Kafka集群搭建配置
本次演示使用 kafka_2.12-2.5.0
wsl2环境，单机集群
一、下载kafka
http://kafka.apache.org/downloads.html
二、解压
tar -zxvf kafka_2.12-2.5.0.tgz
三、复制3份
cp -r kafka_2.12-2.5.0.tgz ./kafka-cluster/kafka1/
cp -r kafka_2.12-2.5.0.tgz ./kafka-cluster/kafka2/
cp -r kafka_2.12-2.5.0.tgz ./kafka-cluster/kafka3/
四、新建3个kafka_data目录，用于存放kafka日志数据，不建议放在根目录中
注意：kafka-server每次启动前，要先清空掉日志文件
cd kafka-cluster
mkdir data_kafka1
mkdir data_kafka2
mkdir data_kafka3
至此，文件目录如下
├── data_kafka1
├── data_kafka2
├── data_kafka3
├── kafka_1
├── kafka_2
└── kafka_3
五、先启动zookeeper集群
看zookeeper集群部署文档，本次演示中，zk集群节点如下
127.0.0.1:2181,127.0.0.1:2182,127.0.0.1:2183
六、设置各个kafka的server.properties文件信息
注意有坑
如果listeners配置的host是localhost或者127.0.0.1，在windows的linux子系统内部署的Kafka集群，windows中将无法访问到此集群
解决方法：将listener的host配置为linux机的局域网地址，或者host，后续用节点地址来访问kafka集群
1.在linux子系统中执行以下命令，拿到在局域网中本机地址，（即inet节点的172.23.112.173）
ifconfig
############
eth0: flags=4163<UP,BROADCAST,RUNNING,MULTICAST> mtu 1500
inet 172.23.112.173 netmask 255.255.240.0 broadcast 172.23.127.255
inet6 fe80::215:5dff:fe73:d023 prefixlen 64 scopeid 0x20<link>
ether 00:15:5d:73:d0:23 txqueuelen 1000 (Ethernet)
RX packets 22748 bytes 34616063 (34.6 MB)
RX errors 0 dropped 0 overruns 0 frame 0
TX packets 3378 bytes 246784 (246.7 KB)
TX errors 0 dropped 0 overruns 0 carrier 0 collisions 0
lo: flags=73<UP,LOOPBACK,RUNNING> mtu 65536
inet 127.0.0.1 netmask 255.0.0.0
inet6 ::1 prefixlen 128 scopeid 0x10<host>
loop txqueuelen 1000 (Local Loopback)
RX packets 745864 bytes 146147115 (146.1 MB)
RX errors 0 dropped 0 overruns 0 frame 0
TX packets 745864 bytes 146147115 (146.1 MB)
TX errors 0 dropped 0 overruns 0 carrier 0 collisions 0
2.将此地址配置到server.properties的listeners中
文件配置
./kafka1/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.
## 注意修改此处，每个broker（分片）的id必须唯一
broker.id=1
########### 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://127.0.0.1:9092
## 注意修改此处，每个broker须监听不同端口
listeners = PLAINTEXT://172.23.112.173:9092
# 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://127.0.0.1:9092
# 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
# The number of threads that the server uses for processing requests, which may include 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 separated list of directories under which to store log files
## 注意修改此处，每个broker的日志地址须不一样
log.dirs=/home/jiangyi/env/kafka/kafka_cluster/data_kafka1/log
# 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=1
# 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 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
# 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
# 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
########### 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.
## 注意修改此处，填入本地zk地址，多个逗号间隔
zookeeper.connect=127.0.0.1:2181,127.0.0.1:2182,127.0.0.1:2183
# Timeout in ms for connecting to zookeeper
zookeeper.connection.timeout.ms=18000
########### 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
./kafka2/config/server.properties
## 与./kafka1/config/server.properties一致,只展示修改部分，省略......
########### Server Basics ###########
## 注意修改此处，每个broker（分片）的id必须唯一
broker.id=2
########### Socket Server Settings ###########
## 注意修改此处，每个broker须监听不同端口
listeners = PLAINTEXT://172.23.112.173:9093
########### Log Basics ###########
## 注意修改此处，每个broker的日志地址须不一样
log.dirs=/home/jiangyi/env/kafka/kafka_cluster/data_kafka2/log
./kafka3/config/server.properties
## 与./kafka1/config/server.properties一致,只展示修改部分，省略......
########### Server Basics ###########
## 注意修改此处，每个broker（分片）的id必须唯一
broker.id=3
########### Socket Server Settings ###########
## 注意修改此处，每个broker须监听不同端口
listeners = PLAINTEXT://172.23.112.173:9094
########### Log Basics ###########
## 注意修改此处，每个broker的日志地址须不一样
log.dirs=/home/jiangyi/env/kafka/kafka_cluster/data_kafka3/log
七、编写本地集群启动脚本
./start-cluster.sh
#!/bin/sh
## kafka启动前要删除所有本地日志
rm -rf /home/jiangyi/env/kafka/kafka_cluster/data_kafka*/*
/home/jiangyi/env/kafka/kafka_cluster/kafka_1/bin/kafka-server-start.sh -daemon /home/jiangyi/env/kafka/kafka_cluster/kafka_1/config/server.properties
echo "kafka-cluster broker 1 started"
/home/jiangyi/env/kafka/kafka_cluster/kafka_2/bin/kafka-server-start.sh -daemon /home/jiangyi/env/kafka/kafka_cluster/kafka_2/config/server.properties
echo "kafka-cluster broker 2 started"
/home/jiangyi/env/kafka/kafka_cluster/kafka_3/bin/kafka-server-start.sh -daemon /home/jiangyi/env/kafka/kafka_cluster/kafka_3/config/server.properties
echo "kafka-cluster broker 3 started"
echo "kafka-cluster started!!!"
脚本设置为可运行
chmod a+x ./*.sh
至此，当前目录结构
├── data_kafka1
├── data_kafka2
├── data_kafka3
├── kafka_1
├── kafka_2
├── kafka_3
└── start-cluster.sh
八、运行启动脚本
启动
./start-cluster.sh
## print
kafka-cluster broker 1 started
kafka-cluster broker 2 started
kafka-cluster broker 3 started
kafka-cluster started!!!
九、测试topic
创建test topic
./kafka_1/bin/kafka-topics.sh --create --zookeeper 127.0.0.1:2181,127.0.0.1:2182,127.0.0.1:2183 --replication-factor 1 --partitions 1 --topic test
查看所有topic
./kafka_1/bin/kafka-topics.sh --list --zookeeper 127.0.0.1:2181,127.0.0.1:2182,127.0.0.1:2183
十、测试producer和consumer
producer（为测试集群，特意监听不同的端口）
./kafka_2/bin/kafka-console-producer.sh --bootstrap-server 172.23.112.173:9094 --topic test
consumer
./kafka_3/bin/kafka-console-consumer.sh --bootstrap-server 172.23.112.173:9092 --topic test
producer输入信息，consumer能收到即成功