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https://issues.apache.org/jira/browse/KAFKA-12463?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Chris Egerton updated KAFKA-12463:
----------------------------------
Description:
Kafka consumers have a pluggable [partition assignment
interface|https://kafka.apache.org/27/javadoc/org/apache/kafka/clients/consumer/ConsumerPartitionAssignor.html]
that comes with several out-of-the-box implementations including the
[RangeAssignor|https://kafka.apache.org/27/javadoc/org/apache/kafka/clients/consumer/RangeAssignor.html],
[RoundRobinAssignor|https://kafka.apache.org/27/javadoc/org/apache/kafka/clients/consumer/RoundRobinAssignor.html],
[StickyAssignor|https://kafka.apache.org/27/javadoc/org/apache/kafka/clients/consumer/StickyAssignor.html],
and
[CooperativeStickyAssignor|https://kafka.apache.org/27/javadoc/org/apache/kafka/clients/consumer/CooperativeStickyAssignor.html].
If no partition assignor is configured with a consumer, the {{RangeAssignor}}
is used by default. Although there are some benefits to this assignor including
stability of assignment across generations and simplicity of design, it comes
with a major drawback: the number of active consumers in a group is limited to
the number of partitions in the topic(s) with the most partitions. For an
example of the worst case, in a consumer group where every member is subscribed
to ten topics that each have one partition, only one member of that group will
be assigned any topic partitions.
This can end up producing counterintuitive and even frustrating behavior when a
sink connector is brought up with N tasks to read from some collection of
topics with a total of N topic partitions, but some tasks end up idling and not
processing any data.
h3. Proposed Change
*NOTE: Until/unless KAFKA-12477 is addressed, the approach outlined below will
not work as consumers will still perform eager rebalancing as long as at least
one of the partition assignors they are configured with does not support
cooperative rebalancing. KAFKA-12487 should also be addressed before
configuring any Connect worker to use the {{CooperativeStickyAssignor}} for any
sink connectors.*
[KIP-429|https://cwiki.apache.org/confluence/display/KAFKA/KIP-429%3A+Kafka+Consumer+Incremental+Rebalance+Protocol]
introduced the {{CooperativeStickyAssignor}}, which seeks to provide a stable
assignment across generations wherever possible, provide the most even
assignment possible (taking into account possible differences in subscriptions
across consumers in the group), and allow consumers to continue processing data
during rebalance. The documentation for the assignor states that "Users should
prefer this assignor for newer clusters."
We should alter the default consumer configuration for sink tasks to use the
new {{CooperativeStickyAssignor}}. In order to do this in a
backwards-compatible fashion that also enables rolling upgrades, this should be
implemented by changing the {{Worker}} to set the following on the consumer
configuration created for each sink connector task:
{code:java}
partition.assignment.strategy=org.apache.kafka.clients.consumer.CooperativeStickyAssignor,org.apache.kafka.clients.consumer.RangeAssignor
{code}
This way, consumer groups for sink connectors on Connect clusters in the
process of being upgraded will continue to use the {{RangeAssignor}} until all
workers in the cluster have been upgraded, and then will switch over to the new
{{CooperativeStickyAssignor}} automatically. But, this setting will be
overwritten by any user-specified {{consumer.partition.assignment.strategy}}
property in the worker configuration, and by any user-specified
{{consumer.override.partition.assignment.strategy}} property in a sink
connector configuration when per-connector client overrides is enabled in the
worker config with {{connector.client.config.override.policy=ALL}}.
This improvement is viable as far back as -2.3- 2.4, when the
{{CooperativeStickyAssignor}} was introduced, but given that it is not a bug
fix, should only be applied to the Connect framework in an upcoming minor
release.
h3. Manually setting the partition assignment strategy
There is a simple workaround to achieve the same behavior in AK releases 2.4
and later that don't also include this improvement: either set a value for the
{{consumer.partition.assignment.strategy}} property in the *worker
configuration, or* set a value for the
{{consumer.override.partition.assignment.strategy}} property in one or more
*connector configurations* when per-connector client overrides is enabled in
the worker config with {{connector.client.config.override.policy=ALL}}.
