window环境搭建zookeeper,kafka集群

本文是对在window环境下如何搭建zookeeper集群和kafka集群的研究，如果你正在查找相关此类资料，希望本文能对你有所帮助。

网上很多资料关于"kafka集群"几乎都是一个模样，写得东西很类似，而且很多细节没有注明，需要在不断的测试过程中推敲才能得到理想的结果。本篇文章力求能尽量说明每一个细节每一个步骤，达到只要认真看过本文者都能自己搭建一个基于window的kafka集群环境，当然这里仅代表学习心得，不具备任何商业用途的说明。

话不多说，实践才是硬道理。在进行搭建之前需要说明几点，为了能更好的了解本文的相关内容，推荐您先认真查阅kafka入门这篇文章，这能作为基础能让你更顺利看懂本篇文章。为了演示集群的效果，这里准备了一台虚拟机(window server 2008)，在虚拟机中搭建了单IP多节点的zookeeper集群（多IP节点的也是同理的），并且在本机（win 10）和虚拟机中都安装了kafka。简言之需要准备的东西如下：

1.三台zookeeper服务器，都安装在同一台虚拟机中。

2.本机win10，和虚拟机分别安装一台kafka服务器。

一：虚拟机和本机网络环境

1.将虚拟机的网络模式调整为桥接模式，将虚拟机的防火墙功能关闭；

2.将主机的防火墙也关闭。

3.互相ping，测试是否能正常连接.

1)查看主机或者虚拟机中的ip：

   在cmd中输入ipconfig，找到IP4地址。这就是机子的ip地址。

   主机win10:

   

   虚拟机winserver2008:

   

2）使用ping ip地址  测试网络是否连接

   在两台机子的cmd中相互输入ping一下对方的ip：

   主机win10：

   

  winserver2008:

   

二 虚拟机中搭建zookeeper集群

  相对来说，zookeeper集群的搭建是很容易的，只需要注意一下配置文件。

  首先准备三份zookeeper程序，这里命名为server1，server2，server3.三台zookeeper服务器不同点在于它们各自的配置文件：

  

  server1的zoo.cfg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=/tmp/zookeeper
dataDir=C:\\Users\\Administrator\\Desktop\\server1\\zookeeper-3.4.8\\zkdata
dataLogDir=C:\\Users\\Administrator\\Desktop\\server1\\zookeeper-3.4.8\\zkdatalog
# the port at which the clients will connect
clientPort=3181
# 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
server.1=192.168.0.102:4181:5181
server.2=192.168.0.102:4182:5182
server.3=192.168.0.102:4183:5183

server2的zoo.cfg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=/tmp/zookeeper
dataDir=C:\\Users\\Administrator\\Desktop\\server2\\zookeeper-3.4.8\\zkdata
dataLogDir=C:\\Users\\Administrator\\Desktop\\server2\\zookeeper-3.4.8\\zkdatalog
# the port at which the clients will connect
clientPort=3182
# 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
server.1=192.168.0.102:4181:5181
server.2=192.168.0.102:4182:5182
server.3=192.168.0.102:4183:5183

server3的zoo.cfg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=/tmp/zookeeper
dataDir=C:\\Users\\Administrator\\Desktop\\server3\\zookeeper-3.4.8\\zkdata
dataLogDir=C:\\Users\\Administrator\\Desktop\\server3\\zookeeper-3.4.8\\zkdatalog
# the port at which the clients will connect
clientPort=3183
# 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
server.1=192.168.18.97:4181:5181
server.2=192.168.18.97:4182:5182
server.3=192.168.18.97:4183:5183

注意：每一个server下的zoo.cfg内容中主要关注几个点，dataDir是zookeeper存放数据的地方，自己手动新建一个位置，比如这里是zkdata，将路径赋值给dataDir即可。同理dataLogDir。对于clientPort是客户端端口，在单IP多节点的这种方式每个clientPort不能一样。在最后server.1,server.2,server.3这是指定zookeeper服务器，第一个端口比如4181是指各个zookeeper之间的通信端口，5181是各个zookeeper的选举leader端口。还有最重要的一点是这个server.1还要在zkdata文件夹下新建一个没有后缀名的myid文件，里面填写1.同理，server.2是在zkdata文件夹下新建一个myid,里面填写2.以此类推，比如server.3的话，请看下图：

启动zookeeper集群：一个一个启动每一个zookeeper服务器：

先后进入每一个zookeeper服务器的bin目录下执行zkserver.cmd,在先启动的zookeeper会打印其他zookeeper服务器未启动的错误信息，直至到最后一个启动的时候就没有异常信息了。

启动：

三 kafka集群

1.配置server.properties文件：

因为模板里面内容挺多的，我就贴一个出来作为演示说明：

# 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
broker.list=192.168.0.101:9093,192.168.0.102:9092
############################# Socket Server Settings #############################

# The port the socket server listens on
port=9093

# Hostname the broker will bind to. If not set, the server will bind to all interfaces
#host.name=localhost

# 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=

# 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=

# 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
#log.dirs=/tmp/kafka-logs
log.dirs=G:\Tools\JAVA\Kafka\kafka_2.11-0.8.2.2\kafka_2.11-0.8.2.2\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.
num.partitions=3

# 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

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

# 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

############################# 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=192.168.0.102:3181,192.168.0.102:3182,192.168.0.102:3183

# Timeout in ms for connecting to zookeeper
zookeeper.connection.timeout.ms=6000

需要修改的几个地方：

broker.id=1
broker.list=192.168.0.101:9093,192.168.0.102:9092

port=9093

log.dirs=G:\Tools\JAVA\Kafka\kafka_2.11-0.8.2.2\kafka_2.11-0.8.2.2\kafka-logs

zookeeper.connect=192.168.0.102:3181,192.168.0.102:3182,192.168.0.102:3183

每一个kafka服务器都需要有一个唯一的broker.id，这个broker.list是kafka集群的地址。

2.启动kafka集群，创建topics

主机win10启动kafka：

虚拟机启动kafka并且创建一个带2个备份的topic（test_yzr_2017_03_29）

三 测试集群

1.消息提供者和消费者之间的消息流通测试

比如在虚拟机上创建一个消息提供者：

kafka-console-producer.bat --broker-list 192.168.0.102:9092,192.168.0.101:9093 --topic test_yzr_2017_03_29

在虚拟机和win10主机上都创建一个消息消费者：

kafka-console-consumer.bat --zookeeper 192.168.0.102:3181 --topic test_yzr_2017_03_29

2.集群的容错性：

首先查看topic的信息

kafka-topics.bat --list --zookeeper 192.168.0.102:3181

或是改成(kafka-topics.bat --list --zookeeper 192.168.0.102:3182  和kafka-topics.bat --list --zookeeper 192.168.0.102:3183都是可以的，因为zookeeper集群共享数据)

查看指定的topic的详细信息：

kafka-topics.bat --describe --zookeeper --192.168.0.102:3181 --topic test_yzr_2017_03_29

可以看到此时选举的leader是0，即就是虚拟机中的kafka服务器，现在把虚拟机的kafka服务器给干掉。

此时leader为变为1，消费者能继续消费。