文章目录

1. 概述
- 1.1. 消息队列
- 1.2. 应用场景
- 1.3. 工作模式
- 1.4. 基础结构
- - 1.4.1. 结构组件
  - 1.4.2. 数据同步
  - 1.4.3. ACK机制
  - 1.4.4. 分区机制
  - - 1.4.4.1. 使用Partition Key写入
    - 1.4.4.2. 轮询写入 - 默认规则
    - 1.4.4.3. 指定Partition写入
  - 1.4.5. Offset偏移量
  - - 1.4.5.1. 消息顺序性
    - 1.4.5.2. Coordinator协调者
  - 1.4.5. ConsumerGroup消费者组
  - 1.4.6. Rebalance机制
  - 1.4.7. 数据一致性
  - - 1.4.7.1. Replicas副本机制
    - 1.4.7.2. Leader选举
    - 1.4.7.3. 可靠性保证
- 1.5 ZK目录结构
- - 1.5.1. /brokers
  - - 1.5.1.1. /brokers/ids
    - 1.5.1.2. /brokers/topics
  - 1.5.2. /consumers
  - - 1.5.2.1. /consumers/{groupId}/ids
    - 1.5.2.2. /consumers/{groupId}/owner
    - 1.5.2.3. /consumers/{groupId}/offset
  - 1.5.3. /admin
  - - 1.5.3.1. /admin/reassign_partitions
    - 1.5.3.2. /admin/preferred_replica_election
    - 1.5.3.3. /admin/delete_topics
  - 1.5.4. /controller
  - 1.5.5. /controller_epoch
2、服务安装
- 2.1. 单机部署
- 2.2. 伪集群部署
- 2.3. 集群操控脚本
- 2.5. 客户端命令行操作
- - 2.5.1. Topic
  - 2.5.2. Producer
  - 2.5.3. Consumer
  - 2.5.4. Consumer group
  - 2.5.5. 操作案例
  - - 2.5.5.1. Topic
    - 2.5.5.2. Producer + Consumer
    - 2.5.5.3. Consumer group
  - 2.5.4. 分区与副本调整
  - - 2.5.4.1. 分区扩容
    - 2.5.4.2. 副本扩容
  - 2.5.5. 消息积压清理
  - 2.5.6. 重选选举Leader主分区
- 2.6. 报错记录
- - 2.6.1. 创建topic时报错
  - 2.6.2. 使用工具时直接返回参数列表
  - 2.6.3. 未知的选项
  - 2.6.4. 重置offset时异常
  - 2.6.5. json格式文件工具
  - 2.6.6. Leader重新选举报错
3、Python连接Kafka
- 3.1. 生产者
- 3.2. 消费者
- 3.3. 执行结果

1. 概述

Kafka是Apache基金会开发的一个开源流处理平台，由Scala和Java编写，Kafka是一个开源的分布式事件流平台，主要应用于大数据实时处理领域。

1.1. 消息队列

目前企业中常见的消息队列产品主要有RabbitMQ、ActivceMQ、RocketMQ、Kafka等。在大数据场景下主要采用Kafka作为消息队列，在JavaEE开发中主要采用RabbitMQ、ActivceMQ、RocketMQ作为消息队列进行使用。

1.2. 应用场景

传统消息队列的主要应用场景有：缓存/消峰、解耦合、异步通信。

缓存/消峰：有助于控制和优化数据流经过系统的速度，解决生产消息和消费消息的处理速度不一致情况。
解耦合：允许独立的扩展或修改两边处理过程，只考虑遵守Kafka接口约束规则即可。
异步通信：允许用户将消息放入队列，并不需要立即处理消息，等待需要时进行处理即可。

1.3. 工作模式

点对点模式：消费者主动拉取数据，消息收到后清除队列中消息；
发布/订阅模式：存在多个topic主题，消费者消费数据后不做删除操作，每个消费者相互独立，都可以消费到所需消息。

