kafka是干什么的，有和特性，我这里就不多说，详情自己研究官方文档。
0. 背景介绍
我需要在三台机器上分别部署kafka broker的实例，构建成一个集群。
kafka的broker集群，是基于zookeeper作为协调器或者资源同步管理器的，主要是记录High Level Offset标记信息的。 另外，zookeeper还用作broker的选主以及partition的选主。
三台机器上分别安装zookeeper和kafka。
10.90.7.2 Linux localhost.localdomain 2.6.18-274.el5 #1 SMP Fri Jul 8 17:36:59 EDT 2011 x86_64 x86_64 x86_64 GNU/Linux 10.90.2.101 Linux bogon 3.10.0-229.el7.x86_64 #1 SMP Thu Jan 29 18:37:38 EST 2015 x86_64 x86_64 x86_64 GNU/Linux 10.90.2.102 Linux localhost.localdomain 3.10.0-229.el7.x86_64 #1 SMP Thu Jan 29 18:37:38 EST 2015 x86_64 x86_64 x86_64 GNU/Linux
1. 软件下载
下载kafka 1.0.1版本
https://www.apache.org/dyn/closer.cgi?path=/kafka/1.0.1/kafka_2.11-1.0.1.tgz
遵循我一贯的原则，为了生产环境的稳定性，不会去首先使用最新版本，当前这个是次新版本。最新的版本是1.1.0，Released March 28, 2018。
下载zookeeper 3.4.9
https://archive.apache.org/dist/zookeeper/zookeeper-3.4.9/zookeeper-3.4.9.tar.gz
这个是当前稳定运行的版本，是次新版，最新的版本，有几个alpha和beta的，版本好最高达到3.5.4了。
2. 软件安装
2.1 zookeeper安装，三台服务器构建最小集群，保证paxos的选主算法正常运行。配置很简单，下面就只是将配置数据贴出来。
# The number of milliseconds of each tick tickTime=2000 # The number of ticks that the initial # synchronization phase can take initLimit=10 # The number of ticks that can pass between # sending a request and getting an acknowledgement syncLimit=5 # the directory where the snapshot is stored. # do not use /tmp for storage, /tmp here is just # example sakes. dataDir=/opt/shihuc/zookeeper-3.4.9/zkData/data dataLogDir=/opt/shihuc/zookeeper-3.4.9/zkData/logs # the port at which the clients will connect clientPort=2181 # the maximum number of client connections. # increase this if you need to handle more clients maxClientCnxns=60 # # Be sure to read the maintenance section of the # administrator guide before turning on autopurge. # # http://zookeeper.apache.org/doc/current/zookeeperAdmin.html#sc_maintenance # # The number of snapshots to retain in dataDir autopurge.snapRetainCount=3 # Purge task interval in hours # Set to "0" to disable auto purge feature autopurge.purgeInterval=1 server.1=10.90.7.2:2888:3888 server.2=10.90.2.101:2888:3888 server.3=10.90.2.102:2888:3888
注意，在每一台zookeeper所在的机器对应配置文件dataDir所在的路径下创建myid，myid文件存放zookeeper服务器的编号（正如配置文件中server.x中的x，本案例中x是1,2,3）。
启动zookeeper，查看启动脚本的帮助信息：
[root@localhost bin]# ./zkServer.sh ZooKeeper JMX enabled by default Using config: /opt/shihuc/zookeeper-3.4.9/bin/../conf/zoo.cfg Usage: ./zkServer.sh {start|start-foreground|stop|restart|status|upgrade|print-cmd}
正常启动操作（三台机器，都做相同操作）：
[root@localhost bin]# ./zkServer.sh start ZooKeeper JMX enabled by default Using config: /opt/shihuc/zookeeper-3.4.9/bin/../conf/zoo.cfg Starting zookeeper ... STARTED
检查几个zookeeper的状态：
[root@localhost bin]# ./zkServer.sh status #---10.90.7.2 ZooKeeper JMX enabled by default Using config: /opt/shihuc/zookeeper-3.4.9/bin/../conf/zoo.cfg Mode: leader [root@localhost bin]# ./zkServer.sh status #---10.90.2.101 ZooKeeper JMX enabled by default Using config: /opt/shihuc/zookeeper-3.4.9/bin/../conf/zoo.cfg Mode: follower [root@localhost bin]# ./zkServer.sh status #---10.90.2.102 ZooKeeper JMX enabled by default Using config: /opt/shihuc/zookeeper-3.4.9/bin/../conf/zoo.cfg Mode: follower
2.2 安装kafka
安装很简单，直接将下载的kafka软件的包解压即可，然后配置一下config下面的server.properties文件，主要是修改log路径以及zookeeper的监听地址。然后运行bin下面的kafka-server-start.sh即可。
配置信息：
# 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 # 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=/opt/shihuc/kafka_2.11-1.0.1/logDir # 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=10.90.7.2:2181,10.90.2.101:2181,10.90.2.102:2181 # 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
启动kafka服务：
