KafkaConsumer represents a consumer of Kafka records, with the
ability to subscribe
to topics, start a single top-level stream,
and optionally control it via the provided fiber instance.
The following top-level streams are provided.
- stream provides a single stream of records, where the order
of records is guaranteed per topic-partition.
- partitionedStream provides a stream with elements as streams
that continually request records for a single partition. Order
is guaranteed per topic-partition, but all assigned partitions
will have to be processed in parallel.
- partitionsMapStream provides a stream where each element contains
a current assignment. The current assignment is the
Map
, where keys is aTopicPartition
, and values are streams with records for a particularTopicPartition
.
For the streams, records are wrapped in [[CommittableConsumerRecord]]s which provide [[CommittableOffset]]s with the ability to commit record offsets to Kafka. For performance reasons, offsets are usually committed in batches using [[CommittableOffsetBatch]]. Provided `Pipe`s, like [[commitBatchWithin]] are available for batch committing offsets. If you are not committing offsets to Kafka, you can simply discard the [[CommittableOffset]], and only make use of the record.
While it's technically possible to start more than one stream from a single [[KafkaConsumer]], it is generally not recommended as there is no guarantee which stream will receive which records, and there might be an overlap, in terms of duplicate records, between the two streams. If a first stream completes, possibly with error, there's no guarantee the stream has processed all of the records it received, and a second stream from the same [[KafkaConsumer]] might not be able to pick up where the first one left off. Therefore, only create a single top-level stream per [[KafkaConsumer]], and if you want to start a new stream if the first one finishes, let the [[KafkaConsumer]] shutdown and create a new one.
- Companion:
- object
Value members
Inherited methods
Manually assigns all partitions for the specified topic to the consumer.
Manually assigns all partitions for the specified topic to the consumer.
- Inherited from:
- KafkaAssignment
Manually assigns the specified list of partitions for the specified topic to the consumer. This function does not allow for incremental assignment and will replace the previous assignment (if there is one).
Manually assigns the specified list of partitions for the specified topic to the consumer. This function does not allow for incremental assignment and will replace the previous assignment (if there is one).
Manual topic assignment through this method does not use the consumer's
group management functionality. As such, there will be no rebalance
operation triggered when group membership or cluster and topic metadata
change. Note that it is not possible to use both manual partition
assignment with assign
and group assignment with subscribe
.
If auto-commit is enabled, an async commit (based on the old assignment) will be triggered before the new assignment replaces the old one.
To unassign all partitions, use KafkaConsumer#unsubscribe.
- See also:
org.apache.kafka.clients.consumer.KafkaConsumer#assign
- Inherited from:
- KafkaAssignment
Manually assigns the specified list of topic partitions to the consumer. This function does not allow for incremental assignment and will replace the previous assignment (if there is one).
Manually assigns the specified list of topic partitions to the consumer. This function does not allow for incremental assignment and will replace the previous assignment (if there is one).
Manual topic assignment through this method does not use the consumer's
group management functionality. As such, there will be no rebalance
operation triggered when group membership or cluster and topic metadata
change. Note that it is not possible to use both manual partition
assignment with assign
and group assigment with subscribe
.
If auto-commit is enabled, an async commit (based on the old assignment) will be triggered before the new assignment replaces the old one.
To unassign all partitions, use KafkaConsumer#unsubscribe.
- See also:
org.apache.kafka.clients.consumer.KafkaConsumer#assign
- Inherited from:
- KafkaAssignment
Returns the set of partitions currently assigned to this consumer.
Returns the set of partitions currently assigned to this consumer.
- Inherited from:
- KafkaAssignment
Stream
where the elements are the set of TopicPartition
s currently
assigned to this consumer. The stream emits whenever a rebalance changes
partition assignments.
Stream
where the elements are the set of TopicPartition
s currently
assigned to this consumer. The stream emits whenever a rebalance changes
partition assignments.
