class KafkaGroupReader:
def __init__(self, kafka_config):
self.log = logging.getLogger(__name__)
self.kafka_config = kafka_config
self._kafka_groups = defaultdict(lambda: defaultdict(dict))
self.active_partitions = {}
self._finished = False
def read_group(self, group_id):
partition_count = get_offset_topic_partition_count(self.kafka_config)
partition = get_group_partition(group_id, partition_count)
return self.read_groups(partition)[group_id]
def read_groups(self, partition=None):
self.consumer = KafkaConsumer(
group_id='offset_monitoring_consumer',
bootstrap_servers=self.kafka_config.broker_list,
auto_offset_reset='earliest',
enable_auto_commit=False,
consumer_timeout_ms=30000,
fetch_max_wait_ms=2000,
max_partition_fetch_bytes=10 * 1024 * 1024, # 10MB
)
# Fetch metadata as partitions_for_topic only returns locally cached metadata
# See https://github.com/dpkp/kafka-python/issues/1742
self.consumer.topics()
if partition is not None:
self.active_partitions = {
partition: TopicPartition(CONSUMER_OFFSET_TOPIC, partition),
}
else:
self.active_partitions = {
p: TopicPartition(CONSUMER_OFFSET_TOPIC, p)
for p in self.consumer.partitions_for_topic(
CONSUMER_OFFSET_TOPIC)
}
self.watermarks = self.get_current_watermarks(
list(self.active_partitions.values()))
# Active partitions are not empty. Remove the empty ones.
self.active_partitions = {
p: tp
for p, tp in self.active_partitions.items()
if tp.partition in self.watermarks
and self.watermarks[tp.partition].highmark > 0 and self.watermarks[
tp.partition].highmark > self.watermarks[tp.partition].lowmark
}
# Cannot consume if there are no active partitions
if not self.active_partitions:
return {}
self.consumer.assign(list(self.active_partitions.values()))
self.log.info("Consuming from %s", self.active_partitions)
message_iterator = iter(self.consumer)
while not self.finished():
try:
message = next(message_iterator)
except StopIteration:
continue
# Stop when reaching the last message written to the
# __consumer_offsets topic when KafkaGroupReader first started
if message.offset >= self.watermarks[
message.partition].highmark - 1:
self.remove_partition_from_consumer(message.partition)
self.process_consumer_offset_message(message)
self._remove_unsubscribed_topics()
return {
group: topics.keys()
for group, topics in six.iteritems(self._kafka_groups) if topics
}
def _remove_unsubscribed_topics(self):
for group, topics in list(six.iteritems(self._kafka_groups)):
for topic, partitions in list(six.iteritems(topics)):
# If offsets for all partitions are 0, consider the topic as unsubscribed
if not any(partitions.values()):
del self._kafka_groups[group][topic]
self.log.info(
"Removed group {group} topic {topic} from list of groups"
.format(group=group, topic=topic))
def remove_partition_from_consumer(self, partition):
deleted = self.active_partitions.pop(partition)
# Terminate if there are no more partitions to consume
if not self.active_partitions:
self.log.info("Completed reading from all partitions")
self._finished = True
return
# Reassign the remaining partitions to the consumer while saving the
# position
positions = [(p, self.consumer.position(p))
for p in self.active_partitions.values()]
self.consumer.assign(list(self.active_partitions.values()))
for topic_partition, position in positions:
self.consumer.seek(topic_partition, position)
self.log.info(
"Completed reading from %s. Remaining partitions: %s",
deleted,
self.active_partitions,
)
def parse_consumer_offset_message(self, message):
key = message.key
((key_schema, ), cur) = relative_unpack(b'>h', key, 0)
if key_schema not in [0, 1]:
raise InvalidMessageException(
) # This is not an offset commit message
(group, cur) = read_short_string(key, cur)
(topic, cur) = read_short_string(key, cur)
((partition, ), cur) = relative_unpack(b'>l', key, cur)
if message.value:
value = message.value
((value_schema, ), cur) = relative_unpack(b'>h', value, 0)
if value_schema not in [0, 1]:
raise InvalidMessageException() # Unrecognized message value
((offset, ), cur) = relative_unpack(b'>q', value, cur)
else:
offset = None # Offset was deleted
return group.decode(), topic.decode(), partition, offset
def process_consumer_offset_message(self, message):
try:
group, topic, partition, offset = self.parse_consumer_offset_message(
message)
except InvalidMessageException:
return
if offset is not None:
self._kafka_groups[group][topic][partition] = offset
self.log.info(
"Updated group {group} topic {topic} and updated offset in list of groups"
.format(
group=group,
topic=topic,
), )
# TODO: check if we can ever find an offset commit message with message.value is None
elif offset is None and group in self._kafka_groups and \
topic in self._kafka_groups[group]: # No offset means topic deletion
del self._kafka_groups[group][topic]
self.log.info(
"Removed group {group} topic {topic} from list of groups".
