apache.zookeeper-3.4与apache.kafka-2.11的安装
zookeeper与Kafka集群安装
集群安装以三台机器（虚拟机，物理机等等）为例子：
192.168.200.100 kafka01 （主节点）
192.168.200.101 kafka02 （从节点）
192.168.200.102 kafka03 （从节点）一、进入集群kafka01（主节点）节点配置hosts文件:
vim /etc/hosts #打开hosts为每个IP配置别名，相当于java中配置变量，以后只需别名
192.168.200.100 kafka01
192.168.200.101 kafka02
192.168.200.102 kafka03在kafka01执行一下操作，将其分发到不同的主机上
scp -r /etc/hosts root@kafka02:/etc/hosts
scp -r /etc/hosts root@kafka03:/etc/hosts二、将三台主机配置免密
ssh-keygen -t rsa #三台机器都执行该命令，然后一直回车至结束。
登陆kafka01将密匙传输其他机器（包括本机）：
ssh-copy-id kafka01
ssh-copy-id kafka02
ssh-copy-id kafka03登陆kafka02将密匙传输其他机器（包括本机）：
ssh-copy-id kafka01
ssh-copy-id kafka02
ssh-copy-id kafka03登陆kafka03将密匙传输其他机器（包括本机）：
ssh-copy-id kafka01
ssh-copy-id kafka02
ssh-copy-id kafka03注：下面的配置中使用的都为IP，生产环境中尽力使用别名代替，这样如果IP发生变化只需要修改hosts就可以了。
安装JDK（可以使用rpm包或者tar.gz包）:
如果使用jdk.rpm包使用，不需要配置环境变量（会安装在/usr/bin 目录下）：
rpm -ivh jdk.rpm #完成后使用 java 进行测试
jdk.tar.gz 包需要配置环境变量：
先解压包：
jar -zxvf xxx.tar.gz
执行vi /etc/profile 修改环境变量，新增以下代码：
export JAVA_HOME=/usr/local/java/jdk1.8.0_181
export JRE_HOME=$JAVA_HOME/jre
export CLASSPATH=.:$JAVA_HOME/jre/lib/rt.jar:$JAVA_HOME/lib/dt.jar:$JAVA_HOME/lib/tools.jar
export PATH=$PATH:$JAVA_HOME/bin:$JRE_HOME/bin
刷新环境变量：source /etc/profile
安装zk:
将zookeeper解压到目录：tar -zxvf zookeeper-3.4.13.tar.gz -C /usr/local
进入/usr/local目录下修改zookeeper名称：mv zookeeper-3.4.13/ zookeeper
在zookeeper安装目录下新建保存数据的目录：mkdir -p zookeeper/data
在zookeeper安装目录下新建日志目录：mkdir -p zookeeper/dataLog
配置环境变量：vim /etc/profile
添加配置如下：
export ZK_HOME=/usr/local/zookeeper
export PATH=$PATH:$ZK_HOME/bin
刷新环境变量：source /etc/profile节点配置：
(1)kafka01(192.168.200.100)
进入配置目录：zookeeper/conf，复制一个zoo.cfg文件：
cp -f zoo_sample.cfg zoo.cfg
配置如下：
dataDir=/usr/local/zookeeper/data #就是刚刚创建的两个目录
dataLogDir=/usr/local/zookeeper/dataLog
#在本节点时就使用0.0.0.0
server.1=0.0.0.0:2888:3888
server.2=192.168.200.101:2888:3888
server.3=192.168.200.102:2888:3888
进入data目录：cd /usr/local/zookeepe/data
生成myid文件（用于选举leader）：echo "1" >myid(2) kafka02(192.168.200.101)
进入配置目录：zookeeper/conf，复制一个zoo.cfg文件：
cp -f zoo_sample.cfg zoo.cfg
配置如下：
dataDir=/usr/local/zookeeper/data
dataLogDir=/usr/local/zookeeper/dataLog
server.1=192.168.200.100:2888:3888
server.2=0.0.0.0:2888:3888
server.3=192.168.200.102:2888:3888
进入data目录：cd /usr/local/zookeeper/ data
生成myid文件（每个节点下的myid都是唯一的）：echo "2" >myid(3) kafka03(192.168.200.102)
进入配置目录：zookeeper/conf，复制一个zoo.cfg文件：
cp -f zoo_sample.cfg zoo.cfg
配置如下：
dataDir=/usr/local/zookeeper/data
dataLogDir=/usr/local/zookeeper/dataLog
server.1=192.168.200.100:2888:3888
server.2=192.168.200.101:2888:3888
server.3=0.0.0.0:2888:3888
进入data目录：cd /usr/local/zookeeper/data
生成myid文件：echo "3" >myid以上步骤完成，全部zookeeper节点配置完成，执行以下命令启动集群：
