Kafka基于Zookeeper管理分布式节点，Zookeeper是基于Java开发，所以，安装Kafka就必须安装JDK和Zookeeper。
一、安装JDK
1、新建一个存放jdk的目录，并解压jdk到该目录下；
如下图所示，jdk存放目录为/home/coshaho/jdk，版本为jdk1.7.0_79。
2、编辑用户环境变量文件~/.bashrc，添加jdk环境变量；
3、执行source ~/.bashrc加载环境变量。
二、安装Zookeeper
1、 新建Zookeeper存放目录，并解压Zookeeper到该目录；
2、在Zookeeper目录下新建zkdata文件夹以及zkdatalog文件夹；
3、进入/home/coshaho/zookeeper/zookeeper-3.4.6/conf目录配置zoo.cfg文件；
(1) dataDir为zk快照日志存储路径；
(2) dataLogDir为zk事务日志，这个目录不配置的话，事务日志会打印到dataDir中，影响性能；
(3) clientPort为zk端口；
(4) server.数字配置节点ip端口信息,第一个端口为master，slaver通信端口，第二个端口为leader选举端口。
4、进入zk快照文件目录创建节点标识；
这里myid文件中的内容和zoo.cfg中的节点标识数字一致。
5、启动zookeeper。
三、安装Kafka
1、新建Kafka存放目录，并解压Kafka到该目录下；
2、在Kafka目录下新建kafkalogs文件夹，用于存放kafka消息；
3、进入/home/coshaho/kafka/kafka_2.9.2-0.8.1.1/config目录编辑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 port the socket server listens on port=19092 # Hostname the broker will bind to. If not set, the server will bind to all interfaces host.name=127.0.1.1 # Hostname the broker will advertise to producers and consumers. If not set, it uses the # value for "host.name" if configured. Otherwise, it will use the value returned from # java.net.InetAddress.getCanonicalHostName(). #advertised.host.name=<hostname routable by clients> # The port to publish to ZooKeeper for clients to use. If this is not set, # it will publish the same port that the broker binds to. #advertised.port=<port accessible by clients> # The number of threads handling network requests num.network.threads=2 # 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=1048576 # The receive buffer (SO_RCVBUF) used by the socket server socket.receive.buffer.bytes=1048576 # 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=/home/coshaho/kafka/kafkalogs # 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=2 ############################# 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 log.retention.hours=168 message.max.byte=5048526 default.replication.factor=2 replica.fetch.max.bytes=5048526 # 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. #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=536870912 # 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=60000 # By default the log cleaner is disabled and the log retention policy will default to just delete segments after their retention expires. # If log.cleaner.enable=true is set the cleaner will be enabled and individual logs can then be marked for log compaction. log.cleaner.enable=false ############################# 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=127.0.1.1:12181 # Timeout in ms for connecting to zookeeper zookeeper.connection.timeout.ms=1000000
4、启动kafka。
四、验证Kafka集群。
1、创建topic；
coshaho@coshaho-virtual-machine:~/kafka/kafka_2.9.2-0.8.1.1$ bin/kafka-topics.sh --create --zookeeper localhost:12181 --replication-factor 1 --partitions 1 --topic hkx Created topic "hkx".
2、创建consumer例子；
coshaho@coshaho-virtual-machine:~/kafka/kafka_2.9.2-0.8.1.1$ bin/kafka-console-consumer.sh --zookeeper 127.0.1.1:12181 --from-beginning --topic hkx
3、创建producer例子；
coshaho@coshaho-virtual-machine:~/kafka/kafka_2.9.2-0.8.1.1$ bin/kafka-console-producer.sh --broker-list 127.0.1.1:19092 --topic hkx
4、producer发送消息，consumer接收消息。
来源：https://www.cnblogs.com/coshaho/p/5906384.html