Coordinator <-- (join) -- Consumer 1 (alive)

(received a join request on consumer 1, rebalance)

...

(upon rebalance finish)

-- (response) -->

---------------------------------------------------------------------------------------

JoinGroupRequest

Code Block
{ Version => int16 CorrelationId => int64 GroupId => String ConsumerAddr => String SessionTimeout => int64 Subscribing => [String] }

JoinGroupResponse

Code Block
{ Version => int16 CorrelationId => int64 ErrorCode => int16 Generation => int16 GroupId => String ConsumerId => String PartitionsToOwn => [<TopicAndPartition>] }

Note that the assigned consumer client id is assigned by the coordinator will also be used in heartbeat protocol and offset management talked below.

Coordinator Startup (Coordinator Failover)

Coordinators will be constructed upon broker startup, and initialized with empty consumer groups. There are two cases a new consumer group can be created on the coordinator:

1) When a first request is received from one of the consumers in this group, the coordinator need to create this group after validating by the group name that it is the assigned coordinator.

2) Since the assignment of coordinators can change as the "offset" topic partition leaders change (mainly due to broker down), they also have to take over existing consumer groups upon coordinator failovers.

The only difference is that for 1) the coordinator will immediately trigger a rebalance for this newly created group, whereas for 2) the coordinator needs to load its current config and ownership information from ZK but do not necessarily trigger the rebalance.

Consumer Fetching Data

As in the new producer, consumers will periodically send topic metadata request to the available brokers to find the leader of its assigned partitions. Upon 1) receiving an error while fetching data and 2) receiving a join response from the coordinator, it will also force a topic metadata refresh.

To fetch data, consumers will issue fetch requests to the known leaders of the assigned partitions with a selector, and the poll function will return data from all the readable channels in the selector.

Wildcard Subscription Handling

With wildcard subscription (for example, whitelist and blacklist), the consumers are responsible to discover matching topics through topic metadata request. That is, its topic metadata request will contain an empty topic list, whose response then will return the partition info of all topics, it will then filter the topics that match its wildcard expression, and then update the subscription list. Again, if the subscription list has changed from the previous values, it will start the consumer re-join group procedure.

Failure Detection

When the consumer has succesfully joined the group, it will keep sending the heartbeat request to the coordinator, this protocol is used both for consumer failure detection (by coordinator) and coordinator failure detection (by consumer).

Heartbeat Protocol

1) Consumers periodically send heartbeat request to the coordinator based on every session_timeout / heartbeat_frequency (which is an integer > 1).

2) Upon receiving the heartbeat request, coordinator checks the generation number and the consumer id, if they are not validate (i.e., consumer id not assigned before, or generation number is smaller than current value), send an error response; otherwise send a normal response.

3) If coordinator has not heard from a consumer after session_timeout, treat the consumer as failed.

4) If consumer has not heart from the coordinator after session timeout, treat the coordinator as failed.

5) If consumer found the channel with the coordinator has closed, treat the coordinator as failed.

Note that on coordinator failover, the consumers may discover the new coordinator before or after the new coordinator has finsihed the failover process including loading the consumer group metadata from ZK, etc. In the latter case, the new coordinator will just accept its ping request as normal; in the former case, the new coordinator may reject its request, causing it to re-dicover coordinators and re-connect again, which is fine. Also, if the consumer connects to the new coordinator too later, it may already be expired by the new coordinator and will hence be treated as a new consumer, which is also fine.

-----------------------------------------------------------------------------------

Coordinator <-- (ping) -- Consumer 1 (alive)

-- (response) -->

<-- (ping) -- Consumer 2 (alive)

-- (response) -->

-----------------------------------------------------------------------------------

Coordinator <-- (ping) -- Consumer 1 (alive)

-- (response) -->

(Have not heard from consumer 2, it must have failed) Consumer 2 (failed)

-----------------------------------------------------------------------------------

Coordinator (failed) <-- (ping) -- Consumer 1 (alive)

(Have not heard back from coordinator, it must have failed)

<-- (ping) -- Consumer 2 (alive)

(Have not heard back from coordinator, it must have failed)

-----------------------------------------------------------------------------------

Coordinator (crashed) <-- X -- Consumer 1 (alive)

(Broken pipe from coordinator, it must have failed)

<-- X -- Consumer 2 (alive)

(Broken pipe from coordinator, it must have failed)

------------------------------------------------------------------------------------------------

PingRequest

Code Block
{ Version => int16 CorrelationId => int64 GroupId => String ConsumerId => String }

PingResponse

Code Block
{ Version => int16 CorrelationId => int64 ErrorCode => int16 }

Consumer Failure Handling

When the coordinator thinks a consumer has failed, it will do the following:

1) Remove the consumer from the group metadata.