format(group=group, topic=topic))
def get_current_watermarks(self, partitions=None):
client = KafkaToolClient(self.kafka_config.broker_list)
client.load_metadata_for_topics(CONSUMER_OFFSET_TOPIC)
offsets = get_topics_watermarks(
client,
[CONSUMER_OFFSET_TOPIC],
)
partitions_set = set(tp.partition
for tp in partitions) if partitions else None
return {
part: offset
for part, offset in six.iteritems(offsets[CONSUMER_OFFSET_TOPIC])
if offset.highmark > offset.lowmark and (
partitions is None or part in partitions_set)
}
def finished(self):
return self._finished
_GROUP_ID = 'my_group'
consumer = KafkaConsumer(
group_id='ddd',
auto_offset_reset='smallest', #largest
enable_auto_commit=
False, ## true时，Consumer会在消费消息后将offset同步到zookeeper，这样当Consumer失败后，新的consumer就能从zookeeper获取最新的offset
bootstrap_servers=_BROKERS)
# consumer = KafkaConsumer(bootstrap_servers=_BROKERS)
consumer.assign([TopicPartition(_TOPIC_NAME, 0)])
tp = TopicPartition(_TOPIC_NAME, 0)
print(consumer.committed(TopicPartition(_TOPIC_NAME, 0)))
# consumer.subscribe(topics=[_TOPIC_NAME])
# # Subscribe to a regex topic pattern
# consumer.subscribe(pattern='^awesome.*')
print(consumer.topics())
# partition = TopicPartition(topic=_TOPIC_NAME, partition=consumer.partitions_for_topic(_TOPIC_NAME))
# consumer.seek_to_beginning()
# consumer.seek(TopicPartition(_TOPIC_NAME, 0), 0)
consumer.seek(tp, 50) # 10 stands for start consumer from 10th offset
a = []
for m in consumer:
if len(a) < 5:
print(m.offset)
a.append(m.offset)
# consumer.commit()
# else:
# a =[]
ProduceRequestPayload = namedtuple("ProduceRequestPayload",
["topic", "partition", "messages"])
class IBUSStreamingDownsamplingConsumer:
LOG_FORMAT ="{} UTC_TS\t"\
"{}"
def __init__(self, kafkaHost, kafkaPort, tcpHost, tcpPort, group_id, topic,
logTopic, interval):
self.kafkaHost = kafkaHost
self.kafkaPort = kafkaPort
self.tcpHost = tcpHost
self.tcpPort = tcpPort
self.group_id = group_id
self.topic = topic
self.logTopic = logTopic
self.interval = int(interval)
self.consumer = KafkaConsumer(
topic,
bootstrap_servers=["{}:{}".format(kafkaHost, kafkaPort)],
group_id=group_id,
enable_auto_commit=False)
self.producer = KafkaProducer(
bootstrap_servers=["{}:{}".format(kafkaHost, kafkaPort)])
self.tcpWriter = None
def getTopicPartitions(self):
self.consumer.topics() #This ensures local cache is updated with
# information about partitions, offsets etc.
pids = self.consumer.partitions_for_topic(self.topic)
tps = [TopicPartition(self.topic, pid) for pid in pids]
return tps
def getTopicPartitionsCommittedPositions(self):
tps = self.getTopicPartitions()
ret = [(tp, self.consumer.committed(tp)) for tp in tps]
return ret
async def tcp_server_handler(self, reader, writer):
addr = str(writer.get_extra_info("socket").getpeername())
if self.tcpWriter is not None:
self.log("refused " + addr)
writer.write(b"Connection limit reached; connection refused.")