zkServer.sh start可以通过zkServer.sh status命令查看集群状态，zkServer.sh stop命令可以停止集群。
或者通过nestat -lnp | grep 2181 查看该进程是否存在（因为zookeeper的端口配置为2181，该命令是指查询占用端口2181的进程）
或使用jps命令查看（使用自带的open java的无法使用该功能）配置Kafka:
下载并解压kafka压缩包：
配置vi kafka/config/server.properties如下：
# 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=1 #每个节点id不能相同
############################# Socket Server Settings #############################
# The port the socket server listens on
#kafka开启服务的端口号
port=9092
# Hostname the broker will bind to. If not set, the server will bind to all interfaces
#改配置使用本节点IP，不能使用别名否则java无法访问kafka，亲测- - 。
host.name=192.168.200.100
# 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=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
#日志文件的保存路径
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.
#主题下分区的备份数，按需求设置
num.partitions=2
# 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.
#消息的备份数
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
#segment的日志保存最大时间，超过将被删除
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.
#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
# 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
export HBASE_MANAGES_ZK=false
offsets.storage=kafka
dual.commit.enabled=true
delete.topic.enable=true
############################# 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.
#之前zookeeper配置的节点，可以使用别名，亲测
zookeeper.connect=192.168.200.100:2181,192.168.200.101:2181,192.168.200.102:2181
# Timeout in ms for connecting to zookeeper
#kafka连接zookeeper的超时间
zookeeper.connection.timeout.ms=6000
以下命令全部在kafka安装目录执行开启kafka集群：
启动kafka不产生日志并且后台运行：
&：指命令运行完后，按下回车，可以继续执行别的命令，该命令会在后台执行，但是关闭该会话窗口，会导致命令终止。如果想要命令继续执行可以使用nohup命令，会一直执行。
nohup bin/kafka-server-start.sh config/server.properties 1>/dev/null 2>&1 &
如果想要看开启kafka时的日志，请去掉 1>/dev/null 2>&1 该命令是将日志指向黑洞（类似windows的回收站，区别在于你无法恢复文件）
bin/kafka-server-start.sh config/server.properties &
输入JPS产看状态：（Jps命令自带的OPenJDK不能使用）
Jps 可以使用 netstat -lnp | grep 9092 查看
创建topic：zookeeper后面的参数就是zookeeper配置时的配置，2181为默认端口
replication-factor：设置主题的备份数量（分区的备份数量在配置文件中设置）
partitions:指定分区数数量。
kafka-topics.sh --create --zookeeper master:2181,slave1:2181,slave2:2181 --replication-factor 1 --partitions 1 --topic book
查看所有topic列表
bin/kafka-topics.sh --zookeeper master:2181,slave1:2181,slave2:2181 --list
查看指定topic信息
bin/kafka-topics.sh --zookeeper master:2181,slave1:2181,slave2:2181 --describe --topic book
控制台向topic生产数据
bin/kafka-console-producer.sh --broker-list master:9092 --topic book
控制台消费topic的数据：
--from-beginning:指定从头消费数据。
bin/kafka-console-consumer.sh --zookeeper master:2181 --topic book --from-beginning
停止kafka：
bin/kafka-server-stop.sh
输入命令：netstat -lnp | grep 9092或jps
查看是否关闭，如果没用使用 kill -9 pid（就是查询出的pid号）
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