- Inherited from:
- KafkaAssignment
Wait for consumer to shut down. Note that awaitTermination
is guaranteed
to complete after consumer shutdown, even when the consumer is
cancelled with terminate
.
Wait for consumer to shut down. Note that awaitTermination
is guaranteed
to complete after consumer shutdown, even when the consumer is
cancelled with terminate
.
This method will not initiate shutdown. To initiate shutdown and wait for
it to complete, you can use terminate >> awaitTermination
.
- Inherited from:
- KafkaConsumerLifecycle
Returns the first offset for the specified partitions.
Returns the first offset for the specified partitions.
- Inherited from:
- KafkaTopics
Returns the first offset for the specified partitions.
Timeout is determined by default.api.timeout.ms
, which
is set using ConsumerSettings#withDefaultApiTimeout.
Returns the first offset for the specified partitions.
Timeout is determined by default.api.timeout.ms
, which
is set using ConsumerSettings#withDefaultApiTimeout.
- Inherited from:
- KafkaTopics
Commit the specified offsets for the specified list of topics and partitions to Kafka.
This commits offsets to Kafka. The offsets committed using this API will be used on the first fetch after every
rebalance and also on startup. As such, if you need to store offsets in anything other than Kafka, this API
should not be used. The committed offset should be the next message your application will consume,
i.e. lastProcessedMessageOffset + 1. If automatic group management with subscribe is used,
then the committed offsets must belong to the currently auto-assigned partitions.
Offsets committed through multiple calls to this API are guaranteed to be sent in the same order as
the invocations. Additionally note that
offsets committed through this API are guaranteed to complete before a subsequent call to commitSync
(and variants) returns.
Note, that the recommended way for committing offsets in fs2-kafka is to use commit
on
CommittableConsumerRecord, CommittableOffset or CommittableOffsetBatch.
commitAsync and commitSync usually needs only for some custom scenarios.
Commit the specified offsets for the specified list of topics and partitions to Kafka.
This commits offsets to Kafka. The offsets committed using this API will be used on the first fetch after every
rebalance and also on startup. As such, if you need to store offsets in anything other than Kafka, this API
should not be used. The committed offset should be the next message your application will consume,
i.e. lastProcessedMessageOffset + 1. If automatic group management with subscribe is used,
then the committed offsets must belong to the currently auto-assigned partitions.
Offsets committed through multiple calls to this API are guaranteed to be sent in the same order as
the invocations. Additionally note that
offsets committed through this API are guaranteed to complete before a subsequent call to commitSync
(and variants) returns.
Note, that the recommended way for committing offsets in fs2-kafka is to use commit
on
CommittableConsumerRecord, CommittableOffset or CommittableOffsetBatch.
commitAsync and commitSync usually needs only for some custom scenarios.
- Value parameters:
- offsets
A map of offsets by partition with associate metadata.
- See also:
org.apache.kafka.clients.consumer.KafkaConsumer#commitAsync
- Inherited from:
- KafkaCommit
Commit the specified offsets for the specified list of topics and partitions.
This commits offsets to Kafka. The offsets committed using this API will be used on the first fetch after every
rebalance and also on startup. As such, if you need to store offsets in anything other than Kafka, this API
should not be used. The committed offset should be the next message your application will consume,
i.e. lastProcessedMessageOffset + 1. If automatic group management with subscribe is used,
then the committed offsets must belong to the currently auto-assigned partitions.
Despite of it's name, this method is not blocking. But it's based on a blocking
org.apache.kafka.clients.consumer.KafkaConsumer#commitSync method.
Note, that the recommended way for committing offsets in fs2-kafka is to use commit
on
CommittableConsumerRecord, CommittableOffset or CommittableOffsetBatch.
commitAsync and commitSync usually needs only for some custom scenarios.
Commit the specified offsets for the specified list of topics and partitions.
This commits offsets to Kafka. The offsets committed using this API will be used on the first fetch after every
rebalance and also on startup. As such, if you need to store offsets in anything other than Kafka, this API
should not be used. The committed offset should be the next message your application will consume,
i.e. lastProcessedMessageOffset + 1. If automatic group management with subscribe is used,
then the committed offsets must belong to the currently auto-assigned partitions.
