鲲鹏麒麟安装Kafka-v1.1.1
因项目需要在鲲鹏麒麟服务器上安装Kafka v1.1.1，因此这里将安装配置过程记录下来。
环境说明
# 查看系统相关详细信息
[root@test kafka_2.12-1.1.1]# uname -a
Linux test.novalocal 4.19.148+ #1 SMP Mon Oct 5 22:04:46 EDT 2020 aarch64 aarch64 aarch64 GNU/Linux
# 查看操作系统版本信息
[root@test kafka_2.12-1.1.1]# cat /etc/kylin-release
Kylin Linux Advanced Server release V10 (Tercel)
# 查看逻辑CPU数量
[root@test kafka_2.12-1.1.1]# cat /proc/cpuinfo| grep "processor"| wc -l
32
# 查看CPU信息
[root@test kafka_2.12-1.1.1]# lscpu
Architecture: aarch64
CPU op-mode(s): 64-bit
Byte Order: Little Endian
CPU(s): 32
On-line CPU(s) list: 0-31
Thread(s) per core: 1
Core(s) per socket: 16
Socket(s): 2
NUMA node(s): 2
Vendor ID: HiSilicon
Model: 0
Model name: Kunpeng-920
Stepping: 0x1
CPU max MHz: 2400.0000
CPU min MHz: 2400.0000
BogoMIPS: 200.00
L1d cache: 2 MiB
L1i cache: 2 MiB
L2 cache: 16 MiB
L3 cache: 64 MiB
NUMA node0 CPU(s): 0-15
NUMA node1 CPU(s): 16-31
Vulnerability Itlb multihit: Not affected
Vulnerability L1tf: Not affected
Vulnerability Mds: Not affected
Vulnerability Meltdown: Not affected
Vulnerability Spec store bypass: Not affected
Vulnerability Spectre v1: Mitigation; __user pointer sanitization
Vulnerability Spectre v2: Not affected
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Not affected
Flags: fp asimd evtstrm aes pmull sha1 sha2 crc32 atomics fphp asimdhp cpuid asimdrdm jscvt fcma dcpop asimddp asimdfhm
# 查看Java的版本信息
[root@test kafka_2.12-1.1.1]# java -version
openjdk version "1.8.0_242"
OpenJDK Runtime Environment (build 1.8.0_242-b08)
OpenJDK 64-Bit Server VM (build 25.242-b08, mixed mode)
下载
从apache官网下载相应的版本信息，地址：https://kafka.apache.org/downloads，找到1.1.1版本下载即可，这里下载kafka_2.12-1.1.1.tgz，下载地址：https://archive.apache.org/dist/kafka/1.1.1/kafka_2.12-1.1.1.tgz
这里的版本号有两段，前一段为Scala的版本号，后一段为Kafka的版本，现在最新版本已经到3.X，这里用1.1.1，主要是项目特殊需要，建议还是用高版本的。
Scala 2.11 和 Scala 2.12 是 Scala 编程语言的两个主要版本，它们之间存在一些关键的区别
1. 性能优化
Scala 2.12 在性能方面做了很多优化，特别是在 JVM 上。它引入了值类（Value Classes）的改进，减少了运行时的开销。
Scala 2.11 的性能相对较低，但它的优化主要集中在稳定性和兼容性上。
2. 字符串插值
Scala 2.12 引入了新的字符串插值语法，使用 s 前缀，例如 s"Hello, $name"。
Scala 2.11 使用的是旧的字符串插值语法，使用 #{}，例如 "Hello, #{name}"。
3. 隐式转换
Scala 2.12 对隐式转换进行了一些改进，使其更加安全和易于理解。
Scala 2.11 的隐式转换机制相对较为复杂，容易引起混淆。
4. 模块化
Scala 2.12 引入了模块化系统，允许开发者将代码分割成多个模块，便于管理和维护。
Scala 2.11 没有模块化系统，所有代码都放在一个项目中。
5. 兼容性
Scala 2.12 相对于 Scala 2.11 有一些不兼容的更改，特别是在 API 和库的使用上。因此，从 Scala 2.11 迁移到 Scala 2.12 可能需要一些工作。
Scala 2.11 是一个长期支持（LTS）版本，这意味着它将获得更长时间的支持和维护。
6. 社区支持
Scala 2.12 是目前的主流版本，得到了广泛的社区支持和库的更新。
Scala 2.11 虽然仍然在使用，但社区支持逐渐减少。
总结
如果你正在开发一个新的项目，建议使用 Scala 2.12 或更高版本，以获得更好的性能和更多的功能。如果你正在维护一个现有的 Scala 2.11 项目，可以考虑在适当的时候迁移到 Scala 2.12，但需要注意兼容性问题。
部署
1、解压文件执行
tar -zxvf kafka_2.12-1.1.1.tgz
2、解压后路径为
[root@test kafka_2.12-1.1.1]# pwd
/data/public/kafka/kafka_2.12-1.1.1
3、修改config/server.properties，注意修改listeners和advertised.listeners即可
# 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://192.138.31.100:9092
# 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://192.138.31.100:9092
# 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=409600000
############################# Log Basics #############################
# A comma separated list of directories under which to store log files
log.dirs=/tmp/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 for 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.
zookeeper.connect=localhost:2181
# Timeout in ms for connecting to zookeeper
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.
group.initial.rebalance.delay.ms=0
启动
1、先启动Zookeeper，执行
nohup /data/public/kafka/kafka_2.12-1.1.1/bin/zookeeper-server-start.sh /data/public/kafka/kafka_2.12-1.1.1/config/zookeeper.properties > /dev/null 2>&1 &
2、然后启动Kafka，执行
nohup /data/public/kafka/kafka_2.12-1.1.1/bin/kafka-server-start.sh /data/public/kafka/kafka_2.12-1.1.1/config/server.properties > /dev/null 2>&1 &
3、检查是否启动
[root@test kafka_2.12-1.1.1]# netstat -nltp | grep -E '(2181|9092)'
tcp6 0 0 192.168.31.100:9092 :::* LISTEN 970022/java
tcp6 0 0 :::2181 :::* LISTEN 966577/java
表明Kafka已经启动起来，其中2181为Zookeeper的端口，9092为Kafka的端口
开启客户端访问
firewall-cmd --zone=public --add-port=2181/tcp --permanent
firewall-cmd --zone=public --add-port=9092/tcp --permanent
firewall-cmd --reload
使用Offset Explorer 2.0访问
配置完成后，连接服务器，这时就可以使用Kafka进行生产和消费消息了。
原文地址：https://blog.csdn.net/Angushine/article/details/144390646
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