was:
Kafka consumers have a pluggable [partition assignment
interface|https://kafka.apache.org/27/javadoc/org/apache/kafka/clients/consumer/ConsumerPartitionAssignor.html]
that comes with several out-of-the-box implementations including the
[RangeAssignor|https://kafka.apache.org/27/javadoc/org/apache/kafka/clients/consumer/RangeAssignor.html],
[RoundRobinAssignor|https://kafka.apache.org/27/javadoc/org/apache/kafka/clients/consumer/RoundRobinAssignor.html],
[StickyAssignor|https://kafka.apache.org/27/javadoc/org/apache/kafka/clients/consumer/StickyAssignor.html],
and
[CooperativeStickyAssignor|https://kafka.apache.org/27/javadoc/org/apache/kafka/clients/consumer/CooperativeStickyAssignor.html].
If no partition assignor is configured with a consumer, the {{RangeAssignor}}
is used by default. Although there are some benefits to this assignor including
stability of assignment across generations and simplicity of design, it comes
with a major drawback: the number of active consumers in a group is limited to
the number of partitions in the topic(s) with the most partitions. For an
example of the worst case, in a consumer group where every member is subscribed
to ten topics that each have one partition, only one member of that group will
be assigned any topic partitions.
This can end up producing counterintuitive and even frustrating behavior when a
sink connector is brought up with N tasks to read from some collection of
topics with a total of N topic partitions, but some tasks end up idling and not
processing any data.
h3. Proposed Change
*NOTE: Until/unless*
[KIP-429|https://cwiki.apache.org/confluence/display/KAFKA/KIP-429%3A+Kafka+Consumer+Incremental+Rebalance+Protocol]
introduced the {{CooperativeStickyAssignor}}, which seeks to provide a stable
assignment across generations wherever possible, provide the most even
assignment possible (taking into account possible differences in subscriptions
across consumers in the group), and allow consumers to continue processing data
during rebalance. The documentation for the assignor states that "Users should
prefer this assignor for newer clusters."
We should alter the default consumer configuration for sink tasks to use the
new {{CooperativeStickyAssignor}}. In order to do this in a
backwards-compatible fashion that also enables rolling upgrades, this should be
implemented by changing the {{Worker}} to set the following on the consumer
configuration created for each sink connector task:
{code:java}
partition.assignment.strategy=org.apache.kafka.clients.consumer.CooperativeStickyAssignor,org.apache.kafka.clients.consumer.RangeAssignor
{code}
This way, consumer groups for sink connectors on Connect clusters in the
process of being upgraded will continue to use the {{RangeAssignor}} until all
workers in the cluster have been upgraded, and then will switch over to the new
{{CooperativeStickyAssignor}} automatically. But, this setting will be
overwritten by any user-specified {{consumer.partition.assignment.strategy}}
property in the worker configuration, and by any user-specified
{{consumer.override.partition.assignment.strategy}} property in a sink
connector configuration when per-connector client overrides is enabled in the
worker config with {{connector.client.config.override.policy=ALL}}.
This improvement is viable as far back as -2.3- 2.4, when the
{{CooperativeStickyAssignor}} was introduced, but given that it is not a bug
fix, should only be applied to the Connect framework in an upcoming minor
release.
h3. Manually setting the partition assignment strategy
There is a simple workaround to achieve the same behavior in AK releases 2.4
and later that don't also include this fix: either set the following in the
*worker configuration*:
{code:java}
consumer.partition.assignment.strategy=org.apache.kafka.clients.consumer.CooperativeStickyAssignor,org.apache.kafka.clients.consumer.RangeAssignor
{code}
or set the following in *connector configurations* when per-connector client
overrides is enabled in the worker config with
{{connector.client.config.override.policy=ALL}}:
{code:java}
consumer.override.partition.assignment.strategy=org.apache.kafka.clients.consumer.CooperativeStickyAssignor,org.apache.kafka.clients.consumer.RangeAssignor
{code}
> Update default consumer partition assignor for sink tasks
> ---------------------------------------------------------
>
> Key: KAFKA-12463
> URL: https://issues.apache.org/jira/browse/KAFKA-12463
> Project: Kafka
> Issue Type: Improvement
> Components: KafkaConnect
> Reporter: Chris Egerton
> Assignee: Chris Egerton
> Priority: Major
>
> Kafka consumers have a pluggable [partition assignment
> interface|https://kafka.apache.org/27/javadoc/org/apache/kafka/clients/consumer/ConsumerPartitionAssignor.html]
> that comes with several out-of-the-box implementations including the
> [RangeAssignor|https://kafka.apache.org/27/javadoc/org/apache/kafka/clients/consumer/RangeAssignor.html],
>
> [RoundRobinAssignor|https://kafka.apache.org/27/javadoc/org/apache/kafka/clients/consumer/RoundRobinAssignor.html],
>
> [StickyAssignor|https://kafka.apache.org/27/javadoc/org/apache/kafka/clients/consumer/StickyAssignor.html],
> and
> [CooperativeStickyAssignor|https://kafka.apache.org/27/javadoc/org/apache/kafka/clients/consumer/CooperativeStickyAssignor.html].
