def comsumer():
# consumer = SimpleConsumer(client, group=None,
# topic=topic, partitions=[0, ],
# auto_commit=False)
# node_id = list(consumer.client.conns.keys())[0]
# print dir(consumer.client.conns[node_id])
# for i in consumer.get_messages(100):
# print i.offset
# consumer.commit()
# from pykafka import KafkaClient
#
# client = KafkaClient(hosts="127.0.0.1:9092")
# print client.topics
# topic1 = client.topics[topic]
# consumer = topic1.get_simple_consumer(auto_commit_enable=True, )
# for message in consumer:
# if message is not None:
# print message.offset, message.value
connect_str = '127.0.0.1:9092'
consumer = KafkaConsumer(topic, group_id='my-group', bootstrap_servers=[connect_str],
auto_offset_reset='largest',auto_commit_enable=True,
auto_commit_interval_messages=1000)# largest,smallest
consumer.set_topic_partitions((topic, 2, 50032),) # Optionally specify offsets to start from
# kafka.set_topic_partitions("topic1", ("topic2", 2), {"topic3": 0}) #partition只能被一个消费者消费,所以最好指定消费哪个partitions
# kafka.set_topic_partitions({ ("topic1", 0): 12, ("topic2", 1): 45 })
# print consumer.topics
for message in consumer:
print ("%s:%d:%d: key=%s value=%s" % (message.topic, message.partition,
message.offset, message.key,
message.value))
consumer.commit()
def consume(args):
schema = args.schema
table = args.table
assert schema in settings.SCHEMAS, 'schema must in settings.SCHEMAS'
assert table in settings.TABLES, 'table must in settings.TABLES'
group_id = f'{schema}.{table}'
consumer = KafkaConsumer(
bootstrap_servers=settings.KAFKA_SERVER,
value_deserializer=lambda x: json.loads(x, object_hook=object_hook),
key_deserializer=lambda x: x.decode() if x else None,
enable_auto_commit=False,
group_id=group_id,
auto_offset_reset='earliest',
)
topic = settings.KAFKA_TOPIC
partition = settings.PARTITIONS.get(group_id)
consumer.assign([TopicPartition(topic, partition)])
event_list = []
logger.info(
f'success consume topic:{topic},partition:{partition},schema:{schema},table:{table}'
)
pk = reader.get_primary_key(schema, table)
for msg in consumer: # type:ConsumerRecord
logger.debug(f'kafka msg:{msg}')
event = msg.value
event_list.append(event)
len_event = len(event_list)
if len_event == settings.INSERT_NUMS or (
(int(time.time() * 10**6) - event_list[0]['event_unixtime']) /
10**6 >= settings.INSERT_INTERVAL > 0):
data_dict = {}
tmp_data = []
for items in event_list:
action = items['action']
action_core = items['action_core']
data_dict.setdefault(table + schema + action + action_core,
[]).append(items)
for k, v in data_dict.items():
tmp_data.append(v)
result = writer.insert_event(tmp_data, settings.SKIP_TYPE,
settings.SKIP_DELETE_TB_NAME, schema,
table, pk)
if result:
event_list = []
consumer.commit()
logger.info(f'commit success {len_event} events!')
else:
logger.error('insert event error!')