1.4. 基础结构

在这里插入图片描述

1.4.1. 结构组件

Broker：Kafka服务实例或服务节点，多个Broker构成了Kafka Cluster；
Producer：生产者，写入消息的角色，将消息写入Broker的Topic Partition Leader副本内；
Consumer：消费者，读取消息的角色，从Broker的Topic Partition Leader读取生产者写入的消息；
Consumer Group：消费者组，一个或多个消费者构成一个消费组，不同的消费组可以订阅同一个主题的消息且互不影响；
ZooKeeper：Kafka Cluster使用ZK来管理集群的Broker、Topic、Partition等元数据，以及控制器的选举；
Topic：消息主题（逻辑概念），每一个消息都属于某个主题，Kafka通过主题来区分不同的消息；
Partition：分区，一个Topic可以划分多个分区，一个分区只属于一个主题；
Replica：副本，一个分区可以拥有多个副本来提高数据可靠性；
Leader & Follower：分区角色，当某个Topic划分为多个分区时，单个分区拥有多个副本，这些副本需要进行消息同步保证数据一致性，主副本提供读写能力，从副本不提供读写，仅仅作为主副本的备份及时同步数据即可；
Offset：偏移量（类比TCP协议分段），分区中的每一条消息都有一个所在分区的偏移量，这个偏移量唯一标识了该消息在当前这个分区的位置，并保证在这个分区的顺序性，不可保证跨分区的顺序性。

1.4.2. 数据同步

以一次数据生产者发送消息的流程进行介绍数据复制过程。
在这里插入图片描述

流程如下：

生产者Producer向Kafka cluster集群中Broker的Topic Partition Leader发送消息请求，写入消息；
Topic Partition Leader收到后，存储完成，并将消息同步到其他Topic Partition Follower；
Follower同步并存储完成后返回ACK至Leader处，当Leader收集到所有Follower的存储确认后，向Producer返回消息写入完成ACK；
消费者Consumer此时就可以向Topic Partition Leader发送消费请求，消费存储好的数据。

1.4.3. ACK机制

在前述流程中Kafka Cluster的ACK响应机制分为三种：

ack=0：生产者Producer向Partition Leader发送消息请求后立即返回ACK，此时消息有可能还未落盘；写入消息吞吐量最高，但数据可靠性最低；
ack=1：生产者Producer向Partition Leader发送消息请求后等待Leader写入成功后返回ACK，此时只有Leader分区存储完成，Follower未存储消息；写入消息吞吐量偏高，但消息还未同步给Follower，若Leader异常则会发生数据丢失问题，因此数据可靠性偏低；
ack=-1：生产者Producer向Partition Leader发送消息请求后，等待Leader和ISR中的Follower都存储完成后返回ACK；写入消息吞吐量较前两种类型更低，但数据可靠性最高，极端情况也会存在数据丢失的风险（当ISR中的Follower均异常时，此时ack=-1系效果等于ack=1，因此数据可靠性最高的场景为：ack=-1 + ISR follower num >= 2）。

1.4.4. 分区机制

Kafka中Topic被分成多个Partition分区，Topic是一个逻辑概念，而Partition是最小存储单元，每个Partition都是一个单独的log文件，每条消息都会以追加的形式写入到此log文件内，因此Producer或Consumer都可以进行并发请求，显著提升I/O性能。

在这里插入图片描述

1.4.4.1. 使用Partition Key写入

Producer发送消息时，可以指定Partition Key（任意值，如UserID），将Key传递到HASH函数，再与该Topic的Partition总数进行取余可得到分区号，此消息因此写入所得编号的Partition内。

优点：使用此方法得到的分区编号可以使得相同UserID的消息存储在同一个分区内；
缺点：如果该UserID产生的消息特别多，那么此分区会异常繁忙，发生数据倾斜问题。

1.4.4.2. 轮询写入 - 默认规则

如果没有使用Partition Key，Kafka默认使用轮询的方式来决定写入哪个Partition，因此消息会均衡的写入各个Partition。

1.4.4.3. 指定Partition写入

Kafka 支持自定义规则，一个Producer可以使用自己的分区指定规则。

1.4.5. Offset偏移量

Topic Partition中的每条记录都会被分配一个唯一的序号，称为Offset（偏移量）。Offset是一个递增的、不可变的数字，由Kafka自动维护。当一条记录写入Partition的时候，它就被追加到log文件的末尾，并被分配一个序号，作为Offset。在消息消费的时候对于一个消费组来说，在一个分区上也会设置一个Offset（消费组的Offset）。

