Source code for cerebralcortex.core.messaging_manager.kafka_handler

# Copyright (c) 2019, MD2K Center of Excellence
# - Nasir Ali <nasir.ali08@gmail.com>
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import json
from pyspark.streaming.kafka import KafkaUtils, KafkaDStream, TopicAndPartition


[docs]class KafkaHandler():
[docs] def produce_message(self, topic: str, msg: str): """ Publish a message on kafka message queue Args: topic (str): name of the kafka topic msg (dict): message that needs to published on kafka Returns: bool: True if successful. In case of failure, it returns an Exception message. Raises: ValueError: topic and message parameters cannot be empty or None. Exception: Error publishing message. Topic: topic_name - error-message """ if not topic and not msg: raise ValueError("topic and message parameters cannot be empty or None.") try: self.producer.send(topic, msg) self.producer.flush() return True except Exception as e: raise Exception("Error publishing message. Topic: "+str(topic)+" - "+str(e))
[docs] def subscribe_to_topic(self, topic: str)-> dict: """ Subscribe to kafka topic as a consumer Args: topic (str): name of the kafka topic Yields: dict: kafka message Raises: ValueError: Topic parameter is missing. """ if not topic: raise ValueError("Topic parameter is missing.") self.consumer.subscribe(topic) for message in self.consumer: #TODO: this is a test-code. yield json.loads(message.value.decode('utf8'))
[docs] def create_direct_kafka_stream(self, kafka_topic: str, ssc) -> KafkaDStream: """ Create a direct stream to kafka topic. Supports only one topic at a time Args: kafka_topic: kafka topic to create stream against Raises: Exception: if direct stream cannot be created. Todo: Enable logging of errors """ try: offsets = self.CC.get_kafka_offsets(kafka_topic) kafka_topic = [kafka_topic] if bool(offsets): fromOffset = {} for offset in offsets: offset_start = offset["offset_start"] topic_partition = offset["topic_partition"] topic = offset["topic"] topicPartion = TopicAndPartition(topic, int(topic_partition)) fromOffset[topicPartion] = int(offset_start) return KafkaUtils.createDirectStream(ssc, kafka_topic, {"metadata.broker.list": self.broker, "group.id": self.consumer_group_id}, fromOffsets=fromOffset) else: offset_reset = "smallest" # smallest OR largest return KafkaUtils.createDirectStream(ssc, kafka_topic, {"metadata.broker.list": self.broker, "auto.offset.reset": offset_reset, "group.id": self.consumer_group_id}) except Exception as e: print(e)