writer.close()
return
self.log("accepted " + addr)
self.tcpWriter = writer
t1 = asyncio.create_task(self.poll_from_Kafka(writer))
try:
while True:
data = await reader.read(1) # 1024*16 bytes
if not data:
break
except BrokenPipeError:
"""
Catches connecton reset by peer when we are sending the batched data,
which is also when we cannot check for reader. The broken connection
on the writer side will ultimately lead to BrokenPipeError on the
reader side. Hence
"""
pass
finally:
t1.cancel()
self.log("closed " + addr)
writer.close()
self.tcpWriter = None
async def poll_from_Kafka(self, writer):
while True:
prevPos = self.getTopicPartitionsCommittedPositions()
polled = self.consumer.poll(timeout_ms=1000)
records = [
record.value for recordList in polled.values()
for record in recordList
]
try:
for record in records:
writer.write(record)
await writer.drain()
except ConnectionResetError:
"""
The error is not thrown reliably. If a connection is broken, and
one try to
writer.write(record)
await writer.drain()
This error may not manifest. It is thrown more often when one try
to repeatedly write to and drain a broken connection.
"""
print("Last batch not fully sent, not commited.")
for tp, pos in prevPos:
self.consumer.seek(tp, pos)
break
else:
self.consumer.commit()
await asyncio.sleep(self.interval)
def log(self, msg):
self.producer.send( self.logTopic,
self.LOG_FORMAT.format( datetime.now().timestamp(),
msg
) \
.encode()
)
def cleanup(self):
self.log("shutdown")
self.consumer.close()
self.producer.flush()
self.producer.close()
def run(self):
self.log("running")
asyncio.run(self._async_run())
async def _async_run(self):
tcpServer = await asyncio.start_server(self.tcp_server_handler,
self.tcpHost, self.tcpPort)
await tcpServer.serve_forever()
class KafkaGroupReader:
def __init__(self, kafka_config):
self.log = logging.getLogger(__name__)
self.kafka_config = kafka_config
self._kafka_groups = defaultdict(lambda: defaultdict(dict))
self.active_partitions = {}
self._finished = False
def read_group(self, group_id):
partition_count = get_offset_topic_partition_count(self.kafka_config)
partition = get_group_partition(group_id, partition_count)
return self.read_groups(partition).get(group_id, [])
def read_groups(self, partition=None):
self.consumer = KafkaConsumer(
group_id='offset_monitoring_consumer',
bootstrap_servers=self.kafka_config.broker_list,
auto_offset_reset='earliest',
enable_auto_commit=False,
consumer_timeout_ms=30000,
fetch_max_wait_ms=2000,
max_partition_fetch_bytes=10 * 1024 * 1024, # 10MB
)
# Fetch metadata as partitions_for_topic only returns locally cached metadata
# See https://github.com/dpkp/kafka-python/issues/1742
self.consumer.topics()
if partition is not None:
self.active_partitions = {
partition: TopicPartition(CONSUMER_OFFSET_TOPIC, partition),
}
else:
self.active_partitions = {
p: TopicPartition(CONSUMER_OFFSET_TOPIC, p)
for p in self.consumer.partitions_for_topic(CONSUMER_OFFSET_TOPIC)
}
self.watermarks = self.get_current_watermarks(list(self.active_partitions.values()))
