- 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 [email protected]:/software/
[root@localhost software]# scp -r /software/kafka_2.9.2-0.8.1.1.tgz [email protected]:/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
- 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=
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=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 Basic
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:
-
Durability: Unflushed data may be lost if you are not using replication.
-
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.
- 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×××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
启动kafka服务
[root@localhost bin]# ./kafka-server-start.sh -daemon ../config/server.properties
[root@localhost bin]# jps
Kafka
Jps
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: Seehttp://www.slf4j.org/codes.html#StaticLoggerBinderfor further details.
- 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: Seehttp://www.slf4j.org/codes.html#StaticLoggerBinderfor further details.
11.在producer中发送消息：hello jeesz
[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: Seehttp://www.slf4j.org/codes.html#StaticLoggerBinderfor further details.
hello jeesz
- 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: Seehttp://www.slf4j.org/codes.html#StaticLoggerBinderfor further details.
hello jeesz