blob: 73ff0c21bee6d912a47652e15ffa797c3bbfd47f [file] [log] [blame]
#!/usr/bin/env python
#
# Copyright 2016 Confluent Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
#
# Example high-level Kafka 0.9 balanced Consumer
#
from confluent_kafka import Consumer, KafkaError
import sys
import getopt
import json
import logging
from pprint import pformat
def print_usage_and_exit(program_name):
sys.stderr.write('Usage: %s [options..] <bootstrap-brokers> <group> <topic1> <topic2> ..\n' % program_name)
options = '''
Options:
-T <intvl> Enable client statistics at specified interval (ms)
'''
sys.stderr.write(options)
sys.exit(1)
if __name__ == '__main__':
optlist, argv = getopt.getopt(sys.argv[1:], 'T:')
if len(argv) < 3:
print_usage_and_exit(sys.argv[0])
broker = argv[0]
group = argv[1]
topics = argv[2:]
# Consumer configuration
# See https://github.com/edenhill/librdkafka/blob/master/CONFIGURATION.md
'''
conf = {'bootstrap.servers': broker,'group.id': group, 'session.timeout.ms': 60000,
'auto.offset.reset': 'earliest'}
'''
conf = {'bootstrap.servers': broker,
'group.id': group,
'session.timeout.ms': 60000}
logger = logging.getLogger('openolt-kafka-consumer')
logger.setLevel(logging.DEBUG)
handler = logging.StreamHandler()
handler.setFormatter(logging.Formatter('%(asctime)-15s %(levelname)-8s %(message)s'))
logger.addHandler(handler)
# Create Consumer instance
# Hint: try debug='fetch' to generate some log messages
# c = Consumer(conf, logger=logger, debug='fetch')
c = Consumer(conf, logger=logger)
def print_assignment(consumer, partitions):
print('Assignment:', partitions)
# Subscribe to topics
c.subscribe(topics, on_assign=print_assignment)
# Read messages from Kafka, print to stdout
try:
while True:
msg = c.poll(timeout=1.0)
if msg is None:
continue
elif not msg.error():
print(msg.value())
elif msg.error().code() == KafkaError._PARTITION_EOF:
# print('End of partition reached {0}/{1}'
# .format(msg.topic(), msg.partition()))
pass
else:
print('Error occured: {0}'.format(msg.error().str()))
except KeyboardInterrupt:
pass
finally:
# Close down consumer to commit final offsets.
c.close()