# Active partitions are not empty. Remove the empty ones.
self.active_partitions = {
p: tp for p, tp in self.active_partitions.items()
if tp.partition in self.watermarks and
self.watermarks[tp.partition].highmark > 0 and
self.watermarks[tp.partition].highmark > self.watermarks[tp.partition].lowmark
}
# Cannot consume if there are no active partitions
if not self.active_partitions:
return {}
self.consumer.assign(list(self.active_partitions.values()))
self.log.info("Consuming from %s", self.active_partitions)
message_iterator = iter(self.consumer)
while not self.finished():
try:
message = next(message_iterator)
except StopIteration:
continue
# Stop when reaching the last message written to the
# __consumer_offsets topic when KafkaGroupReader first started
if message.offset >= self.watermarks[message.partition].highmark - 1:
self.remove_partition_from_consumer(message.partition)
self.process_consumer_offset_message(message)
self._remove_unsubscribed_topics()
return {
group: topics.keys()
for group, topics in six.iteritems(self._kafka_groups)
if topics
}
def _remove_unsubscribed_topics(self):
for group, topics in list(six.iteritems(self._kafka_groups)):
for topic, partitions in list(six.iteritems(topics)):
# If offsets for all partitions are 0, consider the topic as unsubscribed
if not any(partitions.values()):
del self._kafka_groups[group][topic]
self.log.info("Removed group {group} topic {topic} from list of groups".format(group=group, topic=topic))
def remove_partition_from_consumer(self, partition):
deleted = self.active_partitions.pop(partition)
# Terminate if there are no more partitions to consume
if not self.active_partitions:
self.log.info("Completed reading from all partitions")
self._finished = True
return
# Reassign the remaining partitions to the consumer while saving the
# position
positions = [
(p, self.consumer.position(p))
for p in self.active_partitions.values()
]
self.consumer.assign(list(self.active_partitions.values()))
for topic_partition, position in positions:
self.consumer.seek(topic_partition, position)
self.log.info(
"Completed reading from %s. Remaining partitions: %s",
deleted,
self.active_partitions,
)
def parse_consumer_offset_message(self, message):
key = message.key
((key_schema,), cur) = relative_unpack(b'>h', key, 0)
if key_schema not in [0, 1]:
raise InvalidMessageException() # This is not an offset commit message
(group, cur) = read_short_string(key, cur)
(topic, cur) = read_short_string(key, cur)
((partition,), cur) = relative_unpack(b'>l', key, cur)
if message.value:
value = message.value
((value_schema,), cur) = relative_unpack(b'>h', value, 0)
if value_schema not in [0, 1]:
raise InvalidMessageException() # Unrecognized message value
((offset,), cur) = relative_unpack(b'>q', value, cur)
else:
offset = None # Offset was deleted
return group.decode(), topic.decode(), partition, offset
def process_consumer_offset_message(self, message):
try:
group, topic, partition, offset = self.parse_consumer_offset_message(message)
except InvalidMessageException:
return
if offset is not None:
self._kafka_groups[group][topic][partition] = offset
self.log.info(
"Updated group {group} topic {topic} and updated offset in list of groups".format(
group=group,
topic=topic,
),
)
# TODO: check if we can ever find an offset commit message with message.value is None
elif offset is None and group in self._kafka_groups and \
topic in self._kafka_groups[group]: # No offset means topic deletion
del self._kafka_groups[group][topic]
self.log.info("Removed group {group} topic {topic} from list of groups".format(group=group, topic=topic))
def get_current_watermarks(self, partitions=None):
client = KafkaToolClient(self.kafka_config.broker_list)
client.load_metadata_for_topics(CONSUMER_OFFSET_TOPIC)
offsets = get_topics_watermarks(
client,
[CONSUMER_OFFSET_TOPIC],
)
partitions_set = set(tp.partition for tp in partitions) if partitions else None
return {part: offset for part, offset
in six.iteritems(offsets[CONSUMER_OFFSET_TOPIC])
if offset.highmark > offset.lowmark and
(partitions is None or part in partitions_set)}
def finished(self):
return self._finished
