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）