implicit class VertxKafkaConsumerOps[K, V] extends AnyRef
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- new VertxKafkaConsumerOps(target: KafkaConsumer[K, V])
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- def assignL(topicPartitions: Set[TopicPartition]): Task[Unit]
Manually assign a list of partition to this consumer.
Manually assign a list of partition to this consumer.
Due to internal buffering of messages, when reassigning the old set of partitions may remain in effect (as observed by the #handler(Handler) record handler)} until some time after the given
completionHandler
is called. In contrast, the once the givencompletionHandler
is called the#batchHandler(Handler)
will only see messages consistent with the new set of partitions.- topicPartitions
partitions which want assigned
- returns
current KafkaConsumer instance
- def assignL(topicPartition: TopicPartition): Task[Unit]
Manually assign a partition to this consumer.
Manually assign a partition to this consumer.
Due to internal buffering of messages, when reassigning the old partition may remain in effect (as observed by the #handler(Handler) record handler)} until some time after the given
completionHandler
is called. In contrast, the once the givencompletionHandler
is called the#batchHandler(Handler)
will only see messages consistent with the new partition.- topicPartition
partition which want assigned
- returns
current KafkaConsumer instance
- def assignmentL(): Task[Set[TopicPartition]]
Get the set of partitions currently assigned to this consumer.
Get the set of partitions currently assigned to this consumer.
- returns
current KafkaConsumer instance
- def beginningOffsetsL(topicPartition: TopicPartition): Task[Long]
Get the first offset for the given partitions.
Get the first offset for the given partitions.
- topicPartition
the partition to get the earliest offset.
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- @throws(classOf[java.lang.CloneNotSupportedException]) @native()
- def closeL(): Task[Unit]
Close the consumer
- def commitL(): Task[Unit]
Commit current offsets for all the subscribed list of topics and partition.
- def committedL(topicPartition: TopicPartition): Task[OffsetAndMetadata]
Get the last committed offset for the given partition (whether the commit happened by this process or another).
Get the last committed offset for the given partition (whether the commit happened by this process or another).
- topicPartition
topic partition for getting last committed offset
- def endOffsetsL(topicPartition: TopicPartition): Task[Long]
Get the last offset for the given partition.
Get the last offset for the given partition. The last offset of a partition is the offset of the upcoming message, i.e. the offset of the last available message + 1.
- topicPartition
the partition to get the end offset.
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- def offsetsForTimesL(topicPartition: TopicPartition, timestamp: Long): Task[OffsetAndTimestamp]
Look up the offset for the given partition by timestamp.
Look up the offset for the given partition by timestamp. Note: the result might be null in case for the given timestamp no offset can be found -- e.g., when the timestamp refers to the future
- topicPartition
TopicPartition to query.
- timestamp
Timestamp to be used in the query.
- def partitionsForL(topic: String): Task[List[PartitionInfo]]
Get metadata about the partitions for a given topic.
Get metadata about the partitions for a given topic.
- topic
topic partition for which getting partitions info
- returns
current KafkaConsumer instance
- def pauseL(topicPartitions: Set[TopicPartition]): Task[Unit]
Suspend fetching from the requested partitions.
Suspend fetching from the requested partitions.
Due to internal buffering of messages, the record handler will continue to observe messages from the given
topicPartitions
until some time after the givencompletionHandler
is called. In contrast, the once the givencompletionHandler
is called the#batchHandler(Handler)
will not see messages from the giventopicPartitions
.- topicPartitions
topic partition from which suspend fetching
- returns
current KafkaConsumer instance
- def pauseL(topicPartition: TopicPartition): Task[Unit]
Suspend fetching from the requested partition.
Suspend fetching from the requested partition.
Due to internal buffering of messages, the record handler will continue to observe messages from the given
topicPartition
until some time after the givencompletionHandler
is called. In contrast, the once the givencompletionHandler
is called the#batchHandler(Handler)
will not see messages from the giventopicPartition
.- topicPartition
topic partition from which suspend fetching
- returns
current KafkaConsumer instance
- def pausedL(): Task[Set[TopicPartition]]
Get the set of partitions that were previously paused by a call to pause(Set).
- def pipeToL(dst: WriteStream[KafkaConsumerRecord[K, V]]): Task[Unit]
- def pollL(timeout: Long): Task[KafkaConsumerRecords[K, V]]
Executes a poll for getting messages from Kafka
Executes a poll for getting messages from Kafka
- timeout
The time, in milliseconds, spent waiting in poll if data is not available in the buffer. If 0, returns immediately with any records that are available currently in the native Kafka consumer's buffer, else returns empty. Must not be negative.
- def positionL(partition: TopicPartition): Task[Long]
Get the offset of the next record that will be fetched (if a record with that offset exists).
Get the offset of the next record that will be fetched (if a record with that offset exists).
