Tags： kafka

Centos7.5安装kafka集群

• Centos7.5安装kafka集群
  • • 主机环境
    • 软件环境
    • 主机规划
    • 主机安装前准备
    • 安装jdk1.8
    • 安装zookeeper
    • 安装kafka
    • kafka基本操作
      • kafka基本操作
    • 安装管理监控工具Kafka-Manager

主机环境

基本配置：

节点数	3
操作系统	CentOS Linux release 7.5.1804 (Core)
内存	8GB

流程配置：

节点数	3
操作系统	CentOS Linux release 7.5.1804 (Core)
内存	16GB

注： 实际生产中按照需求分配内存，如果只是在vmvare中搭建虚拟机，内存可以调整为每台主机1-2GB即可

软件环境

软件	版本	下载地址
jdk	jdk-8u172-linux-x64	点击下载
zookeeeper	zookeeper-3.4.5-cdh5.14.2	点击下载
kafka	kafka_2.12-1.1.0	点击下载
kafka-manager	kafka-manager-1.3.3.17	源码下载

注： kafka-manager官方只提供源码下载，下载后编译：sbt clean dist，此编译需要x翻XX墙x才能完成，没有条件的话可以下载网友编译好的低一点的版本：kafka-manager-1.3.3.4

主机规划

3个节点角色规划如下：

主机名	CDHNode1	CDHNode2	CDHNode3
IP	192.168.223.201	192.168.223.202	192.168.223.203
zookeeper	yes	yes	yes
kafka	yes	yes	yes

注： ZooKeeper保持奇数个，如果需要高可用则不少于 3 个节点。具体原因，以后详叙。

主机安装前准备

1. 关闭所有节点的 SELinux

sed -i 's/^SELINUX=.*$/SELINUX=disabled/g' /etc/selinux/config

setenforce 0

1. 关闭所有节点防火墙 firewalld or iptables

systemctl disable firewalld;

systemctl stop firewalld;

systemctl disable iptables;

systemctl stop iptables;

1. 开启所有节点时间同步 ntpdate

echo "*/5 * * * * /usr/sbin/ntpdate asia.pool.ntp.org | logger -t NTP" >> /var/spool/cron/root

1. 设置所有节点语言编码以及时区

echo 'export TZ=Asia/Shanghai' >> /etc/profile

echo 'export LANG=en_US.UTF-8' >> /etc/profile

. /etc/profile

1. 所有节点添加kafka用户

useradd -m kafka

echo '123456' | passwd --stdin kafka

# 设置PS1

su - kafka

echo 'export PS1="\u@\h:\$PWD>"' >> ~/.bash_profile

echo "alias mv='mv -i'

alias rm='rm -i'" >> ~/.bash_profile

. ~/.bash_profile

1. 设置kafka用户之间免密登录 首先在CDHNode1主机生成秘钥

su - kafka

ssh-keygen -t rsa	# 一直回车即可生成kafka用户的公钥和私钥

cd .ssh

vi id_rsa.pub  # 去掉私钥末尾的主机名 kafka@CDHNode1

cat id_rsa.pub > authorized_keys

chmod 600 authorized_keys

压缩.ssh文件夹

su - kafka

zip -r ssh.zip .ssh

随后分发ssh.zip到CDHNode2-3主机kafka用户家目录解压即完成免密登录

1. 主机内核参数优化以及最大文件打开数、最大进程数等参数优化 不同主机优化参数有可能不一样，故这里不作出具体优化方法，但如果kafka环境用于正式生产，必须优化，linux默认参数可能会导致kafka集群性能低下。

注： 以上操作需要使用 root 用户，到目前为止操作系统环境已经准备完成，以下开始正式安装，后面的操作如果不做特殊说明均使用 kafka 用户

安装jdk1.8

所有节点都需要安装，安装方式都一样 解压 jdk-8u172-linux-x64.tar.gz

tar zxvf jdk-8u172-linux-x64.tar.gz

mkdir -p /home/kafka/app

mv jdk-8u172-linux-x64 /home/kafka/app/jdk

rm -f jdk-8u172-linux-x64.tar.gz

配置环境变量 vi ~/.bash_profile 添加以下内容：

#java

export JAVA_HOME=/home/kafka/app/jdk

export CLASSPATH=.:$JAVA_HOME/lib:$CLASSPATH

export PATH=$PATH:$JAVA_HOME/bin:$JAVA_HOME/jre/bin

加载环境变量

. ~/.bash_profile

查看是否安装成功 java -version

java version "1.8.0_172"

