t

fs2.kafka.consumer

KafkaConsumeGrouped

trait KafkaConsumeGrouped[F[_], K, V] extends AnyRef

Source
KafkaConsumeGrouped.scala
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Abstract Value Members

  1. abstract def groupedPartitionsMapStream: Stream[F, Map[Set[TopicPartition], Stream[F, CommittableConsumerRecord[F, K, V]]]]

    Stream where each element contains a Map of the current partition-group assignment.

    Stream where each element contains a Map of the current partition-group assignment. Keys are partition groups (Set[TopicPartition]); values are record streams for that group.

    Assigned partitions are split into up to maxParallelism groups, sized as evenly as possible. The default (Int.MaxValue) gives one stream per partition.

    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 groupedPartitionsMapStream 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 emitted Map reflects the current partition-group layout. Streams for retained groups remain active; only streams for revoked or realigned groups are closed.

    This is the most generic Stream method. If you don't need per-partition streams, consider using partitionedStream or stream instead.

    Note

    you have to first use subscribe or assign to subscribe the consumer before using this Stream. If you forgot to subscribe, there will be a NotSubscribedException raised in the Stream.

    See also

    records

    partitionedRecords

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