我有一个基于Django的Web应用程序，我试图在这个名为kafka-python的库的帮助下将Kafka集成。但是，当我尝试向特定主题发送消息时，出现超时错误，提示：
Traceback (most recent call last):
File "/home/paras/vertex/vertex-1.6/vertex-portal-backend/vertex_app/kafka_service.py", line 67, in send_message
x = producer.send(topic, json_data)
File "/home/paras/.local/lib/python3.6/site-packages/kafka/producer/kafka.py", line 555, in send
self._wait_on_metadata(topic, self.config['max_block_ms'] / 1000.0)
File "/home/paras/.local/lib/python3.6/site-packages/kafka/producer/kafka.py", line 682, in _wait_on_metadata
"Failed to update metadata after %.1f secs." % (max_wait,))
kafka.errors.KafkaTimeoutError: KafkaTimeoutError: Failed to update metadata after 60.0 secs.
正在生成消息：
def put_order_into_kafka(order,obj) :
try :
if order is None or offering is None :
raise Exception("Unable to put order into queue order or offering is null")
topic_name = create_kafka_topic_name(obj)
send_message(topic_name,order)
except Exception as e :
print(e)
Kafka服务
#kafka_service.py
from kafka import KafkaProducer
from kafka.admin import KafkaAdminClient, NewTopic
from .constants import KAFKA_BROKER_URL
import json
KAFKA_PRODUCER = None
def get_kafka_producer():
KAFKA_PRODUCER = init_kafka_producer_instance()
return KAFKA_PRODUCER
def init_kafka_producer_instance():
try:
if KAFKA_PRODUCER is not None :
return KAFKA_PRODUCER
producer = None
producer = KafkaProducer(bootstrap_servers=[
KAFKA_BROKER_URL], value_serializer=lambda x: json.dumps(x).encode('utf-8'))
return producer
except Exception as e:
import traceback
print(traceback.format_exc())
return None
def create_kafka_topic_instance(topic_name,num_partitions=1,replication_factor=1) :
try :
if topic_name is None :
raise Exception("Invalid argument topic name")
topic_list = []
topic_list.append(NewTopic(name=topic_name, num_partitions=num_partitions, replication_factor=replication_factor))
create_topic(topic_list)
except Exception as e :
import traceback
print(traceback.format_exc())
def create_topic(topics,validate_only=False):
try:
if topics is None:
raise Exception("Topic is None")
admin_client = get_kafka_admin_instance()
if admin_client is None:
return False
result = admin_client.create_topics(topics,validate_only)
print(result)
except Exception as e:
import traceback
print(traceback.format_exc())
def get_kafka_admin_instance():
try:
admin_client = KafkaAdminClient(bootstrap_servers=KAFKA_BROKER_URL)
return admin_client
except Exception as e:
import traceback
print(traceback.format_exc())
def send_message(topic, json_data):
try:
if topic is None or json_data is None:
raise Exception("Invalid argument topic or data")
producer = get_kafka_producer()
if producer is not None:
x = producer.send(topic, json_data)
print(x)
except Exception as e:
import traceback
print(traceback.format_exc())
def delete_topic(topic):
try:
if topic is None:
raise Exception("Topic is None")
except Exception as e:
import traceback
print(traceback.format_exc())
##Utility Functions
def create_kafka_topic_name(obj) :
try :
if offering is None :
raise Exception("Invalid argument offering, unable to create topic name")
return str(obj.order_id)
except Exception as e :
print(e)
return None
Kafka Server.properties
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You 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.
# see kafka.server.KafkaConfig for additional details and defaults
############################# Server Basics #############################
# The id of the broker. This must be set to a unique integer for each broker.
broker.id=0
############################# Socket Server Settings #############################