Java(TM) SE Runtime Environment (build 1.8.0_172-b11)

Java HotSpot(TM) 64-Bit Server VM (build 25.172-b11, mixed mode)

如果出现以上结果证明安装成功。

安装zookeeper

首先在CDHNode1上安装

解压 zookeeper-3.4.5-cdh5.14.2.tar.gz

tar zxvf zookeeper-3.4.5-cdh5.14.2.tar.gz

mv zookeeper-3.4.5-cdh5.14.2 /home/kafka/app/zookeeper

rm -f zookeeper-3.4.5-cdh5.14.2.tar.gz

设置环境变量 vi ~/.bash_profile 添加以下内容：

#zk

export ZOOKEEPER_HOME=/home/kafka/app/zookeeper

export PATH=$PATH:$ZOOKEEPER_HOME/bin

加载环境变量

. ~/.bash_profile

添加配置文件 vi /home/kafka/app/zookeeper/conf/zoo.cfg 添加以下内容：

# 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.

#数据文件目录与日志目录

dataDir=/home/kafka/data/zookeeper/zkdata

dataLogDir=/home/kafka/data/zookeeper/zkdatalog

# the port at which the clients will connect

clientPort=2181

#server.服务编号=主机名称：Zookeeper不同节点之间同步和通信的端口：选举端口（选举leader）

server.1=CDHNode1:2888:3888

server.2=CDHNode2:2888:3888

server.3=CDHNode3:2888:3888

# 节点变更时只需在此添加或者删除相应的节点（所有节点配置都需要修改），然后在启动新增或者停止删除的节点即可

# 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

创建所需目录

mkdir -p /home/kafka/data/zookeeper/zkdata

mkdir -p /home/kafka/data/zookeeper/zkdatalog

mkdir -p /home/kafka/app/zookeeper/logs

添加myid vim /home/kafka/data/zookeeper/zkdata/myid，添加：

1

注： 此数字来源于zoo.cfg中配置 server.1=CDHNode1:2888:3888行server后面的1，故CDHNode2填写2，CDHNode3填写3

配置日志目录 vim /home/kafka/app/zookeeper/libexec/zkEnv.sh ，修改以下参数为：

ZOO_LOG_DIR="$ZOOKEEPER_HOME/logs"

ZOO_LOG4J_PROP="INFO,ROLLINGFILE"

注： /home/kafka/app/zookeeper/libexec/zkEnv.sh 与 /home/kafka/app/zookeeper/bin/zkEnv.sh 文件内容相同。启动脚本 /home/kafka/app/zookeeper/bin/zkServer.sh 会优先读取/home/kafka/app/zookeeper/libexec/zkEnv.sh，当其不存在时才会读取 /home/kafka/app/zookeeper/bin/zkEnv.sh。

vim /home/kafka/app/zookeeper/conf/log4j.properties ，修改以下参数为：

zookeeper.root.logger=INFO, ROLLINGFILE

zookeeper.log.dir=/home/kafka/app/zookeeper/logs

log4j.appender.ROLLINGFILE=org.apache.log4j.RollingFileAppender

复制zookeeper到CDHNode2-3

scp ~/.bash_profile CDHNode2:/home/kafka

scp ~/.bash_profile CDHNode3:/home/kafka

scp -pr /home/kafka/app/zookeeper CDHNode2:/home/kafka/app

scp -pr /home/kafka/app/zookeeper CDHNode3:/home/kafka/app

ssh CDHNode2 "mkdir -p /home/kafka/data/zookeeper/zkdata;mkdir -p /home/kafka/data/zookeeper/zkdatalog;mkdir -p /home/kafka/app/zookeeper/logs"

ssh CDHNode2 "echo 2 > /home/kafka/data/zookeeper/zkdata/myid"

ssh CDHNode3 "mkdir -p /home/kafka/data/zookeeper/zkdata;mkdir -p /home/kafka/data/zookeeper/zkdatalog;mkdir -p /home/kafka/app/zookeeper/logs"

ssh CDHNode3 "echo 3 > /home/kafka/data/zookeeper/zkdata/myid"

