Kafka 基础高可用版本基础安装使用
Kafka 基础高可用版本基础安装使用
说明
当前文档为高可用版本Kafka安装，需要三台主机，各个节点同时作为管理节点Zookeeper及Kafka节点。
操作系统基于CentOS 7，Kafka版本为 kafka_2.13-2.7.2。
zookeeper集群的每个节点zoo.cfg文件都是相同的，每个节点的环境变量也是相同的，所以下列操作在三台主机上都要进行。kafka及zookeeper都使用普通用户部署，本次使用的用户为kafka
资源划分如下：
| 序号 | 主机名 | 机器IP |
|---|---|---|
| 1 | open0004 | 10.0.0.208 |
| 2 | open0005 | 10.0.0.222 |
| 3 | open0006 | 10.0.0.232 |
部署
部署过程分为Zookeeper管理集群部署及Kafka节点部署两部分，其中发Zookeeper管理集群部署可以参考《Zookeeper基础使用》，其版本为2.4.13。
Zookeeper 部署
参考文档即可，需要注意在1.0.0之后的Kafka版本开始，Kafka的客户端节点不在需要与Zookeeper节点进行直接交互了，即Kafka的客户端节点不需要访问Zookeeper。
Kafka 进程安装
获取安装包
kafka_2.13-2.7.2.tgz，进行解压即可，假设解压至/home/kafka：
//要改版本1
/home/kafkatar -xzvf kafka_2.13-2.7.2.tgz -C /home/kafka
2.13：为Scala版本，如果并未使用其语言进行互操作，选定此版本即可2.7.2：为Kafka版本
调整配置文件内容如下，三个节点的配置文件不完全相同，请仔细查看修改（
/home/kafka/config/server.properties）：1
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139# 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
############################# 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://10.0.0.208:9092
listeners=PLAINTEXT://134.32.51.143:9092
# 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://10.0.0.208:9092
# 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
log.dirs=/home/kafka/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=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=3
transaction.state.log.replication.factor=3
#如果数据比较重要建议设置如下两个参数
#transaction.state.log.min.isr=2
default.replication.factor=3
############################# 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.
zookeeper.connect=10.0.0.208:2181,10.0.0.222:2181,10.0.0.232:2181
# 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- 注意：此配置仅调整了最基础配置，此处只做简要说明
broker.id=2：id集群内全局唯一，三个节点可分别设置为0、1、2，三个节点一定不能相同listeners：监听的端口及本机地址log.dirs=/home/kafka/kafka-logs：log.dirs为Kafka的数据目录，务必注意进行调整，要先创建/home/kafka/kafka-logs目录zookeeper.connect：Zookeeper管理集群地址，即全部Zookeeper进程的地址，此处我们使用10.0.0.208:2181,10.0.0.222:2181,10.0.0.232:2181
配置文件修改完毕后，各个节点使用如下命令启动即可：
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7进到命令目录
cd /home/kafka/bin
各节点均执行命令如下，同时指定了需要使用的配置文件
./kafka-server-start.sh -daemon ../config/server.properties
此命令可以将进程停止
./kafka-server-stop.sh
基础使用
以下是简单基础命令使用，围绕基础Topic使用展开。
创建
topic：1
[kafka@localhost bin]$ ./kafka-topics.sh --create --bootstrap-server 10.0.0.208:9092,10.0.0.222:9092,10.0.0.232:9092 --replication-factor 1 --partitions 1 --topic test
kafka-topics.sh：操作及使用topic的客户端命令bootstrap-server：指定全部Kafka节点replication-factor：指定创建的topic副本数partitions：指定创建的topic分区数
查看
topic：1
2[kafka@localhost bin]$ ./kafka-topics.sh --list --bootstrap-server 10.0.0.208:9092,10.0.0.222:9092,10.0.0.232:9092
testtest：即上一条命令创建的topic名称
发送消息，客户端作为生产者向
Kafka集群发送消息，发送至之前创建的test主题中：1
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5[kafka@localhost bin]$ ./kafka-console-producer.sh --broker-list 10.0.0.208:9092,10.0.0.222:9092,10.0.0.232:9092 --topic test
kafka
nihao
are you ok?消费者消费消息：
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5[kafka@localhost bin]$ ./kafka-console-consumer.sh --bootstrap-server 10.0.0.208:9092,10.0.0.222:9092,10.0.0.232:9092 --topic test --from-beginning
kafka
nihao
are you ok?from-beginningkafka：即当前消费者连接成功后从最初消息开始消费- 获取到的消息与生产者发送的消息一致
此时通过生产者客户端继续发送消息，消费者客户端可以立即读取到
topic删除：1
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5[kafka@localhost bin]$ ./kafka-topics.sh --delete --bootstrap-server 10.0.0.208:9092,10.0.0.222:9092,10.0.0.232:9092 --topic test
此处可以看到，之前创建的 test 主题以及被删除了
[nanquanyuhao@localhost bin]$ ./kafka-topics.sh --list --bootstrap-server 10.0.0.208:9092,10.0.0.222:9092,10.0.0.232:9092
__consumer_offsets查看活动的消费者组
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3[kafka@localhost bin]$ ./kafka-consumer-groups.sh --bootstrap-server 10.0.0.208:9092,10.0.0.222:9092,10.0.0.232:9092 --list
console-consumer-73977
console-consumer-16609查看某消费者组消费的各
topic的延迟情况：1
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5[kafka@localhost bin]$ ./kafka-consumer-groups.sh --bootstrap-server 10.0.0.208:9092,10.0.0.222:9092,10.0.0.232:9092 --describe --group test_agroup
Consumer group 'test_agroup' has no active members.
TOPIC PARTITION CURRENT-OFFSET LOG-END-OFFSET LAG CONSUMER-ID HOST CLIENT-ID
aliCloud_describeInstanceMonitorData_original 0 12 12 0 - - -
压力测试
由于组内平时负责各种基础中间件运维，针对Kafka使用后的内存占用情况并不十分清晰，使用自带压测工具做个简单压测，简单观察内存使用情况，只在一个节点做即可。
生产端压测
1 | [kafka@localhost bin]$ ./kafka-producer-perf-test.sh --topic test --record-size 200 --num-records 100000 --throughput 1000 --producer-props bootstrap.servers=10.0.0.208:9092,10.0.0.222:9092,10.0.0.232:9092 |
--record-size 200：每一条消息的大小为100字节--num-records 100000：压测写入消息的总数量为100000--throughput 1000：写入消息的最大吞吐速率限制为1000条每秒
据压测结果看，其不会超过限制的最大速率保持为999.670109 records/sec，并罗列了延迟时间等相关指标
消费端压测
1 | [kafka@localhost bin]$ ./kafka-consumer-perf-test.sh --broker-list 10.0.0.208:9092,10.0.0.222:9092,10.0.0.232:9092 --topic test --fetch-size 10000 --messages 1000000 --threads 10 |
--fetch-size 10000：指定每次fetch的数据的大小为10000字节--messages 1000000：总共要消费的消息个数为1000000个--threads 10： 消费进程数量，默认就是10
- 标题: Kafka 基础高可用版本基础安装使用
- 作者: Lan Yu
- 创建于 : 2024-07-10 21:39:22
- 更新于 : 2026-10-28 12:12:48
- 链接: https://blog.lanyu.dev/2024/07/10/Kafka 基础高可用版本安装使用/
- 版权声明: 本文章采用 CC BY-NC-SA 4.0 进行许可。
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