- partition
The partition to get the position for
- def resumeL(topicPartitions: Set[TopicPartition]): Task[Unit]
Resume specified partitions which have been paused with pause.
Resume specified partitions which have been paused with pause.
- topicPartitions
topic partition from which resume fetching
- returns
current KafkaConsumer instance
- def resumeL(topicPartition: TopicPartition): Task[Unit]
Resume specified partition which have been paused with pause.
Resume specified partition which have been paused with pause.
- topicPartition
topic partition from which resume fetching
- returns
current KafkaConsumer instance
- def seekL(topicPartition: TopicPartition, offset: Long): Task[Unit]
Overrides the fetch offsets that the consumer will use on the next poll.
Overrides the fetch offsets that the consumer will use on the next poll.
Due to internal buffering of messages, the record handler will continue to observe messages fetched with respect to the old offset until some time after the given
completionHandler
is called. In contrast, the once the givencompletionHandler
is called the#batchHandler(Handler)
will only see messages consistent with the new offset.- topicPartition
topic partition for which seek
- offset
offset to seek inside the topic partition
- returns
current KafkaConsumer instance
- def seekToBeginningL(topicPartitions: Set[TopicPartition]): Task[Unit]
Seek to the first offset for each of the given partitions.
Seek to the first offset for each of the given partitions.
Due to internal buffering of messages, the record handler will continue to observe messages fetched with respect to the old offset until some time after the given
completionHandler
is called. In contrast, the once the givencompletionHandler
is called the#batchHandler(Handler)
will only see messages consistent with the new offset.- topicPartitions
topic partition for which seek
- returns
current KafkaConsumer instance
- def seekToBeginningL(topicPartition: TopicPartition): Task[Unit]
Seek to the first offset for each of the given partition.
Seek to the first offset for each of the given partition.
Due to internal buffering of messages, the record handler will continue to observe messages fetched with respect to the old offset until some time after the given
completionHandler
is called. In contrast, the once the givencompletionHandler
is called the#batchHandler(Handler)
will only see messages consistent with the new offset.- topicPartition
topic partition for which seek
- returns
current KafkaConsumer instance
- def seekToEndL(topicPartitions: Set[TopicPartition]): Task[Unit]
Seek to the last offset for each of the given partitions.
Seek to the last offset for each of the given partitions.
Due to internal buffering of messages, the record handler will continue to observe messages fetched with respect to the old offset until some time after the given
completionHandler
is called. In contrast, the once the givencompletionHandler
is called the#batchHandler(Handler)
will only see messages consistent with the new offset.- topicPartitions
topic partition for which seek
- returns
current KafkaConsumer instance
- def seekToEndL(topicPartition: TopicPartition): Task[Unit]
Seek to the last offset for each of the given partition.
Seek to the last offset for each of the given partition.
Due to internal buffering of messages, the record handler will continue to observe messages fetched with respect to the old offset until some time after the given
completionHandler
is called. In contrast, the once the givencompletionHandler
is called the#batchHandler(Handler)
will only see messages consistent with the new offset.- topicPartition
topic partition for which seek
- returns
current KafkaConsumer instance
- def subscribeL(topics: Set[String]): Task[Unit]
Subscribe to the given list of topics to get dynamically assigned partitions.
Subscribe to the given list of topics to get dynamically assigned partitions.
Due to internal buffering of messages, when changing the subscribed topics the old set of topics may remain in effect (as observed by the #handler(Handler) record handler}) until some time after the given
completionHandler
is called. In contrast, the once the givencompletionHandler
is called the#batchHandler(Handler)
will only see messages consistent with the new set of topics.- topics
topics to subscribe to
- returns
current KafkaConsumer instance
- def subscribeL(topic: String): Task[Unit]
Subscribe to the given topic to get dynamically assigned partitions.
Subscribe to the given topic to get dynamically assigned partitions.
Due to internal buffering of messages, when changing the subscribed topic the old topic may remain in effect (as observed by the #handler(Handler) record handler}) until some time after the given
completionHandler
is called. In contrast, the once the givencompletionHandler
is called the#batchHandler(Handler)
will only see messages consistent with the new topic.- topic
topic to subscribe to
- returns
current KafkaConsumer instance
- def subscriptionL(): Task[Set[String]]
Get the current subscription.
Get the current subscription.
- returns
current KafkaConsumer instance
- final def synchronized[T0](arg0: => T0): T0
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- val target: KafkaConsumer[K, V]
- def toString(): String
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- def unsubscribeL(): Task[Unit]
Unsubscribe from topics currently subscribed with subscribe.
Unsubscribe from topics currently subscribed with subscribe.
- returns
current KafkaConsumer instance
- final def wait(): Unit
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- @throws(classOf[java.lang.InterruptedException])
- final def wait(arg0: Long, arg1: Int): Unit
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- final def wait(arg0: Long): Unit
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