public interface ConsumerRebalanceListener
This is applicable when the consumer is having Kafka auto-manage group membership. If the consumer directly assigns partitions, those partitions will never be reassigned and this callback is not applicable.
When Kafka is managing the group membership, a partition re-assignment will be triggered any time the members of the group change or the subscription of the members changes. This can occur when processes die, new process instances are added or old instances come back to life after failure. Partition re-assignments can also be triggered by changes affecting the subscribed topics (e.g. when the number of partitions is administratively adjusted).
There are many uses for this functionality. One common use is saving offsets in a custom store. By saving offsets in
the onPartitionsRevoked(Collection)
call we can ensure that any time partition assignment changes
the offset gets saved.
Another use is flushing out any kind of cache of intermediate results the consumer may be keeping. For example, consider a case where the consumer is subscribed to a topic containing user page views, and the goal is to count the number of page views per user for each five minute window. Let's say the topic is partitioned by the user id so that all events for a particular user go to a single consumer instance. The consumer can keep in memory a running tally of actions per user and only flush these out to a remote data store when its cache gets too big. However if a partition is reassigned it may want to automatically trigger a flush of this cache, before the new owner takes over consumption.
This callback will only execute in the user thread as part of the poll(long)
call
whenever partition assignment changes.
Under normal conditions, if a partition is reassigned from one consumer to another, then the old consumer will
always invoke onPartitionsRevoked
for that partition prior to the new consumer
invoking onPartitionsAssigned
for the same partition. So if offsets or other state is saved in the
onPartitionsRevoked
call by one consumer member, it will be always accessible by the time the
other consumer member taking over that partition and triggering its onPartitionsAssigned
callback to load the state.
You can think of revocation as a graceful way to give up ownership of a partition. In some cases, the consumer may not have an opportunity to do so.
For example, if the session times out, then the partitions may be reassigned before we have a chance to revoke them gracefully.
For this case, we have a third callback onPartitionsLost(Collection)
. The difference between this function and
onPartitionsRevoked(Collection)
is that upon invocation of onPartitionsLost(Collection)
, the partitions
may already be owned by some other members in the group and therefore users would not be able to commit its consumed offsets for example.
Users could implement these two functions differently (by default,
onPartitionsLost(Collection)
will be calling onPartitionsRevoked(Collection)
directly); for example, in the
onPartitionsLost(Collection)
we should not need to store the offsets since we know these partitions are no longer owned by the consumer
at that time.
During a rebalance event, the onPartitionsAssigned
function will always be triggered exactly once when
the rebalance completes. That is, even if there is no newly assigned partitions for a consumer member, its onPartitionsAssigned
will still be triggered with an empty collection of partitions. As a result this function can be used also to notify when a rebalance event has happened.
With eager rebalancing, onPartitionsRevoked(Collection)
will always be called at the start of a rebalance. On the other hand, onPartitionsLost(Collection)
will only be called when there were non-empty partitions that were lost.
With cooperative rebalancing, onPartitionsRevoked(Collection)
and onPartitionsLost(Collection)
will only be triggered when there are non-empty partitions revoked or lost from this consumer member during a rebalance event.
It is possible
for a WakeupException
or InterruptException
to be raised from one of these nested invocations. In this case, the exception will be propagated to the current
invocation of KafkaConsumer.poll(java.time.Duration)
in which this callback is being executed. This means it is not
necessary to catch these exceptions and re-attempt to wakeup or interrupt the consumer thread.
Also if the callback function implementation itself throws an exception, this exception will be propagated to the current
invocation of KafkaConsumer.poll(java.time.Duration)
as well.
Note that callbacks only serve as notification of an assignment change.
They cannot be used to express acceptance of the change.
Hence throwing an exception from a callback does not affect the assignment in any way,
as it will be propagated all the way up to the KafkaConsumer.poll(java.time.Duration)
call.
If user captures the exception in the caller, the callback is still assumed successful and no further retries will be attempted.