在这里插入图片描述

1.4.5.1. 消息顺序性

一个Topic如果有多个Partition的话，那么从Topic来看消息是无序的，而从Partition来看内部消息有序，跨Partition无序，因此若需要Topic得消息有序，则需要配置该Topic为单个Partition即可。

1.4.5.2. Coordinator协调者

Offset偏移量如何进行存储？一个集群上可能有成百上千个消费组，如何进行分配？

实际上Kafka创建一个内部Topic用来存储Offset偏移量信息，名称为**__consumer_offsets**，这时某个消费组如何找到自己被那个Broker代理？

服务端会通过消费组的HASH对__consumer_offsets的分区数（offsets.topic.num.partitions默认是50，offsets.topic.replication.factor默认为1）进行取模操作，其取值即为Partition编号，这样就拿到了这个消费组的Offset是存在于那个Partition上，然后获取__consumer_offsets topic的该编号Partition的元数据信息，其中Leader就是这个消费组的代理节点即Coordinator（协调者）。

[root@master kafka_cluster]# sh kafka-1/bin/kafka-topics.sh --bootstrap-server 127.0.0.1:9092 --describe --topic __consumer_offsets
Topic: __consumer_offsets       TopicId: B2x90fF5TDOzlyvKQcqGNA PartitionCount: 50      ReplicationFactor: 1    Configs: compression.type=producer,cleanup.policy=compact,segment.bytes=104857600Topic: __consumer_offsets       Partition: 0    Leader: 2       Replicas: 2     Isr: 2~ # 以下内容省略

在一个消费节点启动之后会先从服务端获取该消费组的Coordinator，即发起Findcoordinator请求，然后获取本消费节点处理的分区当前消费的Offset位置，即发起OffsetFetch请求。才可以知道从各个分区应该从哪个位置开始拉取消息数据。

1.4.5. ConsumerGroup消费者组

ConsumerGroup下可以有一个或多个Consumer，Consumer可以是一个进程，也可以是一个线程；
Group.id是一个字符串，唯一标识一个ConsumerGroup；
ConsumerGroup下订阅的Topic下的每个分区只能分配给某个Group下的一个Consumer(当然该分区还可以被分配给其他Group)。

1.4.6. Rebalance机制

Kafka集群模式下，一个Topic有多个Partition，对于消费方来说可以有多个Consumer同时消费这些Partition，为保证Partition和Consumer的均衡性，提升Topic的并发能力，Rebalance规定了一个ConsumerGroup下的所有Consumer如何分配订阅Topic的每个Partition。

Rebalance机制场景：

ConsumerGroup组内成员数量发生变化；
Consumer消费超时；
Group订阅Topic数量发生变化；
Group订阅Topic下Partition数量发生变化。

1.4.7. 数据一致性

从Producer向Broker发送消息、Topic Partition与Replicas及其Leader选举几个角度介绍数据传输可靠性。

AR：Assigned Replicas，所有的副本；
ISR：In-Sync Replicas，所有和主副本保持同步的副本集合（Follower在replica.lag.time.max.ms时间范围内同步到Leader的LEO位置即可）；
OSR：Out-of-Sync Replicas，所有和主副本未保持一致的副本集合；

AR = ISR + OSR

LEO：Log End Offset，下一个消息将要写入的Offset偏移位置，在LEO之前的消息都已完成写入日志，每个副本都有一个自己的LEO位置；
HW：High Watermark，所有与主副本保持同步的副本中，最小的LEO就是HW，意味着在这之前的消息都已经被所有的ISR副本写入到日志中，即使主副本异常后其中一个ISR副本成为主副本时消息也不会发生丢失问题。

1.4.7.1. Replicas副本机制

Kafka从0.8.0版本引入副本机制，每个Partition可以自定义设置副本数量（默认配置数量为3），多个副本中有一个为Leader，其余为Follower，Follower定期向Leader请求数据同步，当Leader异常时可以重新选举出新的Leader，提高Kafka的数据冗余。

