1. 先到官网下载kafka
链接地址：https://www.apache.org/dyn/closer.cgi?path=/kafka/2.4.1/kafka_2.13-2.4.1.tgz
2. tar命令解压包
image.png
[root@localhost kafka_2.13-2.4.1]# ll
总用量 56
drwxr-xr-x. 3 root root 4096 3月 3 08:35 bin #执行脚本
drwxr-xr-x. 2 root root 4096 4月 14 10:58 config #配置文件
drwxr-xr-x. 2 root root 6 4月 14 10:57 data #存储日志文件的目录
drwxr-xr-x. 2 root root 8192 4月 14 10:52 libs #依赖jar包
-rw-r--r--. 1 root root 32216 3月 3 08:32 LICENSE
drwxr-xr-x. 2 root root 182 4月 14 11:34 logs #日志
-rw-r--r--. 1 root root 337 3月 3 08:32 NOTICE
drwxr-xr-x. 2 root root 44 3月 3 08:35 site-docs #文档
config目录：
[root@localhost config]# ll
总用量 76
-rw-r--r--. 1 root root 906 3月 3 08:32 connect-console-sink.properties
-rw-r--r--. 1 root root 909 3月 3 08:32 connect-console-source.properties
-rw-r--r--. 1 root root 5321 3月 3 08:32 connect-distributed.properties
-rw-r--r--. 1 root root 883 3月 3 08:32 connect-file-sink.properties
-rw-r--r--. 1 root root 881 3月 3 08:32 connect-file-source.properties
-rw-r--r--. 1 root root 2247 3月 3 08:32 connect-log4j.properties
-rw-r--r--. 1 root root 1539 3月 3 08:32 connect-mirror-maker.properties
-rw-r--r--. 1 root root 2262 3月 3 08:32 connect-standalone.properties
-rw-r--r--. 1 root root 1221 3月 3 08:32 consumer.properties
-rw-r--r--. 1 root root 4675 3月 3 08:32 log4j.properties
-rw-r--r--. 1 root root 1925 3月 3 08:32 producer.properties
-rw-r--r--. 1 root root 8889 4月 14 11:23 server.properties #服务配置文件
-rw-r--r--. 1 root root 1032 3月 3 08:32 tools-log4j.properties
-rw-r--r--. 1 root root 1169 3月 3 08:32 trogdor.conf
-rw-r--r--. 1 root root 1205 3月 3 08:32 zookeeper.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.
# 经纪人的id。必须为每个代理将其设置为唯一整数。
broker.id=0
############################# 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
# 在项目中使用，别忘了打开注释
#listeners=PLAINTEXT://: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().
# 在项目中使用，别忘了打开注释 - 并修改成自己的ip
#advertised.listeners=PLAINTEXT://your.host.name: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
# 服务器用于接收来自网络的请求并向网络发送响应的线程数
num.network.threads=3
# The number of threads that the server uses for processing requests, which may include disk I/O
# 服务器用于处理请求（可能包括磁盘I/O）的线程数
num.io.threads=8
# The send buffer (SO_SNDBUF) used by the socket server
# 套接字服务器使用的发送缓冲区（sou SNDBUF）
socket.send.buffer.bytes=102400
# The receive buffer (SO_RCVBUF) used by the socket server
# 套接字服务器使用的接收缓冲区（SO RCVBUF）
socket.receive.buffer.bytes=102400
# The maximum size of a request that the socket server will accept (protection against OOM)
# 套接字服务器将接受的请求的最大大小（防止OOM）
socket.request.max.bytes=104857600
############################# Log Basics #############################
# A comma separated list of directories under which to store log files
# 以逗号分隔的存储日志文件的目录列表 - 自己创建的目录
log.dirs=/root/kafka_2.13-2.4.1/data
# 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.
# 每个主题的默认日志分区数。更多的分区允许使用更大的并行性，但这也会导致代理之间有更多的文件。
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.
# 启动时用于日志恢复和关闭时刷新的每个数据目录的线程数。
# 对于数据目录位于RAID阵列中的安装，建议增加此值。
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.
# 对于组元数据内部主题“消费者补偿”和“交易状态”的复制因子，对于开发测试以外的任何内容，建议使用大于1的值以确保可用性，如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
# 在将数据强制刷新到磁盘之前要接受的消息数
#log.flush.interval.messages=10000
# The maximum amount of time a message can sit in a log before we force a flush
# 在强制刷新之前，消息可以在日志中保留的最长时间
#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
# 日志文件的最短期限，可以根据期限进行删除
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.