2) Trigger the rebalance process.

Coordinator Failure Handling

When the consumer thinks its current coordinator has failed, it will do the following:

1) Discover the new coordinator information from the existing known brokers through the find coordinator requests.

2) Set up the connection to the new coordinator.

3) Start sending heartbeats to the new coordinator.

------------------------------------------------------------------------------------

Coordinator (failed) <-- (ping) -- Consumer 1 (alive)

(Have not heard back from coordinator, try to reconnect to the new coordinator)

<-- (ping) -- Consumer 2 (alive)

(Have not heard back from coordinator, try to reconnect to the new coordinator)

Broker (alive) <-- (find_coordinator) -- Consumer 1

-- (response) -->

<-- (find_coordinator) -- Consumer 2

-- (response) -->

Coordinator (new) <-- (ping) -- Consumer 1 (alive)

-- (response) -->

<-- (ping) -- Consumer 2 (alive)

-- (response) -->

-------------------------------------------------------------------------------------------

Consumer Group Rebalance

The coordinator will trigger rebalance under the following conditions:

It found a consumer has failed.
It received a join request from a (possibly unknown) consumer.
It found a partition change on the topics this group is subscribing from.

Rebalance Process: Option 1

On group rebalance, the coordinator will first sends a error code indicating a rebalance in its responses to all the consumers.

Upon receiving the error code, consumer should stop fetching from its current partition leaders, call onPartitionDeassigned(), and then sends a join request to the coordinator.
Upon receiving a join request, coordinator checks if the specified group has already exist.
1. If yes, hold the request and wait for the join requests from all the consumers within the group.
2. If not, adds the group, and do not need to wait for any more join request and directly proceed to the next step.
Coordinator calculates the partition assigned along with the new generation number and send it back in the join response.
If some consumer's join request has not been received after session timeout, remove this consumer and re-trigger the rebalance by sends the join responses to rest consumers.
Upon receiving the normal join response, consumers call onPartitionAssigned() and start fetching.
If receiving error join response, consumer check if it is fatal; if so throw exceptions, otherwise re-send the join request.

Take the rebalance procedure upon new consumer startup for example:

---------------------------- 1 -------------------------------------------------------------------------------------

<-- (join) -- Consumer 3 (new)

Coordinator <-- (ping) -- Consumer 1 (alive)

-- (rebalance) -->

<-- (ping) -- Consumer 2 (alive)

-- (rebalance) -->

--------------------------- 2/3 -------------------------------------------------------------------------------------

(wait for response) Consumer 3 (new)

Coordinator Consumer 1 (alive)

(stop fetching)

(call onPartitionDeassigned)

<-- (join) --

Consumer 2 (alive)

(stop fetching)

(call onPartitionDeassigned)

<-- (join) --

--------------------------- 3/5 -------------------------------------------------------------------------------------

Coordinator (calculate new assignment)

-- (response) --> Consumer 3 (new)

(call onPartitionAssigned)

(start fetching)

-- (response) --> Consumer 1 (alive)

(call onPartitionAssigned)

(start fetching)

...

(call onPartitionAssigned)

(start fetching)

--------------------------- 4/6 -------------------------------------------------------------------------------------

Coordinator (have not heard from Consumer 2, retry rebalance)

-- (retry rebalance) --> Consumer 3 (new)

<-- (join) --

-- (retry rebalance) --> Consumer 1 (alive)

<-- (join) --

<-- X --> Consumer 2 (failed)

-----------------------------------------------------------------------------------------------------------------

Consumer's logic is summarized as:

-----------------------------------------------------------------------------------------------------------------

(Re)Start:

On 1) start-up, 2)subcription-change, 3) heart-beat fail, 4) coordinator fail, sends a join to the coordinator (if it is not known first find it through metadata).