[root@localhost bin]# nohup ./kafka-server-start.sh ../config/server.properties &
对三台机器都做broker的启动操作，遇到下面的问题：
[2018-06-12 14:22:38,986] INFO [TransactionCoordinator id=0] Startup complete. (kafka.coordinator.transaction.TransactionCoordinator) [2018-06-12 14:22:39,013] INFO Creating /brokers/ids/0 (is it secure? false) (kafka.utils.ZKCheckedEphemeral) [2018-06-12 14:22:39,021] INFO Result of znode creation is: NODEEXISTS (kafka.utils.ZKCheckedEphemeral) [2018-06-12 14:22:39,022] FATAL [KafkaServer id=0] Fatal error during KafkaServer startup. Prepare to shutdown (kafka.server.KafkaServer) java.lang.RuntimeException: A broker is already registered on the path /brokers/ids/0. This probably indicates that you either have configured a brokerid that is already in use, or else you have shutdown this broker and restarted it fas ter than the zookeeper timeout so it appears to be re-registering. at kafka.utils.ZkUtils.registerBrokerInZk(ZkUtils.scala:440) at kafka.utils.ZkUtils.registerBrokerInZk(ZkUtils.scala:426) at kafka.server.KafkaHealthcheck.register(KafkaHealthcheck.scala:73) at kafka.server.KafkaHealthcheck.startup(KafkaHealthcheck.scala:53) at kafka.server.KafkaServer.startup(KafkaServer.scala:287) at kafka.server.KafkaServerStartable.startup(KafkaServerStartable.scala:38) at kafka.Kafka$.main(Kafka.scala:92) at kafka.Kafka.main(Kafka.scala) [2018-06-12 14:22:39,024] INFO [KafkaServer id=0] shutting down (kafka.server.KafkaServer) [2018-06-12 14:22:39,025] INFO [SocketServer brokerId=0] Stopping socket server request processors (kafka.network.SocketServer) [2018-06-12 14:22:39,034] INFO [SocketServer brokerId=0] Stopped socket server request processors (kafka.network.SocketServer) [2018-06-12 14:22:39,034] INFO [Kafka Request Handler on Broker 0], shutting down (kafka.server.KafkaRequestHandlerPool) [2018-06-12 14:22:39,036] INFO [Kafka Request Handler on Broker 0], shut down completely (kafka.server.KafkaRequestHandlerPool) [2018-06-12 14:22:39,038] INFO [KafkaApi-0] Shutdown complete. (kafka.server.KafkaApis) [2018-06-12 14:22:39,038] INFO [ExpirationReaper-0-topic]: Shutting down (kafka.server.DelayedOperationPurgatory$ExpiredOperationReaper) [2018-06-12 14:22:39,149] INFO [ExpirationReaper-0-topic]: Stopped (kafka.server.DelayedOperationPurgatory$ExpiredOperationReaper) [2018-06-12 14:22:39,149] INFO [ExpirationReaper-0-topic]: Shutdown completed (kafka.server.DelayedOperationPurgatory$ExpiredOperationReaper) [2018-06-12 14:22:39,151] INFO [TransactionCoordinator id=0] Shutting down. (kafka.coordinator.transaction.TransactionCoordinator) [2018-06-12 14:22:39,151] INFO [ProducerId Manager 0]: Shutdown complete: last producerId assigned 3000 (kafka.coordinator.transaction.ProducerIdManager) [2018-06-12 14:22:39,152] INFO [Transaction State Manager 0]: Shutdown complete (kafka.coordinator.transaction.TransactionStateManager) [2018-06-12 14:22:39,152] INFO [Transaction Marker Channel Manager 0]: Shutting down (kafka.coordinator.transaction.TransactionMarkerChannelManager)
错误原因是server.properties文件中的broker.id的值，在集群环境下重复了，即，一个kafka的集群环境下，broker.id的值是不能重复的，必须唯一。就算kafka服务在不同机器上。
3. 验证环境
3.1 创建一个topic
在10.90.2.102上操作：
[root@localhost bin]# ./kafka-topics.sh --create --zookeeper 10.90.7.2:2181,10.90.2.101:2181,10.90.2.102:2181 --replication-factor 3 --partitions 1 --topic first Created topic "first".