Replicas副本机制为Partition分区的机制，并非Topic主题！

1.4.7.2. Leader选举

每个Partition的Leader都会维护一个ISR列表（Follower副本的Broker编号），只有与Leader同步完成的副本Follower才能加入到ISR列表中，由参数replica.lag.time.max.ms控制（默认10s），只有在ISR列表内的Follower才可以成为Leader（默认配置unclean.leader.election.enable=false，不能从非ISR的副本列表里选择Leader）。因此当Leader异常后，会从ISR列表中选择第一个Follower作为新Leader，以此保证Kafka的消息数据可靠性。

1.4.7.3. 可靠性保证

ACK机制：acks=all（或request.required.acks=-1），同时producer.type=sync
副本数量：设置replication.factor>=3，并且 min.insync.replicas>=2；
分区副本选举：关闭不完全的Leader 选举（unclean.leader.election.enable=false）且保持offsets.topic.replication.factor > 1；

1.5 ZK目录结构

在这里插入图片描述

[root@master ~]# vim /kafka_cluster/kafka-1/config/server.properties
# 测试场景中配置ZK连接位置如下，则ZK中存储的Kafka元数据均位于/kafka路径下
zookeeper.connect=localhost:2181/kafka

1.5.1. /brokers

当一个Broker启动时,会向ZK注册自己持有的Topic和Partitions信息。

> ls /kafka/brokers
[ids, seqid, topics]

1.5.1.1. /brokers/ids

每个Broker的配置文件中都需要指定一个数字类型的id(全局不可重复)，此节点为临时 Znode(EPHEMERAL)。

> ls /kafka/brokers/ids 
[0, 1, 2]
> get -s /kafka/brokers/ids/0
{"listener_security_protocol_map": {"PLAINTEXT": "PLAINTEXT"			# 明文显示},"endpoints": ["PLAINTEXT://master:9092"],"jmx_port": -1,									# jmx端口号"features": {},"host": "master",								# 主机名或ip地址"timestamp": "1691651715646",		# broker初始启动时的时间戳"port": 9092,										# broker的服务端端口号，由server.properties中参数port确定"version": 5										# 版本编号默认为1，递增
}
cZxid = 0x300000071
ctime = Thu Aug 10 15:15:15 CST 2023
mZxid = 0x300000071
mtime = Thu Aug 10 15:15:15 CST 2023
pZxid = 0x300000071
cversion = 0
dataVersion = 1
aclVersion = 0
ephemeralOwner = 0x100233882bf0008	# 临时节点标识
dataLength = 196
numChildren = 0

1.5.1.2. /brokers/topics

包含各Topic的Partition状态信息，此节点为临时Znode(EPHEMERAL)。

> ls /kafka/brokers/topics 
[__consumer_offsets, hello_test]
> ls /kafka/brokers/topics/hello_test
[partitions]
> get -s /kafka/brokers/topics/hello_test
{"removing_replicas": {},"partitions":{"1":[0,2],"0":[1,0]},			# 同步副本组BrokerId列表(ISR)"topic_id": "hQ7vPPgRQF2XEwhRSxO7nA","adding_replicas": {},"version": 3
}
cZxid = 0x200000077
ctime = Tue Aug 08 17:45:47 CST 2023
mZxid = 0x200000077
mtime = Tue Aug 08 17:45:47 CST 2023
pZxid = 0x200000078
cversion = 1
dataVersion = 0
aclVersion = 0
ephemeralOwner = 0x0
dataLength = 128
numChildren = 1> ls /kafka/brokers/topics/hello_test/partitions
[0, 1]
> ls /kafka/brokers/topics/hello_test/partitions/0 
[state]
> get -s /kafka/brokers/topics/hello_test/partitions/0/state 
{"controller_epoch": 3,						# Kafka集群中的中央控制器选举次数"leader": 1,											# 该Partition选举Leader的BrokerId"version": 1,											# 版本编号默认为1"leader_epoch": 3,								# 该Partition Leader选举次数"isr": [0,1]											# ISR列表
}
cZxid = 0x20000007c
ctime = Tue Aug 08 17:45:47 CST 2023
mZxid = 0x30000007b
mtime = Thu Aug 10 15:15:21 CST 2023
pZxid = 0x20000007c
cversion = 0
dataVersion = 4
aclVersion = 0
ephemeralOwner = 0x0
dataLength = 74
numChildren = 0