> If no partition assignor is configured with a consumer, the {{RangeAssignor}}
> is used by default. Although there are some benefits to this assignor
> including stability of assignment across generations and simplicity of
> design, it comes with a major drawback: the number of active consumers in a
> group is limited to the number of partitions in the topic(s) with the most
> partitions. For an example of the worst case, in a consumer group where every
> member is subscribed to ten topics that each have one partition, only one
> member of that group will be assigned any topic partitions.
> This can end up producing counterintuitive and even frustrating behavior when
> a sink connector is brought up with N tasks to read from some collection of
> topics with a total of N topic partitions, but some tasks end up idling and
> not processing any data.
> h3. Proposed Change
> *NOTE: Until/unless KAFKA-12477 is addressed, the approach outlined below
> will not work as consumers will still perform eager rebalancing as long as at
> least one of the partition assignors they are configured with does not
> support cooperative rebalancing. KAFKA-12487 should also be addressed before
> configuring any Connect worker to use the {{CooperativeStickyAssignor}} for
> any sink connectors.*
> [KIP-429|https://cwiki.apache.org/confluence/display/KAFKA/KIP-429%3A+Kafka+Consumer+Incremental+Rebalance+Protocol]
> introduced the {{CooperativeStickyAssignor}}, which seeks to provide a
> stable assignment across generations wherever possible, provide the most even
> assignment possible (taking into account possible differences in
> subscriptions across consumers in the group), and allow consumers to continue
> processing data during rebalance. The documentation for the assignor states
> that "Users should prefer this assignor for newer clusters."
> We should alter the default consumer configuration for sink tasks to use the
> new {{CooperativeStickyAssignor}}. In order to do this in a
> backwards-compatible fashion that also enables rolling upgrades, this should
> be implemented by changing the {{Worker}} to set the following on the
> consumer configuration created for each sink connector task:
> {code:java}
> partition.assignment.strategy=org.apache.kafka.clients.consumer.CooperativeStickyAssignor,org.apache.kafka.clients.consumer.RangeAssignor
> {code}
> This way, consumer groups for sink connectors on Connect clusters in the
> process of being upgraded will continue to use the {{RangeAssignor}} until
> all workers in the cluster have been upgraded, and then will switch over to
> the new {{CooperativeStickyAssignor}} automatically. But, this setting will
> be overwritten by any user-specified
> {{consumer.partition.assignment.strategy}} property in the worker
> configuration, and by any user-specified
> {{consumer.override.partition.assignment.strategy}} property in a sink
> connector configuration when per-connector client overrides is enabled in the
> worker config with {{connector.client.config.override.policy=ALL}}.
> This improvement is viable as far back as -2.3- 2.4, when the
> {{CooperativeStickyAssignor}} was introduced, but given that it is not a bug
> fix, should only be applied to the Connect framework in an upcoming minor
> release.
> h3. Manually setting the partition assignment strategy
> There is a simple workaround to achieve the same behavior in AK releases 2.4
> and later that don't also include this improvement: either set a value for
> the {{consumer.partition.assignment.strategy}} property in the *worker
> configuration, or* set a value for the
> {{consumer.override.partition.assignment.strategy}} property in one or more
> *connector configurations* when per-connector client overrides is enabled in
> the worker config with {{connector.client.config.override.policy=ALL}}.
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