同一台机器上重复操作：
[root@localhost bin]# ./kafka-topics.sh --create --zookeeper 10.90.7.2:2181,10.90.2.101:2181,10.90.2.102:2181 --replication-factor 3 --partitions 1 --topic first Error while executing topic command : Topic 'first' already exists. [2018-06-12 14:45:01,490] ERROR org.apache.kafka.common.errors.TopicExistsException: Topic 'first' already exists. (kafka.admin.TopicCommand$)
在10.90.7.2机器上创建相同的topic：
[root@localhost bin]# ./kafka-topics.sh --create --zookeeper 10.90.7.2:2181,10.90.2.101:2181,10.90.2.102:2181 --replication-factor 3 --partitions 1 --topic first Error while executing topic command : Topic 'first' already exists. [2018-06-12 14:59:29,611] ERROR org.apache.kafka.common.errors.TopicExistsException: Topic 'first' already exists. (kafka.admin.TopicCommand$)
同一个名称的topic，在一个kafka的集群环境下，不能重复创建。
3.2 创建一个kafka的生产者
在10.90.2.101上操作：
[root@localhost bin]# ./kafka-console-producer.sh --broker-list 10.90.7.2:9092,10.90.2.101:9092,10.90.2.102:9092 --topic first > [2018-06-12 14:51:15,514] WARN [Producer clientId=console-producer] Error while fetching metadata with correlation id 3 : {first=LEADER_NOT_AVAILABLE} (org.apache.kafka.clients.NetworkClient) [2018-06-12 14:51:15,655] WARN [Producer clientId=console-producer] Error while fetching metadata with correlation id 4 : {first=LEADER_NOT_AVAILABLE} (org.apache.kafka.clients.NetworkClient) [2018-06-12 14:51:15,761] WARN [Producer clientId=console-producer] Error while fetching metadata with correlation id 5 : {first=LEADER_NOT_AVAILABLE} (org.apache.kafka.clients.NetworkClient) [2018-06-12 14:51:15,868] WARN [Producer clientId=console-producer] Error while fetching metadata with correlation id 6 : {first=LEADER_NOT_AVAILABLE} (org.apache.kafka.clients.NetworkClient) [2018-06-12 14:51:15,975] WARN [Producer clientId=console-producer] Error while fetching metadata with correlation id 7 : {first=LEADER_NOT_AVAILABLE} (org.apache.kafka.clients.NetworkClient) [2018-06-12 14:51:16,083] WARN [Producer clientId=console-producer] Error while fetching metadata with correlation id 8 : {first=LEADER_NOT_AVAILABLE} (org.apache.kafka.clients.NetworkClient) [2018-06-12 14:51:16,189] WARN [Producer clientId=console-producer] Error while fetching metadata with correlation id 9 : {first=LEADER_NOT_AVAILABLE} (org.apache.kafka.clients.NetworkClient)
经过反复测试验证环境配置信息，最终参考了他人的经验，是kafka的server.properties的配置错误。主要是下面的内容配置有问题：
listeners=PLAINTEXT://:9092
将这句注释掉，然后在配置文件中添加下面的两行配置，指明当前broker的地址：
port=9092 host.name=10.90.7.2 #依据具体的服务器，配置相应的服务器的IP地址即可。
修改后，再次重启kafka服务，重新在某台服务器上启动消息生产者服务，例如在10.90.2.102上：
[root@localhost bin]# ./kafka-console-producer.sh --broker-list 10.90.7.2:9092,10.90.2.101:9092,10.90.2.102:9092 --topic first >hello >good >
然后在另外一台服务器上，启动消息消费者，例如在10.90.7.2上：
[root@localhost bin]# ./kafka-console-consumer.sh --bootstrap-server 10.90.7.2:9092,10.90.2.101:9092,10.90.2.102:9092 --topic hello good
到此为止，kafka生产者消费者，在控制台下消息收发正常，说明kafka的环境配置成功。
3.3 查看不同的topic下的broker信息
[root@localhost bin]# ./kafka-topics.sh --describe --zookeeper 10.90.7.2:2181,10.90.2.101:2181,10.90.2.102:2181 --topic first Topic:first PartitionCount:1 ReplicationFactor:3 Configs: Topic: first Partition: 0 Leader: 1 Replicas: 1,2,3 Isr: 1,2,3 [root@localhost bin]# ./kafka-topics.sh --describe --zookeeper 10.90.7.2:2181,10.90.2.101:2181,10.90.2.102:2181 --topic second Topic:second PartitionCount:2 ReplicationFactor:3 Configs: Topic: second Partition: 0 Leader: 3 Replicas: 3,1,2 Isr: 3,2,1 Topic: second Partition: 1 Leader: 1 Replicas: 1,2,3 Isr: 1,2,3
这是输出解释。第一行给出了各个分区的概况，分区有几个就有几行分区详细信息介绍。（我创建了两个topic，一个是first，只有一个分区；一个是second，两个分区）
Leader 是负责当前分区的所有读写请求。每个节点都将领导一个随机选择的分区。
Replicas 是节点列表，复制分区日志，不管他们是不是Leader或者不管它们是否还活着。
Isr 是in-sync的集合。这是Replicas列表当前还活着的子集。
总体来说，Kafka的环境构建，还是比较容易的，配置信息，相对来说，也比较容易理解。到此，环境的bring up工作完美收工。