1.5.2. /consumers

每个Consumer都有唯一的id，用来标记消费者信息，该目录下仅展示使用ZK进行消费的 Consumers，如果之间指定Kafka节点进行消费，不会在此展示。

> ls /consumers
[console-consumer-84155, console-consumer-32194, wolves_report, console-consumer-9761, wolves_v2_gdt, console-consumer-63530, wolves, wolves_feedback, wolves_kuaishou, console-consumer-62629, ftrl1, console-consumer-56068, wolves_tuia]
> ls /consumers/wolves_report
[ids, owners, offsets]

注意事项：

使用kafka-console-consumer.sh命令创建的消费者并不会在Zookeeper的/consumers路径下创建消费者组信息，因为该命令使用的是新的消费者API，它使用了Kafka集群的元数据来管理消费者组信息，而不是使用Zookeeper。
新的消费者API不再需要将消费者组信息写入到Zookeeper中，因为Kafka集群本身就足够强大，可以自己管理消费者组信息。因此，使用kafka-console-consumer.sh创建的消费者不会在Zookeeper的/consumers路径下创建消费者组信息，而是在Kafka集群的元数据中进行管理。

Kafka的最新版本已经逐步淘汰了使用Zookeeper作为消费者元数据存储的方式，而是采用内部存储来管理消费者组信息。因此，新版本的Kafka已经不再支持使用--zookeeper参数来指定Zookeeper的连接信息。

如果你想要创建一个在Zookeeper的/consumers路径下的消费者，你需要使用旧的消费者API，而不是使用kafka-console-consumer.sh命令所使用的新的消费者API。

因此以下配置均来自旧版本Kafka。

1.5.2.1. /consumers/{groupId}/ids

> ls /consumers/wolves_report/ids
[wolves_report_node1.tc.wolves.dmp.com-1536837975646-39504764, wolves_report_node1.tc.wolves.dmp.com-1536838003051-182cc752,...]> get /consumers/wolves_report/ids/wolves_report_node1.tc.wolves.dmp.com-1536837975646-39504764						 # 旧版本下ZK命令get效果等于新版本ZK命令get -s
{"version":1,   									# 版本编号默认为1"subscription": 								# 订阅的Topic列表{"wolves-event":3      # Consumer中Topic消费者线程数},"pattern":"static",						# 模式"timestamp":"1537128878487"  		# Consumer启动时的时间戳
}
cZxid = 0x717782b21
ctime = Mon Sep 17 04:14:38 CST 2022
mZxid = 0x717782b21
mtime = Mon Sep 17 04:14:38 CST 2022
pZxid = 0x717782b21
cversion = 0
dataVersion = 0
aclVersion = 0
ephemeralOwner = 0x36324802b64ea62
dataLength = 94
numChildren = 0

1.5.2.2. /consumers/{groupId}/owner

> ls /consumers/wolves_report/owners
[wolves-event]   # topic> ls /consumers/wolves_report/owners/wolves-event
[0, 1, 2]       # partitionId> get /consumers/wolves_report/owners/wolves-event/0
wolves_report_node1.tc.wolves.dmp.com-1536837527210-1310d8f9-0
cZxid = 0x717782ba9
ctime = Mon Sep 17 04:14:40 CST 2022
mZxid = 0x717782ba9
mtime = Mon Sep 17 04:14:40 CST 2022
pZxid = 0x717782ba9
cversion = 0
dataVersion = 0
aclVersion = 0
ephemeralOwner = 0x26324802b69ea62
dataLength = 62
numChildren = 0

1.5.2.3. /consumers/{groupId}/offset

> ls /consumers/wolves_report/offsets
[wolves-event]    # topic> ls /consumers/wolves_report/offsets/wolves-event
[0, 1, 2]     		# partitionId> get /consumers/wolves_report/offsets/wolves-event/0
48800
cZxid = 0x200e97e36
ctime = Thu Nov 23 17:22:10 CST 2022
mZxid = 0x718665858
mtime = Fri Sep 21 12:02:39 CST 2022
pZxid = 0x200e97e36
cversion = 0
dataVersion = 11910567
aclVersion = 0
ephemeralOwner = 0x0
dataLength = 5
numChildren = 0