启动zookeeper 3个节点均启动

/home/kafka/app/zookeeper/bin/zkServer.sh start

查看节点状态

/home/kafka/app/zookeeper/bin/zkServer.sh status

如果一个节点为leader，另2个节点为follower，则说明Zookeeper安装成功

查看进程

jps

其中 QuorumPeerMain 进程为zookeeper

停止zookeeper

/home/kafka/app/zookeeper/bin/zkServer.sh stop

安装kafka

首先在CDHNode1上安装

解压 kafka_2.12-1.1.0.tgz

tar zxvf kafka_2.12-1.1.0.tgz

mv kafka_2.12-1.1.0 /home/kafka/app/kafka

rm -f kafka_2.12-1.1.0.tgz

设置环境变量 vi ~/.bash_profile 添加以下内容：

#kafka

export KAFKA_HOME=/home/kafka/app/kafka

export PATH=$PATH:$KAFKA_HOME/bin

加载环境变量

. ~/.bash_profile

添加配置文件 vi /home/kafka/app/kafka/config/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

#当前机器在集群中的唯一标识，和zookeeper的myid性质一样，CDHNode1为0,CDHNode1为2,CDHNode3为2

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

port=9092

#当前kafka对外提供服务的端口默认是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://your.host.name: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

num.network.threads=3

#这个是borker进行网络处理的线程数

# The number of threads that the server uses for processing requests, which may include disk I/O

num.io.threads=8

#这个是borker进行I/O处理的线程数

# The send buffer (SO_SNDBUF) used by the socket server

socket.send.buffer.bytes=1024000

#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 receive buffer (SO_RCVBUF) used by the socket server

socket.receive.buffer.bytes=1024000

#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 maximum size of a request that the socket server will accept (protection against OOM)

socket.request.max.bytes=104857600

#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

############################# Log Basics #############################

# A comma separated list of directories under which to store log files

log.dirs=/home/kafka/data/kafka/kafka-logs

#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

# 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=3

#默认的分区数，一个topic默认1个分区数

# 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 for 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.

# The minimum age of a log file to be eligible for deletion due to age

log.retention.hours=168

#默认消息的最大持久化时间，168小时，7天

# 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

#日志数据存储的最大字节数,1GB

# log.retention.hours 与 log.retention.bytes无论哪个先达到都会触发

# The maximum size of a log segment file. When this size is reached a new log segment will be created.

log.segment.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 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

message.max.byte=5242880

#消息保存的最大值5M

default.replication.factor=3

#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,必须小于等于集群节点数

replica.fetch.max.bytes=5242880

#取消息的最大直接数

############################# 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=CDHNode1:2181,CDHNode2:2181,CDHNode3:2181

# Timeout in ms for connecting to zookeeper

zookeeper.connection.timeout.ms=10000

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

• 这里没有启用压缩，启用压缩后吞吐量应该会增加比较明显，具体开启方法以后研究

设置内存使用：vi /home/kafka/app/kafka/bin/kafka-server-start.sh

export KAFKA_HEAP_OPTS="-Xmx3G -Xms3G"

创建所需目录

mkdir -p /home/kafka/data/kafka/kafka-logs

复制kafka到CDHNode2-3

scp ~/.bash_profile CDHNode2:/home/kafka

scp ~/.bash_profile CDHNode3:/home/kafka

scp -pr /home/kafka/app/kafka CDHNode2:/home/kafka/app

scp -pr /home/kafka/app/kafka CDHNode3:/home/kafka/app

ssh CDHNode2 "mkdir -p /home/kafka/data/kafka/kafka-logs"

ssh CDHNode3 "mkdir -p /home/kafka/data/kafka/kafka-logs"

修改 /home/kafka/app/kafka/config/server.properties 中的 broker.id CDHNode2为：1 ，CDHNode3为：2

启动kafka 3个节点均启动

/home/kafka/app/kafka/bin/kafka-server-start.sh -daemon /home/kafka/app/kafka/config/server.properties

• -daemon 后台服务的方式启动
• 有时候启动时明明未绑定端口当时会提示：kafka.common.KafkaException: Socket server failed to bind to ...，导致kafka无法启动，原因大概是非正常退出，pid文件未删除，删除老的pid文件就可以正常启动了。

查看进程

jps

其中 Kafka 进程即为 kafka

停止kafka

/home/kafka/app/kafka/bin/kafka-server-stop.sh

kafka基本操作

kafka基本操作

创建toppic

/home/kafka/app/kafka/bin/kafka-topics.sh --zookeeper CDHNode1:2181,CDHNode2:2181,CDHNode3:2181 --create --topic test --replication-factor 3 --partitions 3

• --replication-factor 指定副本数，必须小于等于集群节点数，否则报错
• --partitions 指定分区数，如果设置3个分区，则最多3个消费者同时消费信息

查看toppic

/home/kafka/app/kafka/bin/kafka-topics.sh --zookeeper CDHNode1:2181,CDHNode2:2181,CDHNode3:2181 --describe --topic test