exit()
def commitTopic(topic, group, partition, commit_offset):
try:
print(
'===================================================================================='
)
print('[commitTopic] : topic=' + topic + ', group=' + group +
', partition=' + str(partition) + ', commit_offset=' +
str(commit_offset))
consumer2 = KafkaConsumer(bootstrap_servers=tmpbootstrap_servers,
enable_auto_commit=False,
group_id=group)
tp = TopicPartition(topic, partition)
if int(commit_offset) > 0:
consumer2.commit({tp: OffsetAndMetadata(commit_offset, None)})
except Exception as ee:
print('error when commit Topic')
print(str(ee))
finally:
print('commitTopic end')
def consume(args):
schema = args.schema
tables = args.tables
skip_error = args.skip_error
assert schema in settings.SCHEMAS, f'schema {schema} must in settings.SCHEMAS'
topic = settings.KAFKA_TOPIC
tables_pk = {}
partitions = []
for table in tables.split(','):
assert table in settings.TABLES, f'table {table} must in settings.TABLES'
partition = settings.PARTITIONS.get(f'{schema}.{table}')
tp = TopicPartition(topic, partition)
partitions.append(tp)
tables_pk[table] = reader.get_primary_key(schema, table)
group_id = f'{schema}.{tables}'
consumer = KafkaConsumer(
bootstrap_servers=settings.KAFKA_SERVER,
value_deserializer=lambda x: json.loads(x, object_hook=object_hook),
key_deserializer=lambda x: x.decode() if x else None,
enable_auto_commit=False,
group_id=group_id,
auto_offset_reset='earliest',
)
consumer.assign(partitions)
event_list = {}
is_insert = False
last_time = 0
len_event = 0
logger.info(f'success consume topic:{topic},partitions:{partitions},schema:{schema},tables:{tables}')
for msg in consumer: # type:ConsumerRecord
logger.debug(f'kafka msg:{msg}')
event = msg.value
event_unixtime = event['event_unixtime'] / 10 ** 6
table = event['table']
schema = event['schema']
event_list.setdefault(table, []).append(event)
len_event += 1
if last_time == 0:
last_time = event_unixtime
if len_event == settings.INSERT_NUMS:
is_insert = True
else:
if event_unixtime - last_time >= settings.INSERT_INTERVAL > 0:
is_insert = True
if is_insert:
data_dict = {}
events_num = 0
for table, items in event_list.items():
for item in items:
action = item['action']
action_core = item['action_core']
data_dict.setdefault(table, {}).setdefault(table + schema + action + action_core, []).append(item)
for table, v in data_dict.items():
tmp_data = []
for k1, v1 in v.items():
events_num += len(v1)
tmp_data.append(v1)
try:
result = writer.insert_event(tmp_data, schema, table, tables_pk.get(table))
if not result:
logger.error('insert event error!')
if not skip_error:
exit()
except Exception as e:
logger.error(f'insert event error!,error:{e}')
if not skip_error:
exit()
consumer.commit()
logger.info(f'commit success {events_num} events!')
event_list = {}
is_insert = False
len_event = last_time = 0
def consume(args):
schema = args.schema
skip_error = args.skip_error
auto_offset_reset = args.auto_offset_reset
topic = settings.KAFKA_TOPIC
tables_pk = {}
tables = settings.SCHEMAS.get(schema)
partitions = []
for table in tables:
partition = settings.PARTITIONS.get(schema)
tp = TopicPartition(topic, partition)
partitions.append(tp)
tables_pk[table] = reader.get_primary_key(schema, table)
consumer = KafkaConsumer(
bootstrap_servers=settings.KAFKA_SERVER,
value_deserializer=lambda x: json.loads(x, object_hook=object_hook),
key_deserializer=lambda x: x.decode() if x else None,
enable_auto_commit=False,
group_id=schema,
auto_offset_reset=auto_offset_reset,
)
consumer.assign(partitions)
event_list = {}
is_insert = False
last_time = 0
len_event = 0
logger.info(
f'success consume topic:{topic},partitions:{partitions},schema:{schema},tables:{tables}'
)
for msg in consumer: # type:ConsumerRecord
logger.debug(f'kafka msg:{msg}')
event = msg.value
event_unixtime = event['event_unixtime'] / 10**6
table = event['table']
schema = event['schema']
action = event['action']
if action == 'query':
do_query = True
query = event['values']['query']
else:
do_query = False
query = None
event_list.setdefault(table, []).append(event)
len_event += 1
if last_time == 0:
last_time = event_unixtime
if len_event == settings.INSERT_NUMS:
is_insert = True
else:
if event_unixtime - last_time >= settings.INSERT_INTERVAL > 0:
is_insert = True
if is_insert or do_query:
data_dict = {}
events_num = 0
for table, items in event_list.items():
for item in items:
action = item['action']
action_core = item['action_core']
data_dict.setdefault(table, {}).setdefault(
table + schema + action + action_core, []).append(item)
for table, v in data_dict.items():
tmp_data = []
for k1, v1 in v.items():
events_num += len(v1)
tmp_data.append(v1)
try:
result = writer.insert_event(tmp_data, schema, table,
tables_pk.get(table))
if not result:
logger.error('insert event error!')