1.5.3. /admin

1.5.3.1. /admin/reassign_partitions

用以Partitions重分区，Reassign结束后会删除该目录。

> ls /admin/reassign_partitions
[]

1.5.3.2. /admin/preferred_replica_election

用以Partitions各副本Leader选举，副本选举结束后会删除该目录。

> ls /admin/reassign_partitions
[]

1.5.3.3. /admin/delete_topics

管理已删除的Topics，Broker启动时检查并确保存在。

> ls /admin/delete_topics
[]

1.5.4. /controller

存储Center controller中央控制器所在Kafka broker的信息。

> get -s /kafka/controller
{"version": 2,										# 版本编号默认为1"brokerid": 1,									# BrokerID"timestamp": "1691722592052",		# Broker中央控制器变更时的时间戳"kraftControllerEpoch": -1
}
cZxid = 0x4000000de
ctime = Fri Aug 11 10:56:32 CST 2023
mZxid = 0x4000000de
mtime = Fri Aug 11 10:56:32 CST 2023
pZxid = 0x4000000de
cversion = 0
dataVersion = 0
aclVersion = 0
ephemeralOwner = 0x10000042fff0009
dataLength = 80
numChildren = 0

1.5.5. /controller_epoch

Kafka集群中第一个Broker第一次启动时该值为1，后续只要集群中Center Controller中央控制器所在Broker变更或挂掉，就会重新选举新的Center Controller，每次Center Controller变更controller_epoch值就会自增1。

> get -s /kafka/controller_epoch
6
cZxid = 0x10000003f
ctime = Tue Aug 08 16:24:00 CST 2023
mZxid = 0x4000000de
mtime = Fri Aug 11 10:56:32 CST 2023
pZxid = 0x10000003f
cversion = 0
dataVersion = 6
aclVersion = 0
ephemeralOwner = 0x0
dataLength = 1
numChildren = 0

