# 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)