第一步：准備
1. 操作系統
CentOS-7-x86_64-Everything-1511
2. 安裝包
kafka_2.12-0.10.2.0.tgz
zookeeper-3.4.9.tar.gz
3. Java 環境
Zookeeper 和 Kafka 的運行都需要 Java 環境，Kafka 默認使用 G1 垃圾回收器。如果不更改垃圾回收期，官方推薦使用 7u51 以上版本的 JRE 。如果使用老版本的 JRE，需要更改 Kafka 的啟動腳本，指定 G1 以外的垃圾回收器。
本文使用系統自帶的 Java 環境。
第二步：Zookeeper 集群搭建
1. 簡介
Kafka 依賴 Zookeeper 管理自身集群（Broker、Offset、Producer、Consumer等），所以先要安裝 Zookeeper。
為了達到高可用的目的，Zookeeper 自身也不能是單點，接下來就介紹如何搭建一個最小的 Zookeeper 集群（3個 zk 節點）。
2. 安裝
# tar zxvf zookeeper-3.4.9.tar.gz # mv zookeeper-3.4.9 zookeeper
3. 配置
1）配置文件位置
路徑：zookeeper/conf
2）生成配置文件
將 zoo_sample.cfg 復制一份，命名為 zoo.cfg，此即為Zookeeper的配置文件。
# cd zookeeper
# cd conf
# cp zoo_sample.cfg zoo.cfg
3）編輯配置文件
默認配置：
配置完成：
# 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=/root/zookeeper/data
dataLogDir=/root/zookeeper/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.0=192.168.6.128:4001:4002 server.1=192.168.6.129:4001:4002 server.2=192.168.6.130:4001:4002
說明：
- dataDir 和 dataLogDir 需要在啟動前創建完成
- clientPort 為 zookeeper的服務端口
- server.0、server.1、server.2 為 zk 集群中三個 node 的信息，定義格式為 hostname:port1:port2，其中 port1 是 node 間通信使用的端口，port2 是node 選舉使用的端口，需確保三台主機的這兩個端口都是互通的。
4. 更改日志配置
Zookeeper 默認會將控制台信息輸出到啟動路徑下的 zookeeper.out 中，通過如下方法，可以讓 Zookeeper 輸出按尺寸切分的日志文件：
1）修改conf/log4j.properties文件，將
zookeeper.root.logger=INFO, CONSOLE
改為
zookeeper.root.logger=INFO, ROLLINGFILE
2）修改bin/zkEnv.sh文件，將
ZOO_LOG4J_PROP="INFO,CONSOLE"
改為
ZOO_LOG4J_PROP="INFO,ROLLINGFILE"
5. 按照上述操作，在另外兩台主機上安裝並配置 zookeeper
6. 創建 myid 文件
分別在三台主機的 dataDir 路徑下創建一個文件名為 myid 的文件，文件內容為該 zk 節點的編號。
例如，在第一台主機上建立的 myid 文件內容是 0，第二台是 1。
7. 啟動
啟動三台主機上的 zookeeper 服務
# cd bin
# ./zkServer.sh start
返回信息：
8. 查看集群狀態
3個節點啟動完成后，可依次執行如下命令查看集群狀態：
./zkServer.sh status
192.168.6.128 返回：
192.168.6.129 返回：
192.168.6.130 返回：
如上所示，3個節點中，有1個 leader 和兩個 follower。
9. 測試集群高可用性
1）停掉集群中的為 leader 的 zookeeper 服務，本文中的leader為 server2。
# ./zkServer.sh stop
返回信息：
2）查看集群中 server0 和 server1 的的狀態
server0：
server1：
此時，server1 成為了集群中的 leader，server0依然為 follower。
3）啟動 server2 的 zookeeper 服務，並查看狀態
此時，server2 成為了集群中的 follower。
此時，Zookeeper 集群的安裝及高可用性驗證已完成！
第三步：Kafka 集群搭建
1. 簡介
本文會安裝配置一個具有兩個 Broker 組成的 Kafka 集群，並在其上創建一個具有兩個分區的Topic。
2. 安裝
# tar zxvf kafka_2.12-0.10.2.0.tgz # mv kafka_2.12-0.10.2.0 kafka
3. 配置
1）配置文件位置
路徑：kafka/config/server.properties
2）默認配置
# 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 # Switch to enable topic deletion or not, default value is false #delete.topic.enable=true ############################# 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 handling network requests num.network.threads=3 # The number of threads doing 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 ############################# 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 as long as the remaining # segments don't 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
3）更改配置
############################# Server Basics ############################# # The id of the broker. This must be set to a unique integer for each broker. broker.id=0 # Switch to enable topic deletion or not, default value is false #delete.topic.enable=true ############################# 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 port=9092 host.name=192.168.6.128 advertised.host.name=192.168.6.128 advertised.port=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 docume ntation for more details #listener.security.protocol.map=PLAINTEXT:PLAINTEXT,SSL:SSL,SASL_PLAINTEXT:SASL_PLAINTEXT,SASL_SSL:SASL_SS L # The number of threads handling network requests num.network.threads=3 # The number of threads doing 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=/root/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 ############################# 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 le ad 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 as long as the remaining # segments don't 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=192.168.6.128:2181,192.168.6.129:2181,192.168.6.130:2181 # Timeout in ms for connecting to zookeeper zookeeper.connection.timeout.ms=6000
配置的詳細說明請參考官方文檔：http://kafka.apache.org/documentation.html#brokerconfigs
注意：按照官方文檔的說法，advertised.host.name 和 advertised.port 這兩個參數用於定義集群向 Producer 和 Consumer 廣播的節點 host 和 port，如果不定義，會默認使用 host.name 和 port 的定義。但在實際應用中，發現如果不定義 advertised.host.name 參數，使用 Java 客戶端從遠端連接集群時，會發生連接超時，拋出異常：org.apache.kafka.common.errors.TimeoutException: Batch Expired
經過過 debug 發現，連接到集群是成功的，但連接到集群后更新回來的集群 meta 信息卻是錯誤的。metadata 中的 Cluster 信息中節點的 hostname 是一串字符，而不是實際的ip地址。這串其實是遠端主機的 hostname，這說明在沒有配置 advertised.host.name 的情況下，Kafka 並沒有像官方文檔宣稱的那樣改為廣播我們配置的 host.name，而是廣播了主機配置的 hostname 。遠端的客戶端並沒有配置 hosts，所以自然是連接不上這個 hostname 的。要解決這一問題，把 host.name 和 advertised.host.name 都配置成絕對的 ip 地址就可以了。
4. 在另一台主機上安裝 kafka，並做配置
5. 在兩台主機上分別啟動 Kafka 服務
# bin/kafka-server-start.sh -daemon config/server.properties
官方給出的啟動方法是：bin/kafka-server-start.sh config/server.properties &
6. 創建分區和 topic
1）創建一個名為 ruready，擁有兩個分區，兩個副本的Topic
# bin/kafka-topics.sh --create --zookeeper 192.168.6.128:2181,192.168.6.129:2181,192.168.6.130:2181 --replication-factor 2 --partitions 2 --topic ruready
返回信息：
2）查看 Topic 狀態
# bin/kafka-topics.sh --describe --zookeeper 192.168.6.128:2181,192.168.6.129:2181,192.168.6.130:2181 --topic ruready
返回信息：