Despite of it's name, this method is not blocking. But it's based on a blocking
org.apache.kafka.clients.consumer.KafkaConsumer#commitSync method.
Note, that the recommended way for committing offsets in fs2-kafka is to use commit
on
CommittableConsumerRecord, CommittableOffset or CommittableOffsetBatch.
commitAsync and commitSync usually needs only for some custom scenarios.
- Value parameters:
- offsets
A map of offsets by partition with associated metadata
- See also:
org.apache.kafka.clients.consumer.KafkaConsumer#commitSync
- Inherited from:
- KafkaCommit
Returns the last committed offsets for the given partitions.
Timeout is determined by default.api.timeout.ms
, which
is set using ConsumerSettings#withDefaultApiTimeout.
Returns the last committed offsets for the given partitions.
Timeout is determined by default.api.timeout.ms
, which
is set using ConsumerSettings#withDefaultApiTimeout.
- Inherited from:
- KafkaOffsetsV2
Returns the last committed offsets for the given partitions.
Returns the last committed offsets for the given partitions.
- Inherited from:
- KafkaOffsetsV2
Returns the last offset for the specified partitions.
Returns the last offset for the specified partitions.
- Inherited from:
- KafkaTopics
Returns the last offset for the specified partitions.
Timeout is determined by request.timeout.ms
, which
is set using ConsumerSettings#withRequestTimeout.
Returns the last offset for the specified partitions.
Timeout is determined by request.timeout.ms
, which
is set using ConsumerSettings#withRequestTimeout.
- Inherited from:
- KafkaTopics
Returns consumer metrics.
Returns consumer metrics.
- See also:
org.apache.kafka.clients.consumer.KafkaConsumer#metrics
- Inherited from:
- KafkaMetrics
Stream
where the elements themselves are Stream
s which continually
request records for a single partition. These Stream
s will have to be
processed in parallel, using parJoin
or parJoinUnbounded
. Note that
when using parJoin(n)
and n
is smaller than the number of currently
assigned partitions, then there will be assigned partitions which won't
be processed. For that reason, prefer parJoinUnbounded
and the actual
limit will be the number of assigned partitions.
If you do not want to process all partitions in parallel, then you
can use records instead, where records for all partitions are in
a single Stream
.
Stream
where the elements themselves are Stream
s which continually
request records for a single partition. These Stream
s will have to be
processed in parallel, using parJoin
or parJoinUnbounded
. Note that
when using parJoin(n)
and n
is smaller than the number of currently
assigned partitions, then there will be assigned partitions which won't
be processed. For that reason, prefer parJoinUnbounded
and the actual
limit will be the number of assigned partitions.
If you do not want to process all partitions in parallel, then you
can use records instead, where records for all partitions are in
a single Stream
.
- Note:
you have to first use
subscribe
orassign
the consumer before using thisStream
. If you forgot to subscribe, there will be a NotSubscribedException raised in theStream
.- Inherited from:
- KafkaConsume
Returns the partitions for the specified topic.
Returns the partitions for the specified topic.
- Inherited from:
- KafkaTopics
Returns the partitions for the specified topic.
Returns the partitions for the specified topic.
Timeout is determined by default.api.timeout.ms
, which
is set using ConsumerSettings#withDefaultApiTimeout.
- Inherited from:
- KafkaTopics
Stream
where each element contains a Map
with all newly assigned partitions.
Keys of this Map
are TopicPartition
s, and values are record streams for
the particular TopicPartition
. These streams will be closed only when
a partition is revoked.
With the default assignor, all previous partitions are revoked at
once, and a new set of partitions is assigned to a consumer on each
rebalance. In this case, each returned Map
contains the full partition
assignment for the consumer. And all streams from the previous assignment are closed.
It means, that partitionsMapStream
reflects
the default assignment process in a streaming manner.
