window环境搭建zookeeper,kafka集群
2017-09-13 10:43
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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:
三台zookeeper服务器,都安装在同一台虚拟机中。
本机win10,和虚拟机分别安装一台kafka服务器。
将主机的防火墙也关闭。
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:
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:
server2的zoo.cfg文件:
server3的zoo.cfg文件:
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:
因为模板里面内容挺多的,我就贴一个出来作为演示说明:
需要修改的几个地方:
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)
比如在虚拟机上创建一个消息提供者:
在虚拟机和win10主机上都创建一个消息消费者:
2.集群的容错性:
首先查看topic的信息
或是改成(
查看指定的topic的详细信息:
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。
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:
三台zookeeper服务器,都安装在同一台虚拟机中。
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
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;将主机的防火墙也关闭。
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=<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 #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)
四 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。
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