• Leader：负责处理消息的读和写，Leader是从所有节点中随机选择的
• Replicas：列出了所有的副本节点，不管节点是否在服务中。
• Isr：是正在服务中的节点

查看所有toppic

/home/kafka/app/kafka/bin/kafka-topics.sh --zookeeper CDHNode1:2181,CDHNode2:2181,CDHNode3:2181 --list

生成消息 使用kafka自带工具

/home/kafka/app/kafka/bin/kafka-console-producer.sh --broker-list CDHNode1:9092,CDHNode2:9092,CDHNode3:9092 --topic test

• 进入控制台输入消息然后回车就生成一条消息

消费消息 使用kafka自带工具 第一种方法：

/home/kafka/app/kafka/bin/kafka-console-consumer.sh --zookeeper CDHNode1:2181,CDHNode2:2181,CDHNode3:2181 --from-beginning --topic test

• 不会记录消费者offset，每次都是从头开始

第二种方法：

/home/kafka/app/kafka/bin/kafka-console-consumer.sh --zookeeper CDHNode1:2181,CDHNode2:2181,CDHNode3:2181 --group test_group  --topic test

• 指定消费者组，会记录消费者offset
• --zookeeper CDHNode1:2181,CDHNode2:2181,CDHNode3:2181 可以使用 --bootstrap-server CDHNode1:9092,CDHNode2:9092,CDHNode3:9092 代替，相应的查看消费者组时 --zookeeper 也需要使用 --bootstrap-server 代替

第三种方法：

/home/kafka/app/kafka/bin/kafka-console-consumer.sh --bootstrap-server CDHNode1:9092,CDHNode2:9092,CDHNode3:9092 --offset 0 --partition 0 --group test_group --topic test

• 默认消费会从最新开始，可以指定offset，指定offset后必须指定partition，offset 从 0开始，且指定offset只使用与新版的使用--bootstrap-server的消费者，使用zookeeper消费者不支持

注： kafka中数据的删除跟有没有消费者消费完全无关。数据的删除，只跟kafka broker的这两个配置有关：

log.retention.hours=720 #数据最多保存720小时

log.retention.bytes=10737418240 #数据最多10GB

查看所有消费者组

/home/kafka/app/kafka/bin/kafka-consumer-groups.sh --bootstrap-server CDHNode1:9092,CDHNode2:9092,CDHNode3:9092 --list

• 结果中的 KafkaManagerOffsetCache 为系统内置组

查看消费者组消费信息

/home/kafka/app/kafka/bin/kafka-consumer-groups.sh --zookeeper CDHNode1:2181,CDHNode2:2181,CDHNode3:2181 --group test_group --describe

• --zookeeper CDHNode1:2181,CDHNode2:2181,CDHNode3:2181 可以使用 --bootstrap-server CDHNode1:9092,CDHNode2:9092,CDHNode3:9092 代替，这里是使用 --zookeeper 还是 --bootstrap-server 由消费者组消费时的选择而定

查看topic偏移量最大（小）值

/home/kafka/app/kafka/bin/kafka-run-class.sh kafka.tools.GetOffsetShell --topic test --time -1 --broker-list CDHNode1:9092,CDHNode2:9092,CDHNode3:9092 --partitions 2

• time为-1时表示最大值，time为-2时表示最小值
• 结果 test:2:0 ，中间数字为分区编号，最后的数字为结果

删除toppic

/home/kafka/app/kafka/bin/kafka-topics.sh --zookeeper CDHNode1:2181,CDHNode2:2181,CDHNode3:2181 --delete --topic test

删除消费者组

1. 使用 --zookeeper 的消费者组：

$ $ZOOKEEPER_HOME/bin/zkCli.sh -server CDHNode1:2181,CDHNode2:2181,CDHNode3:2181

  rmr /consumers/test_group

1. 使用 --bootstrap-server的消费者组，使用命令：

$KAFKA_HOME/bin/kafka-consumer-groups.sh --bootstrap-server CDHNode1:9092,CDHNode2:9092,CDHNode3:9092 --delete --group test_group

• 删除即时生效，但在kafka-manager管理界面还是会显示，只有重启集群才消失，应该是kafka-manager本身的问题

topic 分区负载均衡 在创建一个topic时，kafka尽量将partition均分在所有的brokers上，并且将replicas也j均分在不同的broker上。

每个partitiion的所有replicas叫做"assigned replicas"，"assigned replicas"中的第一个replicas叫"preferred replica"，刚创建的topic一般"preferred replica"是leader。leader replica负责所有的读写。