2、服务安装

官网下载安装包：https://kafka.apache.org/，根据需求下载对应版本即可，本文以最新版本为例做部署操作说明。

在这里插入图片描述

2.1. 单机部署

# 解压安装包并创建软链接
[root@master ~]# tar -xvf kafka_2.12-3.3.1.tgz -C /middleware/
[root@master ~]# cd /middleware/
[root@master middleware]# ln -s kafka_2.12-3.3.1/ kafka
[root@master middleware]# cd kafka
[root@master kafka]# ll
total 64
drwxr-xr-x 3 root root  4096 Sep 30 03:05 bin								# 可执行文件
drwxr-xr-x 3 root root  4096 Sep 30 03:05 config							# 配置文件
drwxr-xr-x 2 root root  4096 Nov 11 16:49 libs
-rw-rw-r-- 1 root root 14842 Sep 30 03:03 LICENSE
drwxr-xr-x 2 root root  4096 Sep 30 03:05 licenses
-rw-rw-r-- 1 root root 28184 Sep 30 03:03 NOTICE
drwxr-xr-x 2 root root  4096 Sep 30 03:05 site-docs
[root@master kafka]# cd config/
[root@master config]# ll
total 72
-rw-r--r-- 1 root root  906 Mar  3  2020 connect-console-sink.properties
-rw-r--r-- 1 root root  909 Mar  3  2020 connect-console-source.properties
-rw-r--r-- 1 root root 5321 Mar  3  2020 connect-distributed.properties
-rw-r--r-- 1 root root  883 Mar  3  2020 connect-file-sink.properties
-rw-r--r-- 1 root root  881 Mar  3  2020 connect-file-source.properties
-rw-r--r-- 1 root root 2247 Mar  3  2020 connect-log4j.properties
-rw-r--r-- 1 root root 1539 Mar  3  2020 connect-mirror-maker.properties
-rw-r--r-- 1 root root 2262 Mar  3  2020 connect-standalone.properties
-rw-r--r-- 1 root root 1221 Mar  3  2020 consumer.properties
-rw-r--r-- 1 root root 4675 Mar  3  2020 log4j.properties
-rw-r--r-- 1 root root 1925 Mar  3  2020 producer.properties
-rw-r--r-- 1 root root 6848 Mar  3  2020 server.properties					# 服务属性
-rw-r--r-- 1 root root 1032 Mar  3  2020 tools-log4j.properties
-rw-r--r-- 1 root root 1169 Mar  3  2020 trogdor.conf
-rw-r--r-- 1 root root 1205 Mar  3  2020 zookeeper.properties# 修改服务配置
[root@master kafka]# cd config/
[root@master kafka]# vim server.properties24 broker.id=0																# 指定broker id，集群内保持有且唯一34 listeners=PLAINTEXT://node1:9092										# 服务监听端口，默认909262 log.dirs=/middleware/kafka/data											# 日志存放路径67 num.partitions=1														# 分区数量，默认为1125 zookeeper.connect=master:2181,node1:2181,node2:2181/kafka				# ZK集群配置# ZK携带路径原因：携带路径之后kafka信息将保存在ZK中/kafka路径下，后续使用--zokeeper连接时就需要携带此路径，否则无法寻找相关数据[root@master kafka]# cd ../bin/
[root@master bin]# ll
total 140
-rwxr-xr-x 1 root root 1421 Mar  3  2020 connect-distributed.sh
-rwxr-xr-x 1 root root 1394 Mar  3  2020 connect-mirror-maker.sh
-rwxr-xr-x 1 root root 1418 Mar  3  2020 connect-standalone.sh
-rwxr-xr-x 1 root root  861 Mar  3  2020 kafka-acls.sh
-rwxr-xr-x 1 root root  873 Mar  3  2020 kafka-broker-api-versions.sh
-rwxr-xr-x 1 root root  864 Mar  3  2020 kafka-configs.sh
-rwxr-xr-x 1 root root  945 Mar  3  2020 kafka-console-consumer.sh			# consumer操作
-rwxr-xr-x 1 root root  944 Mar  3  2020 kafka-console-producer.sh			# producer操作
-rwxr-xr-x 1 root root  871 Mar  3  2020 kafka-consumer-groups.sh			# consumer groups操作
-rwxr-xr-x 1 root root  948 Mar  3  2020 kafka-consumer-perf-test.sh
-rwxr-xr-x 1 root root  871 Mar  3  2020 kafka-delegation-tokens.sh
-rwxr-xr-x 1 root root  869 Mar  3  2020 kafka-delete-records.sh
-rwxr-xr-x 1 root root  866 Mar  3  2020 kafka-dump-log.sh
-rwxr-xr-x 1 root root  870 Mar  3  2020 kafka-leader-election.sh
-rwxr-xr-x 1 root root  863 Mar  3  2020 kafka-log-dirs.sh
-rwxr-xr-x 1 root root  862 Mar  3  2020 kafka-mirror-maker.sh
-rwxr-xr-x 1 root root  886 Mar  3  2020 kafka-preferred-replica-election.sh
-rwxr-xr-x 1 root root  959 Mar  3  2020 kafka-producer-perf-test.sh
-rwxr-xr-x 1 root root  874 Mar  3  2020 kafka-reassign-partitions.sh
-rwxr-xr-x 1 root root  874 Mar  3  2020 kafka-replica-verification.sh
-rwxr-xr-x 1 root root 9633 Mar  3  2020 kafka-run-class.sh
-rwxr-xr-x 1 root root 1376 Mar  3  2020 kafka-server-start.sh				# 开启服务
-rwxr-xr-x 1 root root  997 Mar  3  2020 kafka-server-stop.sh				# 关闭服务
-rwxr-xr-x 1 root root  945 Mar  3  2020 kafka-streams-application-reset.sh
-rwxr-xr-x 1 root root  863 Mar  3  2020 kafka-topics.sh					# topic操作
-rwxr-xr-x 1 root root  958 Mar  3  2020 kafka-verifiable-consumer.sh
-rwxr-xr-x 1 root root  958 Mar  3  2020 kafka-verifiable-producer.sh
-rwxr-xr-x 1 root root 1722 Mar  3  2020 trogdor.sh
drwxr-xr-x 2 root root 4096 Mar  3  2020 windows
-rwxr-xr-x 1 root root  867 Mar  3  2020 zookeeper-security-migration.sh
-rwxr-xr-x 1 root root 1393 Mar  3  2020 zookeeper-server-start.sh
-rwxr-xr-x 1 root root 1001 Mar  3  2020 zookeeper-server-stop.sh
-rwxr-xr-x 1 root root  968 Mar  3  2020 zookeeper-shell.sh# 确认ZK服务正常启动
[root@master kafka]# sh /middleware/zookeeper/bin/zkCluster.sh start
[root@master kafka]# jps
6720 Jps
6301 QuorumPeerMain# 开启Kafka服务
[root@master kafka]# ./bin/kafka-server-start.sh 
USAGE: ./bin/kafka-server-start.sh [-daemon] server.properties [--override property=value]*
[root@master kafka]# ./bin/kafka-server-start.sh -daemon ./config/server.properties# 确认Kafka服务正常启动
[root@master kafka]# jps
7202 Jps
7084 Kafka
6301 QuorumPeerMain