# The address the socket server listens on. It will get the value returned from
# java.net.InetAddress.getCanonicalHostName() if not configured.
# FORMAT:
# listeners = listener_name://host_name:port
# EXAMPLE:
# listeners = PLAINTEXT://your.host.name:9092
#listeners=PLAINTEXT://:9092
# Hostname and port the broker will advertise to producers and consumers. If not set,
# it uses the value for "listeners" if configured. Otherwise, it will use the value
# returned from java.net.InetAddress.getCanonicalHostName().
#advertised.listeners=PLAINTEXT://your.host.name:9092
advertised.listeners=PLAINTEXT://localhost:9092
# Maps listener names to security protocols, the default is for them to be the same. See the config documentation for more details
#listener.security.protocol.map=PLAINTEXT:PLAINTEXT,SSL:SSL,SASL_PLAINTEXT:SASL_PLAINTEXT,SASL_SSL:SASL_SSL
# The number of threads that the server uses for receiving requests from the network and sending responses to the network
num.network.threads=3
# The number of threads that the server uses for processing requests, which may include disk I/O
num.io.threads=8
# The send buffer (SO_SNDBUF) used by the socket server
socket.send.buffer.bytes=102400
# The receive buffer (SO_RCVBUF) used by the socket server
socket.receive.buffer.bytes=102400
# The maximum size of a request that the socket server will accept (protection against OOM)
socket.request.max.bytes=104857600
############################# Log Basics #############################
# A comma separated list of directories under which to store log files
log.dirs=/tmp/kafka-logs
# The default number of log partitions per topic. More partitions allow greater
# parallelism for consumption, but this will also result in more files across
# the brokers.
num.partitions=1
# The number of threads per data directory to be used for log recovery at startup and flushing at shutdown.
# This value is recommended to be increased for installations with data dirs located in RAID array.
num.recovery.threads.per.data.dir=1
############################# Internal Topic Settings #############################
# The replication factor for the group metadata internal topics "__consumer_offsets" and "__transaction_state"
# For anything other than development testing, a value greater than 1 is recommended for to ensure availability such as 3.
offsets.topic.replication.factor=1
transaction.state.log.replication.factor=1
transaction.state.log.min.isr=1
############################# Log Flush Policy #############################
# Messages are immediately written to the filesystem but by default we only fsync() to sync
# the OS cache lazily. The following configurations control the flush of data to disk.
# There are a few important trade-offs here:
# 1. Durability: Unflushed data may be lost if you are not using replication.
# 2. Latency: Very large flush intervals may lead to latency spikes when the flush does occur as there will be a lot of data to flush.
# 3. Throughput: The flush is generally the most expensive operation, and a small flush interval may lead to excessive seeks.
# The settings below allow one to configure the flush policy to flush data after a period of time or
# every N messages (or both). This can be done globally and overridden on a per-topic basis.
# The number of messages to accept before forcing a flush of data to disk
#log.flush.interval.messages=10000
# The maximum amount of time a message can sit in a log before we force a flush
#log.flush.interval.ms=1000
############################# Log Retention Policy #############################
# The following configurations control the disposal of log segments. The policy can
# be set to delete segments after a period of time, or after a given size has accumulated.
# A segment will be deleted whenever *either* of these criteria are met. Deletion always happens
# from the end of the log.
# The minimum age of a log file to be eligible for deletion due to age
log.retention.hours=168
# A size-based retention policy for logs. Segments are pruned from the log unless the remaining
# segments drop below log.retention.bytes. Functions independently of log.retention.hours.
#log.retention.bytes=1073741824
# The maximum size of a log segment file. When this size is reached a new log segment will be created.
log.segment.bytes=1073741824
# The interval at which log segments are checked to see if they can be deleted according
# to the retention policies
log.retention.check.interval.ms=300000
############################# Zookeeper #############################
# Zookeeper connection string (see zookeeper docs for details).
# This is a comma separated host:port pairs, each corresponding to a zk
# server. e.g. "127.0.0.1:3000,127.0.0.1:3001,127.0.0.1:3002".
# You can also append an optional chroot string to the urls to specify the
# root directory for all kafka znodes.
zookeeper.connect=localhost:2181
# Timeout in ms for connecting to zookeeper
zookeeper.connection.timeout.ms=6000
############################# Group Coordinator Settings #############################
# The following configuration specifies the time, in milliseconds, that the GroupCoordinator will delay the initial consumer rebalance.
# The rebalance will be further delayed by the value of group.initial.rebalance.delay.ms as new members join the group, up to a maximum of max.poll.interval.ms.
# The default value for this is 3 seconds.
# We override this to 0 here as it makes for a better out-of-the-box experience for development and testing.
# However, in production environments the default value of 3 seconds is more suitable as this will help to avoid unnecessary, and potentially expensive, rebalances during application startup.
group.initial.rebalance.delay.ms=0
但是，我尝试从该应用程序中编写一个虚拟函数，因此能够将消息放入队列中。我对python和Kafka相当陌生，我不确定哪里出了问题。有人可以帮我吗？
答案 0 :(得分：3)
您还必须定义listeners：
listeners=PLAINTEXT://:9092