This may not be the case when a custom assignor is configured in the
consumer. When using the CooperativeStickyAssignor
, for instance,
partitions may be revoked individually. In this case, each
element in the stream (eachMap
) will contain only streams for newly assigned
partitions. Previously returned streams for partitions that are retained
will remain active. Only streams for revoked partitions will be closed.
This is the most generic Stream
method. If you don't need such control,
consider using partitionedStream
or stream
methods. They are both
based on a partitionsMapStream
.
Stream
where each element contains a Map
with all newly assigned partitions.
Keys of this Map
are TopicPartition
s, and values are record streams for
the particular TopicPartition
. These streams will be closed only when
a partition is revoked.
With the default assignor, all previous partitions are revoked at
once, and a new set of partitions is assigned to a consumer on each
rebalance. In this case, each returned Map
contains the full partition
assignment for the consumer. And all streams from the previous assignment are closed.
It means, that partitionsMapStream
reflects
the default assignment process in a streaming manner.
This may not be the case when a custom assignor is configured in the
consumer. When using the CooperativeStickyAssignor
, for instance,
partitions may be revoked individually. In this case, each
element in the stream (eachMap
) will contain only streams for newly assigned
partitions. Previously returned streams for partitions that are retained
will remain active. Only streams for revoked partitions will be closed.
This is the most generic Stream
method. If you don't need such control,
consider using partitionedStream
or stream
methods. They are both
based on a partitionsMapStream
.
- See also:
- Note:
you have to first use
subscribe
orassign
to subscribe the consumer before using thisStream
. If you forgot to subscribe, there will be a NotSubscribedException raised in theStream
.- Inherited from:
- KafkaConsume
Returns the offset of the next record that will be fetched.
Returns the offset of the next record that will be fetched.
- Inherited from:
- KafkaOffsets
Returns the offset of the next record that will be fetched.
Timeout is determined by default.api.timeout.ms
, which
is set using ConsumerSettings#withDefaultApiTimeout.
Returns the offset of the next record that will be fetched.
Timeout is determined by default.api.timeout.ms
, which
is set using ConsumerSettings#withDefaultApiTimeout.
- Inherited from:
- KafkaOffsets
Consume from all assigned partitions, producing a stream of CommittableConsumerRecords. Alias for stream.
Consume from all assigned partitions, producing a stream of CommittableConsumerRecords. Alias for stream.
- Inherited from:
- KafkaConsume
Overrides the fetch offsets that the consumer will use when reading the next record. If this API is invoked for the same partition more than once, the latest offset will be used. Note that you may lose data if this API is arbitrarily used in the middle of consumption to reset the fetch offsets.
Overrides the fetch offsets that the consumer will use when reading the next record. If this API is invoked for the same partition more than once, the latest offset will be used. Note that you may lose data if this API is arbitrarily used in the middle of consumption to reset the fetch offsets.
- Inherited from:
- KafkaOffsets
Seeks to the first offset for each of the specified partitions.
If no partitions are provided, seeks to the first offset for
all currently assigned partitions.
Note that this seek evaluates lazily, and only on the next call
to poll
or position
.
Seeks to the first offset for each of the specified partitions.
If no partitions are provided, seeks to the first offset for
all currently assigned partitions.
Note that this seek evaluates lazily, and only on the next call
to poll
or position
.
- Inherited from:
- KafkaOffsets
Seeks to the first offset for each currently assigned partition.
This is equivalent to using seekToBeginning
with an empty set
of partitions.
Note that this seek evaluates lazily, and only on the next call
to poll
or position
.
Seeks to the first offset for each currently assigned partition.
This is equivalent to using seekToBeginning
with an empty set
of partitions.
Note that this seek evaluates lazily, and only on the next call
to poll
or position
.
- Inherited from:
- KafkaOffsets
Seeks to the last offset for each of the specified partitions.
If no partitions are provided, seeks to the last offset for
all currently assigned partitions.
