我正在尝试使用谷歌云计算引擎虚拟机实例作为卡夫卡消费者。我发现VM阻止来自任何外部计算机的流量，我成功设置防火墙规则以从本地计算机访问VM。
我可以在云VM实例上创建和列出主题。但是我无法发送和接收来自kafka主题的消息。 它会抛出超时异常。
我使用telnet来检查端口是否打开，我也获得了端口的Escape序列（9092）。
当我尝试使用另一个云VM实例实现相同的功能时，我可以执行所有kafka操作。 （发送/接收消息，创建/列出主题）
到目前为止，我只尝试使用kafka控制台生产者和控制台消费者。
我一直试图从上周开始解决这个问题。如果有人可以帮助我，那将是一个很大的帮助。
我在单个云虚拟机上运行kafka服务器和消费者。我想使用Raspberry Pi作为制作人。
提前致谢。
更新
我的config / server.properties文件如下
# 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://localhost: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://35.196.XXX.XXX:9092 #Google VM External IP
# 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 seperated 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 exceessive 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
当我在My local machine上运行以下命令时
bin/kafka-console-consumer.sh --bootstrap-server 35.196.227.191:9092 --topic test --from-beginning
我的Google VM实例上出现以下错误：
[2018-02-04 12:42:19,839] ERROR [KafkaApi-0] Number of alive brokers '0' does not meet the required replication factor '1' for the offsets topic (configured via 'offsets.topic.replication.factor'). This error can be ignored if the cluster is starting up and not all brokers are up yet. (kafka.server.KafkaApis)
但是当我看到服务器启动时的日志时，
[2018-02-04 12:33:39,995] INFO [GroupMetadataManager brokerId=0] Removed 0 expired offsets in 1 milliseconds. (kafka.coordinator.group.GroupMetadataManager)
[2018-02-04 12:33:40,012] INFO [ProducerId Manager 0]: Acquired new producerId block (brokerId:0,blockStartProducerId:1000,blockEndProducerId:1999) by writing to Zk with path version 2 (kafka.coordinator.transaction.ProducerIdManager)
[2018-02-04 12:33:40,081] INFO [TransactionCoordinator id=0] Starting up. (kafka.coordinator.transaction.TransactionCoordinator)
[2018-02-04 12:33:40,095] INFO [TransactionCoordinator id=0] Startup complete. (kafka.coordinator.transaction.TransactionCoordinator)
[2018-02-04 12:33:40,099] INFO [Transaction Marker Channel Manager 0]: Starting (kafka.coordinator.transaction.TransactionMarkerChannelManager)
[2018-02-04 12:33:40,249] INFO Creating /brokers/ids/0 (is it secure? false) (kafka.utils.ZKCheckedEphemeral)
[2018-02-04 12:33:40,268] INFO Result of znode creation is: OK (kafka.utils.ZKCheckedEphemeral)
---> [2018-02-04 12:33:40,270] INFO Registered broker 0 at path /brokers/ids/0 with addresses: EndPoint(35.196.XXX.XXX,9092,ListenerName(PLAINTEXT),PLAINTEXT) (kafka.utils.ZkUtils)
[2018-02-04 12:33:40,282] INFO Kafka version : 1.0.0 (org.apache.kafka.common.utils.AppInfoParser)
[2018-02-04 12:33:40,282] INFO Kafka commitId : aaa7af6d4a11b29d (org.apache.kafka.common.utils.AppInfoParser)
[2018-02-04 12:33:40,286] INFO [KafkaServer id=0] started (kafka.server.KafkaServer)
当我看到行---＆gt; （检查上面的日志）时，它表示经纪人已注册。有人可以解释发生了什么。
答案 0 :(得分：0)
我认为有几个潜在的问题。