if not skip_error:
exit()
if settings.UI_ENABLE:
insert_into_redis('consumer', schema, table, len(v1))
except Exception as e:
logger.error(f'insert event error!,error:{e}')
if not skip_error:
exit()
if do_query:
try:
logger.info(f'execute query:{query}')
writer.execute(query)
except Exception as e:
logger.error(f'execute query error!,error:{e}')
if not skip_error:
exit()
consumer.commit()
logger.info(f'commit success {events_num} events!')
event_list = {}
is_insert = False
len_event = last_time = 0
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()
def consume(args):
settings = Global.settings
writer = Global.writer
reader = Global.reader
schema = args.schema
skip_error = args.skip_error
auto_offset_reset = args.auto_offset_reset
offset = args.offset
topic = settings.kafka_topic
tables_pk = {}
schema_table = settings.schema_table.get(schema)
tables = schema_table.get("tables")
for table in tables:
tables_pk[table] = reader.get_primary_key(schema, table)
consumer = KafkaConsumer(
bootstrap_servers=settings.kafka_server,
value_deserializer=lambda x: json.loads(x, object_hook=object_hook),
key_deserializer=lambda x: x.decode() if x else None,
enable_auto_commit=False,
group_id=schema,
auto_offset_reset=auto_offset_reset,
)
partition = schema_table.get("kafka_partition")
topic_partition = TopicPartition(topic, partition)
consumer.assign([topic_partition])
if offset:
consumer.seek(topic_partition, offset)
event_list = {}
is_insert = False
last_time = 0
len_event = 0
logger.info(
f"success consume topic:{topic},partitions:{partition},schema:{schema},tables:{tables}"
)
for msg in consumer: # type:ConsumerRecord
logger.debug(f"kafka msg:{msg}")
event = msg.value
event_unixtime = event["event_unixtime"] / 10**6
table = event["table"]
schema = event["schema"]
action = event["action"]
if action == "query":
alter_table = True
query = event["values"]["query"]
else:
alter_table = False
query = None
event_list.setdefault(table, []).append(event)
len_event += 1
if last_time == 0:
last_time = event_unixtime
if len_event == settings.insert_num:
is_insert = True
else:
if event_unixtime - last_time >= settings.insert_interval > 0:
is_insert = True
if is_insert or alter_table:
data_dict = {}
events_num = 0
for table, items in event_list.items():
for item in items:
action = item["action"]
action_core = item["action_core"]
data_dict.setdefault(table, {}).setdefault(
table + schema + action + action_core, []).append(item)
for table, v in data_dict.items():
tmp_data = []
for k1, v1 in v.items():
events_num += len(v1)
tmp_data.append(v1)
try:
result = writer.insert_event(tmp_data, schema, table,
tables_pk.get(table))
if not result:
logger.error("insert event error!")
if not skip_error:
exit()
except Exception as e:
logger.error(f"insert event error!,error:{e}")
if not skip_error:
exit()
if alter_table:
try:
logger.info(f"execute query:{query}")
writer.execute(query)
except Exception as e:
logger.error(f"execute query error!,error:{e}")
if not skip_error:
exit()
consumer.commit()
logger.info(f"commit success {events_num} events!")
event_list = {}
is_insert = False
len_event = last_time = 0