Kafka集群安装

一、为啥用Kafka二、Zookeeper与Kafka以及SpringBoot的版本对应

2.1、JDK8支持的Kafka版本2.2、Kafka与SpringBoot的版本对应 三、Zookeeper集群搭建

3.1、软件环境3.2、配置&安装Zookeeper3.3启动并查看zookeeper 四、安装Kafka集群

打开kafka的官网，找到对应版本的kafka，查看文档中各版本对jdk8(java8)的支持(下面地址是2.6的版本，注意选自己需要的版本)
文档地址：https://kafka.apache.org/26/documentation.html

本次集群我是用的版本是kafka_2.13-2.5.0，这个版本支持jdk1.8
使用的Zookeeper是kafka_2.13-2.5.0.

这里需要强调的是，先看自己电脑安装的java版本，然后去查能对应安装的kafka和Zookeeper的最高版本是什么，然后再对应Zookeeper能对应的kafka本本。

Kafka集群是把状态保存在Zookeeper中的，首先要搭建Zookeeper集群。

（3台服务器-我的测试）
192.168.1.221 server1
192.168.1.110 server2
192.168.1.31 server3
1、服务器一台、三台、五台、（2*n+1），Zookeeper集群的工作是超过半数才能对外提供服务，3台中超过两台超过半数，允许1台挂掉 ，是否可以用偶数，其实没必要。
如果有四台那么挂掉一台还剩下三台服务器，如果在挂掉一个就不行了，这里记住是超过半数。
2、Java jdk1.8 zookeeper是用java写的所以他的需要JAVA环境，java是运行在java虚拟机上的
3、Zookeeper的稳定版本Zookeeper 3.4.6版本

解压Zookeeper压缩包配置系统环境变量（系统变量中新增ZOOKEEPER_HOME变量，指向Zookeeper所在根目录
- 系统变量path中添加“%ZOOKEEPER_HOME%bin”修改配置文件

# 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=E:\MOM\apache-zookeeper-3.7.0-bin\zkdata
# 事物日志的存储路径，如果不配置这个那么事物日志会默认存储到dataDir制定的目录，这样会严重影响zk的性能，当zk吞吐量较大的时候，产生的事物日志、快照日志太多
dataLogDir=E:\MOM\apache-zookeeper-3.7.0-bin\zkdatalog
# the port at which the clients will connect
clientPort=2181
server.1=192.168.1.221:2888:3888
server.2=192.168.1.110:2888:3888
server.3=192.168.1.31:2888:3888
#server.1 这个1是服务器的标识也可以是其他的数字， 表示这个是第几号服务器，用来标识服务器，这个标识要写到快照目录下面myid文件里
#192.168.1.221为集群里的IP地址，第一个端口是master和slave之间的通信端口，默认是2888，第二个端口是leader选举的端口，集群刚启动的时候选举或者leader挂掉之后进行新的选举的端口默认是3888
#myid文件没有后缀，dataDir目录下直接创建名字myid，内容分别为server后的数字1、 2 、 3
# 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

## Metrics Providers
#
# https://prometheus.io Metrics Exporter
#metricsProvider.className=org.apache.zookeeper.metrics.prometheus.PrometheusMetricsProvider
#metricsProvider.httpPort=7000
#metricsProvider.exportJvmInfo=true

配置文件解释

#tickTime：
这个时间是作为 Zookeeper 服务器之间或客户端与服务器之间维持心跳的时间间隔，也就是每个 tickTime 时间就会发送一个心跳。
#initLimit：
这个配置项是用来配置 Zookeeper 接受客户端（这里所说的客户端不是用户连接 Zookeeper 服务器的客户端，而是 Zookeeper 服务器集群中连接到 Leader 的 Follower 服务器）初始化连接时最长能忍受多少个心跳时间间隔数。当已经超过 5个心跳的时间（也就是 tickTime）长度后 Zookeeper 服务器还没有收到客户端的返回信息，那么表明这个客户端连接失败。总的时间长度就是 5*2000=10 秒
#syncLimit：
这个配置项标识 Leader 与Follower 之间发送消息，请求和应答时间长度，最长不能超过多少个 tickTime 的时间长度，总的时间长度就是5*2000=10秒
#dataDir：
快照日志的存储路径
#dataLogDir：
事物日志的存储路径，如果不配置这个那么事物日志会默认存储到dataDir制定的目录，这样会严重影响zk的性能，当zk吞吐量较大的时候，产生的事物日志、快照日志太多
#clientPort：
这个端口就是客户端连接 Zookeeper 服务器的端口，Zookeeper 会监听这个端口，接受客户端的访问请求。修改他的端口改大点

创建myid文件
在配置文件中指定的快照日志的存储路径(dataDir=E:\MOM\apache-zookeeper-3.7.0-bin\zkdata)文件夹中创建myid文件，创建文本文件，修改名字为myid，去掉后缀，server.1 服务器内容就写1然后保存，也就是说要把配置文件中server.后面指定的标识写入myid文件。注意每个服务器根据自己ip对应的标识写入这里还要强调一点，myid保存是最好不要修改文档编码格式，我改成utf-8后启动zookeeper后报错，改成默认就好了。

重要配置说明

myid文件和server.myid 在快照目录下存放的标识本台服务器的文件，他是整个zk集群用来发现彼此的一个重要标识。zoo.cfg 文件是zookeeper配置文件 在conf目录里。

此处引用一个转载说明：
ZooKeeper server will not remove old snapshots and log files when using the default configuration (see autopurge below), this is the responsibility of the operator
zookeeper不会主动的清除旧的快照和日志文件，这个是操作者的责任。
但是可以通过命令去定期的清理。