但随着时间推移，broker可能会停机，会导致leader迁移，导致机群的负载不均衡。我们期望对topic的leader进行重新负载均衡，让partition选择"preferred replica"做为leader。

对所有Topics进行均衡操作

/home/kafka/app/kafka/bin/kafka-preferred-replica-election.sh --zookeeper CDHNode1:2181,CDHNode2:2181,CDHNode3:2181

对某个Topic进行操作，先创建分配json文件

{

 "partitions":

  [

    {"topic":"test","partition": 2}

  ]

}

or

{

 "partitions":

  [

    {"topic":"test","partition": 0},

    {"topic":"test","partition": 1},

    {"topic":"test","partition": 2}

  ]

}

执行

/home/kafka/app/kafka/bin/kafka-preferred-replica-election.sh --zookeeper CDHNode1:2181,CDHNode2:2181,CDHNode3:2181 --path-to-json-file topic.json

安装管理监控工具Kafka-Manager

CDHNode1上解压安装下载好的 kafka-manager-1.3.3.4.zip

unzip kafka-manager-1.3.3.4.zip

mv kafka-manager-1.3.3.4 /home/kafka/app/kafka-manager

mkdir -p /home/kafka/app/kafka-manager/logs

rm -f kafka-manager-1.3.3.4.zip

添加配置文件 vi /home/kafka/app/kafka-manager/conf/application.conf：

# Copyright 2015 Yahoo Inc. Licensed under the Apache License, Version 2.0

# See accompanying LICENSE file.

# This is the main configuration file for the application.

# ~~~~~

# Secret key

# ~~~~~

# The secret key is used to secure cryptographics functions.

# If you deploy your application to several instances be sure to use the same key!

play.crypto.secret="^<csmm5Fx4d=r2HEX8pelM3iBkFVv?k[mc;IZE<_Qoq8EkX_/7@Zt6dP05Pzea3U"

play.crypto.secret=${?APPLICATION_SECRET}

# The application languages

# ~~~~~

play.i18n.langs=["en"]

play.http.requestHandler = "play.http.DefaultHttpRequestHandler"

play.http.context = "/"

play.application.loader=loader.KafkaManagerLoader

kafka-manager.zkhosts="CDHNode1:2181,CDHNode2:2181,CDHNode3:2181"

kafka-manager.zkhosts=${?ZK_HOSTS}

pinned-dispatcher.type="PinnedDispatcher"

pinned-dispatcher.executor="thread-pool-executor"

application.features=["KMClusterManagerFeature","KMTopicManagerFeature","KMPreferredReplicaElectionFeature","KMReassignPartitionsFeature"]

akka {

  loggers = ["akka.event.slf4j.Slf4jLogger"]

  loglevel = "INFO"

}

# 开启http基本密码验证

basicAuthentication.enabled=true

basicAuthentication.username="admin"

basicAuthentication.password="password"

basicAuthentication.realm="Kafka-Manager"

kafka-manager.consumer.properties.file=${?CONSUMER_PROPERTIES_FILE}

启动（nohup）

nohup /home/kafka/app/kafka-manager/bin/kafka-manager -Dconfig.file=/home/kafka/app/kafka-manager/conf/application.conf -Dhttp.port=8080 > /home/kafka/app/kafka-manager/logs/server.log 2>&1 &

• -Dhttp.port=8080 指定端口，默认9000
• -Dconfig.file 指定配置文件

停止

kill pid

访问

http://CDHNode1:8080

点击【Cluster】>【Add Cluster】打开如下添加集群的配置界面： 自定义集群名称和zookeeper地址 版本没有1.1.0，选择最新的0.10.1.0即可

其他broker的配置可以根据自己需要进行配置，默认情况下，点击【保存】时，会提示几个默认值为1的配置错误，需要配置为>=2的值。保存成功后，点击【Go to cluster view.】打开当前的集群界面。

关于kafka-manager的其他功能和操作可以参考官网：https://github.com/yahoo/kafka-manager。

开启kafka-server JMX 开启后kafka-manager能够显示更多监控信息，开启方法 vi $KAFKA_HOME/bin/kafka_server_start.sh, 添加以下参数

if [ "x$KAFKA_HEAP_OPTS" = "x" ]; then

    export KAFKA_HEAP_OPTS="-Xmx1G -Xms1G"

    export JMX_PORT="9999"

fi

然后kafka-manager添加集群是勾选 Enable JMX Polling (Set JMX_PORT env variable before starting kafka server) 即可