Note that this seek evaluates lazily, and only on the next call
to poll
or position
.
Seeks to the last offset for each of the specified partitions.
If no partitions are provided, seeks to the last offset for
all currently assigned partitions.
Note that this seek evaluates lazily, and only on the next call
to poll
or position
.
- Inherited from:
- KafkaOffsets
Seeks to the last offset for each currently assigned partition.
This is equivalent to using seekToEnd
with an empty set of
partitions.
Note that this seek evaluates lazily, and only on the next call
to poll
or position
.
Seeks to the last offset for each currently assigned partition.
This is equivalent to using seekToEnd
with an empty set of
partitions.
Note that this seek evaluates lazily, and only on the next call
to poll
or position
.
- Inherited from:
- KafkaOffsets
Stops consuming new messages from Kafka.
This method could be used to implement a graceful shutdown.
This method has a few effects:
Stops consuming new messages from Kafka.
This method could be used to implement a graceful shutdown.
This method has a few effects:
- After this call no more data will be fetched from Kafka through the
poll
method. - All currently running streams will continue to run until all in-flight messages will be processed.
It means that streams will be completed when all fetched messages will be processed.
If some of the [[records]] methods will be called after [[stopConsuming]] call, these methods will return empty streams.
More than one call of [[stopConsuming]] will have no effect.
- Inherited from:
- KafkaConsume
Alias for partitionedStream.parJoinUnbounded
.
See partitionedRecords for more information.
Alias for partitionedStream.parJoinUnbounded
.
See partitionedRecords for more information.
- Note:
you have to first use
subscribe
orassign
the consumer before using thisStream
. If you forgot to subscribe, there will be a NotSubscribedException raised in theStream
.- Inherited from:
- KafkaConsume
Subscribes the consumer to the topics matching the specified Regex
.
Note that you have to use one of the subscribe
functions before you
can use any of the provided Stream
s, or a NotSubscribedException
will be raised in the Stream
s.
Subscribes the consumer to the topics matching the specified Regex
.
Note that you have to use one of the subscribe
functions before you
can use any of the provided Stream
s, or a NotSubscribedException
will be raised in the Stream
s.
- Value parameters:
- regex
the regex to which matching topics should be subscribed
- Inherited from:
- KafkaSubscription
Subscribes the consumer to the specified topics. Note that you have to
use one of the subscribe
functions to subscribe to one or more topics
before using any of the provided Stream
s, or a NotSubscribedException
will be raised in the Stream
s.
Subscribes the consumer to the specified topics. Note that you have to
use one of the subscribe
functions to subscribe to one or more topics
before using any of the provided Stream
s, or a NotSubscribedException
will be raised in the Stream
s.
- Value parameters:
- topics
the topics to which the consumer should subscribe
- Inherited from:
- KafkaSubscription
Subscribes the consumer to the specified topics. Note that you have to
use one of the subscribe
functions to subscribe to one or more topics
before using any of the provided Stream
s, or a NotSubscribedException
will be raised in the Stream
s.
Subscribes the consumer to the specified topics. Note that you have to
use one of the subscribe
functions to subscribe to one or more topics
before using any of the provided Stream
s, or a NotSubscribedException
will be raised in the Stream
s.
- Inherited from:
- KafkaSubscription
Whenever terminate
is invoked, an attempt will be made to stop the
underlying consumer. The terminate
operation will not wait for the
consumer to shutdown. If you also want to wait for the shutdown
to complete, you can use terminate >> awaitTermination
.
Whenever terminate
is invoked, an attempt will be made to stop the
underlying consumer. The terminate
operation will not wait for the
consumer to shutdown. If you also want to wait for the shutdown
to complete, you can use terminate >> awaitTermination
.
- Inherited from:
- KafkaConsumerLifecycle
Unsubscribes the consumer from all topics and partitions assigned
by subscribe
or assign
.
Unsubscribes the consumer from all topics and partitions assigned
by subscribe
or assign
.
- Inherited from:
- KafkaSubscription