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一、kafka原理

1、kafka是一个高性能的消息队列系统，能够处理大规模的数据流，并提供低延迟的数据传输，它能够以每秒数十万条消息的速度进行读写操作。

二、kafka优点

1、服务解耦

（1）提高系统的可维护性‌

   通过服务解耦，可以将系统分解为独立的部分，当需要更新或修复某个服务时，可以独立地进行操作，而不会影响到其他服务的正常运作。这大大减少了维护工作的难度和所需时间。

‌（2）增强系统的可扩展性‌

      解耦后的系统更容易扩展。添加新功能或服务通常不会影响现有系统的其他部分，从而快速响应市场和用户的需求变化。

2、高吞吐量、低延迟

    kafka每秒可以处理几十万条消息，它的延迟最低只有几毫秒，每个topic可以分多个partition, consumer group 对partition进行consume操作。

3、可扩展性

    集群支持热扩展（kafka-reassign-partitions.sh）分区重分配、迁移

4、持久性、可靠性

消息被持久化到本地磁盘，并且支持数据备份防止数据丢失

5、容错性

允许集群中节点失败（若副本数量为n,则允许n-1个节点失败）

6、高并发

支持数千个客户端同时读写

三、主要概念

1. 主题 (Topic)

Kafka 中的消息以主题 (Topic) 为单位进行组织。每个主题代表一个消息流，消息生产者向主题发送消息，消息消费者从主题消费消息。

2. 分区 (Partition)

每个主题可以分为多个分区 (Partition)，每个分区是一个有序、不可变的消息序列。分区的存在使得 Kafka 能够水平扩展，可以处理大量数据并提供高吞吐量。

3. 副本 (Replica)

为了保证数据的高可用性，Kafka 允许每个分区有多个副本 (Replica)，这些副本存储在不同的服务器上。这样，即使某个服务器故障，数据仍然可用。

4. 生产者 (Producer)

生产者是向 Kafka 主题发送消息的客户端。生产者可以选择将消息发送到特定的分区，也可以让 Kafka 根据某种策略（如轮询）决定将消息发送到哪个分区。

5. 消费者 (Consumer)

消费者是从 Kafka 主题消费消息的客户端。消费者通常属于某个消费者组 (Consumer Group)，一个消费者组中的多个消费者可以并行消费同一个主题的不同分区，提高消费速度和效率。

6. 经纪人 (Broker)

Kafka 集群由多个经纪人 (Broker) 组成，每个经纪人是一个 Kafka 实例。经纪人负责存储消息并处理消息的读写请求。

7. ZooKeeper

ZooKeeper 是一个分布式协调服务，Kafka 使用 ZooKeeper 来管理集群元数据，如主题、分区、经纪人等信息。

四、kafka安装教程

   1、 点此链接进入官网下载地址

   2、点击 图1红色方框DOWNLOAD KAFKA 

                            图1

3、点击图2选中的链接下载即可

图2

3、将kafka解压到服务器后修改配置项kafka_2.13-4.0.0\config\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.
# the directory where the snapshot is stored.
dataDir=/tmp/zookeeper
# the port at which the clients will connect
clientPort=2181
# disable the per-ip limit on the number of connections since this is a non-production config
maxClientCnxns=0
# Disable the adminserver by default to avoid port conflicts.
# Set the port to something non-conflicting if choosing to enable this
admin.enableServer=true
admin.enable=true
audit.enable=true
# admin.serverPort=8080

4、修改配置项 kafka_2.13-4.0.0\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.#
# This configuration file is intended for use in ZK-based mode, where Apache ZooKeeper is required.
# 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=1############################# Socket Server Settings ############################## The address the socket server listens on. If not configured, the host name will be equal to the value of
# java.net.InetAddress.getCanonicalHostName(), with PLAINTEXT listener name, and port 9092.
#   FORMAT:
#     listeners = listener_name://host_name:port
#   EXAMPLE:
#     listeners = PLAINTEXT://your.host.name:9092
listeners=PLAINTEXT://10.11.22.122:9092# Listener name, hostname and port the broker will advertise to clients.
# If not set, it uses the value for "listeners".
#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
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=/app/test/kafka/kafka_2.13-3.2.3/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=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=10.11.22.121:2181,10.11.22.122:2181,10.11.22.124:2181
zookeeper.connect=10.11.22.122:2181# Timeout in ms for connecting to zookeeper
zookeeper.connection.timeout.ms=180000############################# 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

5、下载zookeeper

按照图3所示点击网站链接下载zookeeper

(1点击链接到zookeeper下载网址

           图3

解压到服务器进入到apache-zookeeper-3.9.3-bin\conf目录下新建文件zoo.cfg

# The number of milliseconds of each tick
tickTime=2000
# The number of ticks that the initial 
# synchronization phase can take
initLimit=10
# The number of ticks that can pass between 
# sending a request and getting an acknowledgement
syncLimit=5
# the directory where the snapshot is stored.
# do not use /tmp for storage, /tmp here is just 
# example sakes.
dataDir=/app/install-test/zk/zookeeper-3.4.6/zkdata
dataLogDir=/app/install-test/zk/zookeeper-3.4.6/logs
# the port at which the clients will connect
clientPort=2181
# the maximum number of client connections.
# increase this if you need to handle more clients
#maxClientCnxns=60
#
# Be sure to read the maintenance section of the 
# administrator guide before turning on autopurge.
#
# https://zookeeper.apache.org/doc/current/zookeeperAdmin.html#sc_maintenance
#
# The number of snapshots to retain in dataDir
#autopurge.snapRetainCount=3
# Purge task interval in hours
# Set to "0" to disable auto purge feature
#autopurge.purgeInterval=1
audit.enable=true
## Metrics Providers
#
# https://prometheus.io Metrics Exporter
#metricsProvider.className=org.apache.zookeeper.metrics.prometheus.PrometheusMetricsProvider
#metricsProvider.httpHost=0.0.0.0
#metricsProvider.httpPort=7000
#metricsProvider.exportJvmInfo=trueserver.1=10.11.22.122:2888:2889
#server.2=10.11.22.123:2888:2889
#server.3=10.11.22.124:2888:2889

  6、修改各配置项后先启动zookeeper服务,进入到kafka_2.13-4.0.0文件夹启动命令如下

./bin/zookeeper-server-start.sh  -daemon ./config/zookeeper.properties 

启动成功后查看进程

ps -ef| grep zookeeper

启动成功后如图4所示

图4

7、切换到目录apache-zookeeper-3.9.3-bin\bin目录下输入命令启动zookeeper客户端

./zkCli.sh  -daemon

启动成功后如图5所示

图5

8、切换到kafka_2.13-4.0.0文件夹输入kafka启动命令

./bin/kafka-server-start.sh  -daemon ./config/server.properties 

启动成功后查看进程如图6所示

ps -ef| grep kafka

     图6