kafka是干什么的，有和特性，我這里就不多說，詳情自己研究官方文檔。
0. 背景介紹
我需要在三台機器上分別部署kafka broker的實例，構建成一個集群。
kafka的broker集群，是基於zookeeper作為協調器或者資源同步管理器的，主要是記錄High Level Offset標記信息的。 另外，zookeeper還用作broker的選主以及partition的選主。
三台機器上分別安裝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. 軟件下載
下載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
遵循我一貫的原則，為了生產環境的穩定性，不會去首先使用最新版本，當前這個是次新版本。最新的版本是1.1.0，Released March 28, 2018。
下載zookeeper 3.4.9
https://archive.apache.org/dist/zookeeper/zookeeper-3.4.9/zookeeper-3.4.9.tar.gz
這個是當前穩定運行的版本，是次新版，最新的版本，有幾個alpha和beta的，版本好最高達到3.5.4了。
2. 軟件安裝
2.1 zookeeper安裝，三台服務器構建最小集群，保證paxos的選主算法正常運行。配置很簡單，下面就只是將配置數據貼出來。
# 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所在的機器對應配置文件dataDir所在的路徑下創建myid，myid文件存放zookeeper服務器的編號（正如配置文件中server.x中的x，本案例中x是1,2,3）。
啟動zookeeper，查看啟動腳本的幫助信息：
[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}
正常啟動操作（三台機器，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
檢查幾個zookeeper的狀態：
[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 安裝kafka
安裝很簡單，直接將下載的kafka軟件的包解壓即可，然后配置一下config下面的server.properties文件，主要是修改log路徑以及zookeeper的監聽地址。然后運行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
啟動kafka服務：
[root@localhost bin]# nohup ./kafka-server-start.sh ../config/server.properties &
對三台機器都做broker的啟動操作，遇到下面的問題：
[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)
錯誤原因是server.properties文件中的broker.id的值，在集群環境下重復了，即，一個kafka的集群環境下，broker.id的值是不能重復的，必須唯一。就算kafka服務在不同機器上。
3. 驗證環境
3.1 創建一個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".
同一台機器上重復操作：
[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$)
在10.90.7.2機器上創建相同的topic：
[root@localhost bin]# ./kafka-topics.sh --create --zookeeper 10.90.7.2:2181,10.90.2.101:2181,10.90.2.102:2181 --replication-factor 3 --partitions 1 --topic first Error while executing topic command : Topic 'first' already exists. [2018-06-12 14:59:29,611] ERROR org.apache.kafka.common.errors.TopicExistsException: Topic 'first' already exists. (kafka.admin.TopicCommand$)
同一個名稱的topic，在一個kafka的集群環境下，不能重復創建。
3.2 創建一個kafka的生產者
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)
經過反復測試驗證環境配置信息，最終參考了他人的經驗，是kafka的server.properties的配置錯誤。主要是下面的內容配置有問題：
listeners=PLAINTEXT://:9092
將這句注釋掉，然后在配置文件中添加下面的兩行配置，指明當前broker的地址：
port=9092 host.name=10.90.7.2 #依據具體的服務器，配置相應的服務器的IP地址即可。
修改后，再次重啟kafka服務，重新在某台服務器上啟動消息生產者服務，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 >
然后在另外一台服務器上，啟動消息消費者，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
到此為止，kafka生產者消費者，在控制台下消息收發正常，說明kafka的環境配置成功。
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
這是輸出解釋。第一行給出了各個分區的概況，分區有幾個就有幾行分區詳細信息介紹。（我創建了兩個topic，一個是first，只有一個分區；一個是second，兩個分區）
Leader 是負責當前分區的所有讀寫請求。每個節點都將領導一個隨機選擇的分區。
Replicas 是節點列表，復制分區日志，不管他們是不是Leader或者不管它們是否還活着。
Isr 是in-sync的集合。這是Replicas列表當前還活着的子集。
總體來說，Kafka的環境構建，還是比較容易的，配置信息，相對來說，也比較容易理解。到此，環境的bring up工作完美收工。