Join group:

Upon receive join response, if it is normal record the sequence number and assignment and start consuming; otherwise retry or fail-fatally based on error code.

Heart beat:

Periodically send ping to coordinator, and if error received goes to the "start" step.

-----------------------------------------------------------------------------------------------------------------

The pros of this design would be avoiding unnecessary rebalances on coordinator failover, the cons is mainly at the fact that rebalance latency is lower-bounded by the ping frequency.

Another approach would be trigger the rebalance by closing the socket:

Rebalance Process: Option 2

On group rebalance, the coordinator will close sockets to all consumers (probably except the one which has sent him a join request).

Upon getting a broken pipe from the current coordinator, consumer should stop fetching from its current partition leaders, call onPartitionDeassigned().
It then find the new coordinator through metadata request, and send a join request to the new coordinator.
Upon receiving join request from all the consumers within the group, coordinator calculates the partition assigned along with the new generation number and send it back in the join response.
Upon receiving a join request from an unknown group, immediately calculates the partition assigned (without waiting for any new comers).

Consumer's logic is similar to option 2 except that consumer do not need to handle heartbeat-failure case, since it is merged into coordinator-failure: the key here is to enforce a rebalance to consumers as coordinator failures.

This can lift the lower bound of the rebalance latency on ping frequency, but will require more one metadata request along with unnecessary rebalances on coordinator failover (cause they are now treated as one scenario).

Offset Management

Commit Offset

Upon receiving the commit offset request, the coordinator checks if the consumer is 1) within the group specified, 2) owns the partitions it commit offsets to, and 3) has the correct generation number. If yes append the offset entry to the corresponding log, otherwise rejects the request.

OffsetCommitRequest

Code Block
{ Version => int16 CorrelationId => int64 GroupId => String ConsumerId => String Generation => int16 Offsets => [TopicAndPartition -> OffsetAndError] }

OffsetCommitResponse

Code Block
{ Version => int16 CorrelationId => int64 responses => [TopicAndPartition -> int16] // error code for each partition }

Fetch Offset

Fetch offset request is also handled by the coordinator.

Upon receiving the fetch offset request, the coordinator checks if the consumer within the group specified. If yes returns the current offset, otherwise rejects the request.

Upon receiving a reject response from the coordinator, the consumer will try to connect to the new coordinator (i.e., set up the connection, send heartbeat and get valid response) and then retry.

OffsetFetchRequest

Code Block
{ Version => int16 CorrelationId => int64 GroupId => String ConsumerId => String Generation => int16 partitions => [TopicAndPartition] }

OffsetFetchResponse

Code Block
{ Version => int16 CorrelationId => int64 offsets => [TopicAndPartition -> OffsetAndError] }

Consumer Architecture

API Implementation

Code Block
subscribe (subscription): 1. Check if the new subscription is valid with the old subscription: 1.1. If yes change the subscription and return. 1.2. Otherwise throw SubscriptionNotValidException.

Code Block

poll (timeout):
 
   1. Check if the cluster metadata needs to be refreshed, if yes send metadata request.

   2. Check if the subscription list is empty, if yes throw SubscriptionIsEmptyException.

   3. Check if the subscription list is topic-based:
 
   3.1. If not, call fetch(). // no need to talk to coordinator

   3.2. If yes, first call coordinate() then call fetch()

Code Block
commit(sync): 1. Call coordinate(). 2. Send commit offset to coordinator, based on sync block wait on response or not.

Code Block

getPartition:

   1. Check if the subscription list is empty, if yes throw SubscriptionIsEmptyException

   2. If the partition info is not known, call coordinate()

   3. Return partitions info.


getOffset(s):

   1. Check if the subscription list is empty, if yes throw SubscriptionIsEmptyException

   2. If the partition info is not known, call coordinate()

   3. If the offset info is not known, based on kafka.offset.manage send getOffset to coordinator or throw InvalidPartitionsToGetOffsetException

Code Block

fetch:
 
   1. Select-now on readable channels to get all available responses, for each response:

   1.1. If it is fetch-response, store the fetched-data.

   1.2. If it is metadata-response, process it and check if there is topic-change:

   1.2.1. If yes, update the subscription list, and return immediately with stored data.

   2. If there is no available data after step 1.
 
   3. If there is no readable channels, check if the offset is known.

   3.1. If not throw ConsumeInitOffsetNotKnownException.

   3.2. Otherwise send the fetch request to leader and timeout-select.

Code Block

coordinate:
 
   1. Check if the coordinator channel has been setup and not closed, and if subscription list has not changed. If not: 

   1.1. Block wait on getting the coordinator metadata.

   1.2. call onPartitionDeassignment().