# 日志的基于大小的保留策略。除非剩余的段低于log.retention.bytes，否则将从日志中删除段。功能独立于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.
# 日志段文件的最大大小。当达到此大小时，将创建一个新的日志段。
log.segment.bytes=1073741824
# The interval at which log segments are checked to see if they can be deleted according
# to the retention policies
# 根据保留策略检查日志段是否可以删除的间隔
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.
zookeeper.connect=localhost:2181
# Timeout in ms for connecting to zookeeper
# 连接到zookeeper超时（毫秒）
zookeeper.connection.timeout.ms=6000
############################# 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.
# 以下配置指定GroupCoordinator将延迟初始使用者重新平衡的时间（毫秒）。
# 当新成员加入组时，重新平衡将被group.initial.rebalance.delay.ms的值进一步延迟，最大值为max.poll.interval.ms。
# 默认值为3秒。
# 我们在这里将其重写为0，因为它可以为开发和测试提供更好的开箱即用体验。
# 然而，在生产环境中，3秒的默认值更合适，因为这将有助于避免在应用程序启动期间不必要的、潜在的昂贵的重新平衡。
group.initial.rebalance.delay.ms=0
启动服务
启动一个 Kafka 服务。命令行操作如下：
[root@localhost bin]# ./kafka-server-start.sh ../config/server.properties
[2020-04-14 14:09:16,882] INFO [TransactionCoordinator id=0] Starting up. (kafka.coordinator.transaction.TransactionCoordinator)
[2020-04-14 14:09:16,894] INFO [TransactionCoordinator id=0] Startup complete. (kafka.coordinator.transaction.TransactionCoordinator)
[2020-04-14 14:09:16,924] INFO [Transaction Marker Channel Manager 0]: Starting (kafka.coordinator.transaction.TransactionMarkerChannelManager)
[2020-04-14 14:09:17,005] INFO [ExpirationReaper-0-AlterAcls]: Starting (kafka.server.DelayedOperationPurgatory$ExpiredOperationReaper)
[2020-04-14 14:09:17,137] INFO [SocketServer brokerId=0] Started data-plane processors for 1 acceptors (kafka.network.SocketServer)
[2020-04-14 14:09:17,141] INFO [/config/changes-event-process-thread]: Starting (kafka.common.ZkNodeChangeNotificationListener$ChangeEventProcessThread)
[2020-04-14 14:09:17,171] INFO Kafka version: 2.4.1 (org.apache.kafka.common.utils.AppInfoParser)
[2020-04-14 14:09:17,171] INFO Kafka commitId: c57222ae8cd7866b (org.apache.kafka.common.utils.AppInfoParser)
[2020-04-14 14:09:17,171] INFO Kafka startTimeMs: 1586844557138 (org.apache.kafka.common.utils.AppInfoParser)
[2020-04-14 14:09:17,173] INFO [KafkaServer id=0] started (kafka.server.KafkaServer)
启动成功.
- 默认情况下，Kafka 日志文件所在地址为 logs/server.log 。如果想要自定义，可以通过 config/log4j.properties 配置文件来进行修改。
测试kafka 消息发送接收
- 创建一个Topic 为 demoTopic
[root@localhost bin]# ./kafka-topics.sh --create --zookeeper 127.0.0.1:2181 --replication-factor 1 --partitions 1 --topic demoTopic
Created topic demoTopic.
- 发送消息
[root@localhost bin]# ./kafka-console-producer.sh --broker-list 127.0.0.1:9092 --topic demoTopic
每输入一行，回车，都会发送一条消息
>test1
>test2
>test3
>test4
- 消费消息
[root@localhost bin]# ./kafka-console-consumer.sh --bootstrap-server 127.0.0.1:9092 --topic demoTopic --from-beginning
test1
test2
test3
test4
kafka管理控制台
- CMAK（kafka manager）安装包下载：https://blog.wolfogre.com/posts/kafka-manager-download/
[root@localhost ~]# wget https://github.com/wolfogre/kafka-manager-docker/releases/download/3.0.0.4/cmak-3.0.0.4.zip
- 解压
- 修改conf目录下application.conf
kafka-manager.zkhosts="127.0.0.1:2181" - 切换到bin目录
./kafka-manager 启动 - 访问地址
http://192.168.2.26:9000/
- 修改conf目录下application.conf
总结
- 已经简单的实现单机版的kafka 的搭建部署以及测试.
- Springboot Demo https://gitee.com/benbenyezi/kafka
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