KafKa集群安装详细步骤

最近在使用Spring Cloud进行分布式微服务搭建，顺便对集成KafKa的方案做了一些总结，今天详细介绍一下KafKa集群安装过程：



1. 在根目录创建kafka文件夹（service1、service2、service3都创建）

[root@localhost /]# mkdir kafka



2.通过Xshell上传文件到service1服务器：上传kafka_2.9.2-0.8.1.1.tgz到/software文件夹

3.远程copy将service1下的/software/kafka_2.9.2-0.8.1.1.tgz到service2、service3

[root@localhost software]# scp -r /software/kafka_2.9.2-0.8.1.1.tgz root@192.168.2.212:/software/

[root@localhost software]# scp -r /software/kafka_2.9.2-0.8.1.1.tgz root@192.168.2.213:/software/



3.copy /software/kafka_2.9.2-0.8.1.1.tgz到/kafka/目录（service1、service2、service3都执行）

[root@localhost software]# cp /software/kafka_2.9.2-0.8.1.1.tgz /kafka/



4.安装解压kafka_2.9.2-0.8.1.1.tgz（service1、service2、service3都执行）

[root@localhost /]# cd /kafka/

[root@localhost kafka]# tar -zxvf kafka_2.9.2-0.8.1.1.tgz





5.创建kafka消息目录（service1,service2,service3都要创建）

[root@localhost kafka]# mkdir kafkaLogs



6. 修改kafka的配置文件（service1,service2,service3都要配置）

[root@localhost /]# cd /kafka/kafka_2.9.2-0.8.1.1/

[root@localhost kafka_2.9.2-0.8.1.1]# cd config/

[root@localhost config]# ls

consumer.properties  log4j.properties  producer.properties  server.properties  test-log4j.properties  tools-log4j.properties  zookeeper.properties

[root@localhost config]# vi 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  ---唯一标识



############################# Socket Server Settings #############################



# The port the socket server listens on

port=19092  --当前broker对外提供的TCP端口,默认9092



# Hostname the broker will bind to. If not set, the server will bind to all interfaces

host.name=192.168.2.213  --一般是关闭状态，我们要将它打开，如果dns解析失败，会出现文件句柄泄露，不要小看dns解析失败率，如果dns解析失败率为万分之一，由于kafka的性能非常高，每个topic的每个分区，每秒可以处理十万多条的数据，即使万分之一的失败率，每秒也要泄露10个文件句柄，很快句柄数就会泄露完毕，就会超过linux打开文件的数，就会出现异常，所以我们配置ip，就不会进行dns解析





# 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=2   --broker网络处理的线程数，一般不做处理



# The number of threads doing disk I/O

num.io.threads=8  --broker io处理的线程数，这个数量一定要比log.dirs的目录数要大



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

socket.send.buffer.bytes=1048576  --将发送的消息先放到缓冲区，当到达一定量的时候再一次性发出



# The receive buffer (SO_RCVBUF) used by the socket server

socket.receive.buffer.bytes=1048576  --kafka接受消息的缓冲区，当接受的数量达到一定量的时候再写入磁盘



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

socket.request.max.bytes=104857600   --像kafka发送或者请求消息的最大数，此设置不能超过java堆栈大小





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



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

log.dirs=/kafka/kafkaLogs  --多个目录可以用，隔开



# 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=2  --一个topic默认分区数



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



message.max.byte=5048576   --kafka每条消息容纳的最大大小

default.replication.factor=2  --默认的复制因子，默认消息只有一个副本，不太安全，所以设置为2，如果某个分区的消息失败了，我们可以使用另一个分区的消息服务

replica.fetch.max.byte=5048576 --kafka每条消息容纳的最大大小





# 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=536870912  --消息持久化的最大大小



# 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=60000



# 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  --不使用log压缩



############################# 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=192.168.2.211:2181,192.168.2.212:2181,192.168.2.213:2181   --zk地址



# Timeout in ms for connecting to zookeeper

zookeeper.connection.timeout.ms=1000000



7.启动kafka服务

[root@localhost bin]# ./kafka-server-start.sh -daemon ../config/server.properties

[root@localhost bin]# jps

27413 Kafka

27450 Jps

17884 QuorumPeerMain



8.验证kafka集群

[root@localhost bin]# ./kafka-topics.sh --create --zookeeper localhost:2181 --replication-factor 2 --partitions 1 --topic test

Created topic "test".



9.在service1上开启producer程序

./kafka-console-producer.sh --broker-list 192.168.2.211:9092 --topic test

[root@localhost bin]# ./kafka-console-producer.sh --broker-list 192.168.2.211:9092 --topic test

SLF4J: Failed to load class "org.slf4j.impl.StaticLoggerBinder".

SLF4J: Defaulting to no-operation (NOP) logger implementation

SLF4J: See http://www.slf4j.org/codes.html#StaticLoggerBinder for further details.





10. 在service2上开启consumer程序

[root@localhost bin]# ./kafka-console-consumer.sh --zookeeper localhost:2181 --topic test --from-beginning

SLF4J: Failed to load class "org.slf4j.impl.StaticLoggerBinder".

SLF4J: Defaulting to no-operation (NOP) logger implementation

SLF4J: See http://www.slf4j.org/codes.html#StaticLoggerBinder for further details.



11.在producer中发送消息：hello honghu

[root@localhost bin]# ./kafka-console-consumer.sh --zookeeper localhost:2181 --topic test --from-beginning

SLF4J: Failed to load class "org.slf4j.impl.StaticLoggerBinder".

SLF4J: Defaulting to no-operation (NOP) logger implementation

SLF4J: See http://www.slf4j.org/codes.html#StaticLoggerBinder for further details.

hello honghu



12. 在consumer中接受到消息

[root@localhost bin]# ./kafka-console-consumer.sh --zookeeper localhost:2181 --topic test --from-beginning

SLF4J: Failed to load class "org.slf4j.impl.StaticLoggerBinder".

SLF4J: Defaulting to no-operation (NOP) logger implementation

SLF4J: See http://www.slf4j.org/codes.html#StaticLoggerBinder for further details.

hello honghu
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