   1.3. Send the registerConsumer to coordinator, set up the channel and block wait on registry response.
 
   1.3.a.1 The registerConsumer response contain member info and partition info, call partitionsToConsume to get the owned partitions.

   1.3.a.2 Send the partitions to consume info and get confirmed from the coordinator. // two round trips
 
   1.3.b. The registerConsumer response contain partition assignment from the coordinator. // one round trip
 
   1.4. and call onPartitionAssigned().

   2. If yes, check if heartbeat period has reached, if yes, send a ping to coordinator.

Open Questions

Apart with the above proposal, we still have some open questions that worth discuss:

coordinate/deserialization/decompress procedures need to be interruptible on timeout?
getOffsets and getPartitions be blocking?Should coordinator use its own socket server or use broker's socket server? Although the proposal suggests former we can think about this more.
Should we allow consumers from the same group to have different session timeout? If yes when do we reject a consumer registration because of its proposed session timeout?
Should we allow consumers from the same group have specific fixed subscribing topic partitions (G5)? If yes when do we reject a consumer registration with its subscribed topic partitions?
Should we provide tools to delete topics? If yes, how will this affect coordinator's topic change logic?
Should we do de-serialization/compression in fetcher thread or user thread? Although the proposal suggests de-serialization in user thread and de-compression in fetcher thread (or deserialization/compression all in client thread if we are following Option 1.a) we can still think about this more.
Do we allow to call subscribe multiple times during its life time? This is related to G5.a
Do we allow users to specify the offsets in commit() function call, and explicitly get last committed offset? This is related to G6.a
Would we still keep a zookeeper string in consumer properties for consumer to read the bootstrap broker list as an alternative to the broker list property?
Shall we try to avoid unnecessary rebalances on coordinator failover? In the current proposal upon coordinator failover the consumers will re-issue registration requests to the new coordinator, causing the new coordinator to trigger rebalance that is unnecessary.
Shall we restrict commit offset request to only for the client's own assigned partitions? For some use cases such as clients managing their offsets themselves and only want to call commit offset once on startup, this might be useful.
Shall we avoid request forwarding for option 2.b? One way to do that is let consumer remember two coordinators, and upon receiving stop fetching from group management coordinator, send a commit offset request to offset management coordinator and wait on response, and then respond to the stop fetching request.

...

Space shortcuts

Child pages

Page History

Versions Compared

Old Version 30

New Version Current

Key

Goals

Consumer API

Consumer Coordinator Overview

Consumer Startup (Subscription Change)

Coordinator Discovery

WARN: This is an obsolete design. The design that's implemented in Kafka 0.9.0 is described in this wiki.

Motivation

Consumer API

Consumer HowTo

Group management protocol

Consumer

Co-ordinator

Failure detection protocol

State diagram

Consumer

Co-ordinator

Consumer id assignment

Memory management

Request formats

ConsumerMetadataRequest

ConsumerMetadataResponse

JoinGroupRequest

JoinGroupResponse

HeartbeatRequest

HeartbeatResponse

OffsetCommitRequest (v1)

Configs

Server side configs

Client side configs

Wildcard Subscription

Interesting scenarios to consider

Co-ordinator failover or connection loss to the co-ordinator

Partition changes for subscribed topics

Offset commits during rebalance

Heartbeats during rebalance

Co-ordinator failure during rebalance

Slow consumers

Consumer (re)Join-Group

Coordinator Startup (Coordinator Failover)

Consumer Fetching Data

Wildcard Subscription Handling

Failure Detection

Heartbeat Protocol

Consumer Failure Handling

Coordinator Failure Handling

Consumer Group Rebalance

Rebalance Process: Option 1

Rebalance Process: Option 2

Offset Management

Commit Offset

OffsetCommitRequest

OffsetCommitResponse

Fetch Offset

OffsetFetchRequest

OffsetFetchResponse

Consumer Architecture

API Implementation

Open Questions