最近在使用Spring Cloud进行分布式微服务搭建，顺便对集成KafKa的方案做了一些总结，今天详细介绍一下KafKa集群安装过程：
1. 在根目录创建kafka文件夹（service1、service2、service3都创建）
[root@localhost /]# mkdir kafka
2.通过Xshell上传文件到service1服务器：上传kafka_2.9.2-0.8.1.1.tgz到/software文件夹
3.远程copy将service1下的/software/kafka_2.9.2-0.8.1.1.tgz到service2、service3
[root@localhost software]# scp -r /software/kafka_2.9.2-0.8.1.1.tgz root@192.168.2.212:/software/
[root@localhost software]# scp -r /software/kafka_2.9.2-0.8.1.1.tgz root@192.168.2.213:/software/
3.copy /software/kafka_2.9.2-0.8.1.1.tgz到/kafka/目录（service1、service2、service3都执行）
[root@localhost software]# cp /software/kafka_2.9.2-0.8.1.1.tgz /kafka/
4.安装解压kafka_2.9.2-0.8.1.1.tgz（service1、service2、service3都执行）
[root@localhost /]# cd /kafka/
[root@localhost kafka]# tar -zxvf kafka_2.9.2-0.8.1.1.tgz
5.创建kafka消息目录（service1,service2,service3都要创建）
[root@localhost kafka]# mkdir kafkaLogs
6. 修改kafka的配置文件（service1,service2,service3都要配置）
[root@localhost /]# cd /kafka/kafka_2.9.2-0.8.1.1/
[root@localhost kafka_2.9.2-0.8.1.1]# cd config/
[root@localhost config]# ls
consumer.properties log4j.properties producer.properties server.properties test-log4j.properties tools-log4j.properties zookeeper.properties
[root@localhost config]# vi 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 ---唯一标识
############################# Socket Server Settings #############################
# The port the socket server listens on
port=19092 --当前broker对外提供的TCP端口,默认9092
# Hostname the broker will bind to. If not set, the server will bind to all interfaces
host.name=192.168.2.213 --一般是关闭状态，我们要将它打开，如果dns解析失败，会出现文件句柄泄露，不要小看dns解析失败率，如果dns解析失败率为万分之一，由于kafka的性能非常高，每个topic的每个分区，每秒可以处理十万多条的数据，即使万分之一的失败率，每秒也要泄露10个文件句柄，很快句柄数就会泄露完毕，就会超过linux打开文件的数，就会出现异常，所以我们配置ip，就不会进行dns解析
# 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 --broker网络处理的线程数，一般不做处理
# The number of threads doing disk I/O
num.io.threads=8 --broker io处理的线程数，这个数量一定要比log.dirs的目录数要大
# The send buffer (SO_SNDBUF) used by the socket server
socket.send.buffer.bytes=1048576 --将发送的消息先放到缓冲区，当到达一定量的时候再一次性发出
# The receive buffer (SO_RCVBUF) used by the socket server
socket.receive.buffer.bytes=1048576 --kafka接受消息的缓冲区，当接受的数量达到一定量的时候再写入磁盘
# The maximum size of a request that the socket server will accept (protection against OOM)
socket.request.max.bytes=104857600 --像kafka发送或者请求消息的最大数，此设置不能超过java堆栈大小
############################# Log Basics #############################
# A comma seperated list of directories under which to store log files
log.dirs=/kafka/kafkaLogs --多个目录可以用，隔开
# 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 --一个topic默认分区数
############################# 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=5048576 --kafka每条消息容纳的最大大小
default.replication.factor=2 --默认的复制因子，默认消息只有一个副本，不太安全，所以设置为2，如果某个分区的消息失败了，我们可以使用另一个分区的消息服务
replica.fetch.max.byte=5048576 --kafka每条消息容纳的最大大小
# 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 --消息持久化的最大大小
# 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 --不使用log压缩
############################# 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=192.168.2.211:2181,192.168.2.212:2181,192.168.2.213:2181 --zk地址
# Timeout in ms for connecting to zookeeper
zookeeper.connection.timeout.ms=1000000
7.启动kafka服务
[root@localhost bin]# ./kafka-server-start.sh -daemon ../config/server.properties
[root@localhost bin]# jps
27413 Kafka
27450 Jps
17884 QuorumPeerMain
8.验证kafka集群
[root@localhost bin]# ./kafka-topics.sh --create --zookeeper localhost:2181 --replication-factor 2 --partitions 1 --topic test
Created topic "test".
9.在service1上开启producer程序
./kafka-console-producer.sh --broker-list 192.168.2.211:9092 --topic test
[root@localhost bin]# ./kafka-console-producer.sh --broker-list 192.168.2.211:9092 --topic test
SLF4J: Failed to load class "org.slf4j.impl.StaticLoggerBinder".
SLF4J: Defaulting to no-operation (NOP) logger implementation
SLF4J: See http://www.slf4j.org/codes.html#StaticLoggerBinder for further details.
10. 在service2上开启consumer程序
[root@localhost bin]# ./kafka-console-consumer.sh --zookeeper localhost:2181 --topic test --from-beginning
SLF4J: Failed to load class "org.slf4j.impl.StaticLoggerBinder".
SLF4J: Defaulting to no-operation (NOP) logger implementation
SLF4J: See http://www.slf4j.org/codes.html#StaticLoggerBinder for further details.
11.在producer中发送消息：hello honghu
[root@localhost bin]# ./kafka-console-consumer.sh --zookeeper localhost:2181 --topic test --from-beginning
SLF4J: Failed to load class "org.slf4j.impl.StaticLoggerBinder".
SLF4J: Defaulting to no-operation (NOP) logger implementation
SLF4J: See http://www.slf4j.org/codes.html#StaticLoggerBinder for further details.
hello honghu
12. 在consumer中接受到消息
[root@localhost bin]# ./kafka-console-consumer.sh --zookeeper localhost:2181 --topic test --from-beginning
SLF4J: Failed to load class "org.slf4j.impl.StaticLoggerBinder".
SLF4J: Defaulting to no-operation (NOP) logger implementation
SLF4J: See http://www.slf4j.org/codes.html#StaticLoggerBinder for further details.
hello honghu 源码来源