#!/bin/bash 
 
#snapshot file dir 
dataDir=/opt/zookeeper/zkdata/version-2
#tran log dir 
dataLogDir=/opt/zookeeper/zkdatalog/version-2

#Leave 66 files 
count=66 
count=$[$count+1] 
ls -t $dataLogDir/log.* | tail -n +$count | xargs rm -f 
ls -t $dataDir/snapshot.* | tail -n +$count | xargs rm -f 

#以上这个脚本定义了删除对应两个目录中的文件，保留最新的66个文件，可以将他写到crontab中，设置为每天凌晨2点执行一次就可以了。


#zk log dir   del the zookeeper log
#logDir=
#ls -t $logDir/zookeeper.log.* | tail -n +$count | xargs rm -f

其他方法：

第二种：使用ZK的工具类PurgeTxnLog，它的实现了一种简单的历史文件清理策略，可以在这里看一下他的使用方法 http://zookeeper.apache.org/doc/r3.4.6/zookeeperAdmin.html

第三种：对于上面这个执行，ZK自己已经写好了脚本，在bin/zkCleanup.sh中，所以直接使用这个脚本也是可以执行清理工作的。

第四种：从3.4.0开始，zookeeper提供了自动清理snapshot和事务日志的功能，通过配置 autopurge.snapRetainCount 和 autopurge.purgeInterval 这两个参数能够实现定时清理了。这两个参数都是在zoo.cfg中配置的：
autopurge.purgeInterval 这个参数指定了清理频率，单位是小时，需要填写一个1或更大的整数，默认是0，表示不开启自己清理功能。
autopurge.snapRetainCount 这个参数和上面的参数搭配使用，这个参数指定了需要保留的文件数目。默认是保留3个。

推荐使用第一种方法，对于运维人员来说，将日志清理工作独立出来，便于统一管理也更可控。毕竟zk自带的一些工具并不怎么给力。

在控制台输入:zkServer启动zookeeper
zk集群一般只有一个leader，多个follower，主一般是相应客户端的读写请求，而从主同步数据，当主挂掉之后就会从follower里投票选举一个leader出来。

可以用“jps”查看zk的进程，这个是zk的整个工程的main

主要是将kafka加压到目录，然后再配置文件中最好配置就可以启动了，

config/server.properties 配置文件

# 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.
# 当前机器在集群中的唯一标识，和zookeeper的myid性质一样
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://192.168.1.221:9092

# 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
# 这个是borker进行网络处理的线程数
num.network.threads=3

# The number of threads that the server uses for processing requests, which may include disk I/O
# 这个是borker进行I/O处理的线程数
num.io.threads=8

# 发送缓冲区buffer大小，数据不是一下子就发送的，先回存储到缓冲区了到达一定的大小后在发送，能提高性能
# The send buffer (SO_SNDBUF) used by the socket server
socket.send.buffer.bytes=102400

# kafka接收缓冲区大小，当数据到达一定大小后在序列化到磁盘
# The receive buffer (SO_RCVBUF) used by the socket server
socket.receive.buffer.bytes=102400

# 这个参数是向kafka请求消息或者向kafka发送消息的请请求的最大数，这个值不能超过java的堆栈大小
# The maximum size of a request that the socket server will accept (protection against OOM)
socket.request.max.bytes=104857600


############################# Log Basics #############################
# 消息存放的目录，这个目录可以配置为“，”逗号分割的表达式，上面的num.io.threads要大于这个目录的个数这个目录
# 如果配置多个目录，新创建的topic他把消息持久化的地方是，当前以逗号分割的目录中，那个分区数最少就放那一个
# A comma separated list of directories under which to store log files
log.dirs=D:\mom\kafka_2.13-2.5.0\kafka-data
# 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.
# 默认的分区数，一个topic默认1个分区数
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 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 excessive 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.
# 默认消息的最大持久化时间，168小时，7天
# The minimum age of a log file to be eligible for deletion due to age
log.retention.hours=168
# 消息保存的最大值5M
message.max.byte=5242880
# kafka保存消息的副本数，如果一个副本失效了，另一个还可以继续提供服务
default.replication.factor=2
# 取消息的最大直接数
replica.fetch.max.bytes=5242880
# 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
# 这个参数是：因为kafka的消息是以追加的形式落地到文件，当超过这个值的时候，kafka会新起一个文件
# The maximum size of a log segment file. When this size is reached a new log segment will be created.
log.segment.bytes=1073741824
# 每隔300000毫秒去检查上面配置的log失效时间（log.retention.hours=168 ），到目录查看是否有过期的消息如果有，删除
# 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=192.168.1.221:2181,192.168.1.110:2181,192.168.1.31:2181

# Timeout in ms for connecting to zookeeper
zookeeper.connection.timeout.ms=18000


############################# 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

这里说明一下，主要修改四个指标：

broker.id=0 # 当前机器在集群中的唯一标识，和zookeeper的myid性质一样三台机器要设置不同的broker.id

listeners=PLAINTEXT://:9092
# 每台服务器要根据自己的实际ip进行修改
advertised.listeners=PLAINTEXT://192.168.1.221:9092
# 消息存放的目录，这个目录可以配置为“，”逗号分割的表达式，上面的num.io.threads要大于这个目录的个数这个目录
# 如果配置多个目录，新创建的topic他把消息持久化的地方是，当前以逗号分割的目录中，那个分区数最少就放那一个
log.dirs=D:\mom\kafka_2.13-2.5.0\kafka-data

# 需要将zookeeper服务器地址及端口全部配置上
zookeeper.connect=192.168.1.221:2181,192.168.1.110:2181,192.168.1.31:2181

此时启动kafka就可以了，注意需要先启动zookeeper