def get_outcomes_consumer(concurrency=None, **options):
"""
Handles outcome requests coming via a kafka queue from Relay.
"""
return create_batching_kafka_consumer(
topic_name=settings.KAFKA_OUTCOMES,
worker=OutcomesConsumerWorker(concurrency=concurrency),
**options)
def get_profiles_consumer(
topic: str,
**options: Dict[str, str],
) -> BatchingKafkaConsumer:
return create_batching_kafka_consumer(
{topic},
worker=ProfilesConsumer(),
**options,
)
def get_ingest_consumer(consumer_types, once=False, **options):
"""
Handles events coming via a kafka queue.
The events should have already been processed (normalized... ) upstream (by Relay).
"""
topic_names = {ConsumerType.get_topic_name(consumer_type) for consumer_type in consumer_types}
return create_batching_kafka_consumer(
topic_names=topic_names, worker=IngestConsumerWorker(), **options
)
def get_metrics_consumer(topic: Optional[str] = None,
**options: Dict[str, str]) -> BatchingKafkaConsumer:
snuba_metrics = settings.KAFKA_TOPICS[settings.KAFKA_SNUBA_METRICS]
snuba_metrics_producer = Producer(
kafka_config.get_kafka_producer_cluster_options(
snuba_metrics["cluster"]), )
return create_batching_kafka_consumer(
{topic},
worker=MetricsIndexerWorker(producer=snuba_metrics_producer),
**options,
)