Here is pseudo-code for a callback implementation for saving offsets:
public class SaveOffsetsOnRebalance implements ConsumerRebalanceListener {
private Consumer<?,?> consumer;
public SaveOffsetsOnRebalance(Consumer<?,?> consumer) {
this.consumer = consumer;
}
public void onPartitionsRevoked(Collection<TopicPartition> partitions) {
// save the offsets in an external store using some custom code not described here
for(TopicPartition partition: partitions)
saveOffsetInExternalStore(consumer.position(partition));
}
public void onPartitionsLost(Collection<TopicPartition> partitions) {
// do not need to save the offsets since these partitions are probably owned by other consumers already
}
public void onPartitionsAssigned(Collection<TopicPartition> partitions) {
// read the offsets from an external store using some custom code not described here
for(TopicPartition partition: partitions)
consumer.seek(partition, readOffsetFromExternalStore(partition));
}
}
Modifier and Type | Method and Description |
---|---|
void |
onPartitionsAssigned(java.util.Collection<TopicPartition> partitions)
A callback method the user can implement to provide handling of customized offsets on completion of a successful
partition re-assignment.
|
default void |
onPartitionsLost(java.util.Collection<TopicPartition> partitions)
A callback method you can implement to provide handling of cleaning up resources for partitions that have already
been reassigned to other consumers.
|
void |
onPartitionsRevoked(java.util.Collection<TopicPartition> partitions)
A callback method the user can implement to provide handling of offset commits to a customized store.
|
void onPartitionsRevoked(java.util.Collection<TopicPartition> partitions)
KafkaConsumer.close(Duration)
)
or is unsubscribing (KafkaConsumer.unsubscribe()
).
It is recommended that offsets should be committed in this callback to either Kafka or a
custom offset store to prevent duplicate data.
In eager rebalancing, it will always be called at the start of a rebalance and after the consumer stops fetching data.
In cooperative rebalancing, it will be called at the end of a rebalance on the set of partitions being revoked iff the set is non-empty.
For examples on usage of this API, see Usage Examples section of KafkaConsumer
.
It is common for the revocation callback to use the consumer instance in order to commit offsets. It is possible
for a WakeupException
or InterruptException
to be raised from one of these nested invocations. In this case, the exception will be propagated to the current
invocation of KafkaConsumer.poll(java.time.Duration)
in which this callback is being executed. This means it is not
necessary to catch these exceptions and re-attempt to wakeup or interrupt the consumer thread.
partitions
- The list of partitions that were assigned to the consumer and now need to be revoked (may not
include all currently assigned partitions, i.e. there may still be some partitions left)WakeupException
- If raised from a nested call to KafkaConsumer
InterruptException
- If raised from a nested call to KafkaConsumer
void onPartitionsAssigned(java.util.Collection<TopicPartition> partitions)
poll(long)
call.
It is guaranteed that under normal conditions all the processes in a consumer group will execute their
onPartitionsRevoked(Collection)
callback before any instance executes its
onPartitionsAssigned(Collection)
callback. During exceptional scenarios, partitions may be migrated
without the old owner being notified (i.e. their onPartitionsRevoked(Collection)
callback not triggered),
and later when the old owner consumer realized this event, the onPartitionsLost(Collection)
(Collection)} callback
will be triggered by the consumer then.
It is common for the assignment callback to use the consumer instance in order to query offsets. It is possible
for a WakeupException
or InterruptException
to be raised from one of these nested invocations. In this case, the exception will be propagated to the current
invocation of KafkaConsumer.poll(java.time.Duration)
in which this callback is being executed. This means it is not
necessary to catch these exceptions and re-attempt to wakeup or interrupt the consumer thread.
partitions
- The list of partitions that are now assigned to the consumer (previously owned partitions will
NOT be included, i.e. this list will only include newly added partitions)WakeupException
- If raised from a nested call to KafkaConsumer
InterruptException
- If raised from a nested call to KafkaConsumer
default void onPartitionsLost(java.util.Collection<TopicPartition> partitions)
onPartitionsRevoked(java.util.Collection<org.apache.kafka.common.TopicPartition>)
, before being reassigned
to other consumers during a rebalance event. However, during exceptional scenarios when the consumer realized that it
does not own this partition any longer, i.e. not revoked via a normal rebalance event, then this method would be invoked.
For example, this function is called if a consumer's session timeout has expired, or if a fatal error has been received indicating the consumer is no longer part of the group.
By default it will just trigger onPartitionsRevoked(java.util.Collection<org.apache.kafka.common.TopicPartition>)
; for users who want to distinguish
the handling logic of revoked partitions v.s. lost partitions, they can override the default implementation.
It is possible
for a WakeupException
or InterruptException
to be raised from one of these nested invocations. In this case, the exception will be propagated to the current
invocation of KafkaConsumer.poll(java.time.Duration)
in which this callback is being executed. This means it is not
necessary to catch these exceptions and re-attempt to wakeup or interrupt the consumer thread.
partitions
- The list of partitions that were assigned to the consumer and now have been reassigned
to other consumers. With the current protocol this will always include all of the consumer's
previously assigned partitions, but this may change in future protocols (ie there would still
be some partitions left)WakeupException
- If raised from a nested call to KafkaConsumer
InterruptException
- If raised from a nested call to KafkaConsumer