2.2. 伪集群部署

# master配置
[root@master kafka_cluster]# cat kafka-1/config/server.properties | grep -Ev "^$|^#"
broker.id=0
listeners=PLAINTEXT://:9092
num.network.threads=3
num.io.threads=8
socket.send.buffer.bytes=102400
socket.receive.buffer.bytes=102400
socket.request.max.bytes=104857600
log.dirs=/kafka_cluster/kafka-1/kafka-logs
num.partitions=1
num.recovery.threads.per.data.dir=1
offsets.topic.replication.factor=1
transaction.state.log.replication.factor=1
transaction.state.log.min.isr=1
log.retention.hours=168
log.retention.check.interval.ms=300000
zookeeper.connect=localhost:2181/kafka
zookeeper.connection.timeout.ms=18000
group.initial.rebalance.delay.ms=0# node1配置
[root@master kafka_cluster]# cat kafka-2/config/server.properties | grep -Ev "^$|^#"
broker.id=1
listeners=PLAINTEXT://:9093
num.network.threads=3
num.io.threads=8
socket.send.buffer.bytes=102400
socket.receive.buffer.bytes=102400
socket.request.max.bytes=104857600
log.dirs=/kafka_cluster/kafka-2/kafka-logs
num.partitions=1
num.recovery.threads.per.data.dir=1
offsets.topic.replication.factor=1
transaction.state.log.replication.factor=1
transaction.state.log.min.isr=1
log.retention.hours=168
log.retention.check.interval.ms=300000
zookeeper.connect=localhost:2181/kafka
zookeeper.connection.timeout.ms=18000
group.initial.rebalance.delay.ms=0# node2配置
[root@master kafka_cluster]# cat kafka-3/config/server.properties | grep -Ev "^$|^#"
broker.id=2
listeners=PLAINTEXT://:9094
num.network.threads=3
num.io.threads=8
socket.send.buffer.bytes=102400
socket.receive.buffer.bytes=102400
socket.request.max.bytes=104857600
log.dirs=/kafka_cluster/kafka-3/kafka-logs
num.partitions=1
num.recovery.threads.per.data.dir=1
offsets.topic.replication.factor=1
transaction.state.log.replication.factor=1
transaction.state.log.min.isr=1
log.retention.hours=168
log.retention.check.interval.ms=300000
zookeeper.connect=localhost:2181/kafka
zookeeper.connection.timeout.ms=18000
group.initial.rebalance.delay.ms=0# 分别在kafka-1、kafka-2、kafka-3目录下开启服务
[root@master kafka_cluster]# ./kafka-1/bin/kafka-server-start.sh 
USAGE: ./bin/kafka-server-start.sh [-daemon] server.properties [--override property=value]*
[root@master kafka]# ./bin/kafka-server-start.sh -daemon ./config/server.properties

2.3. 集群操控脚本

[root@master kafka_cluster]# cat cluster.sh 
#!/bin/bashnode_list=`ls -l /kafka_cluster/ | awk '{print$9}' | grep kafka-`case ${1:-help} in
"start")for i in ${node_list[@]}dosu redhat -c "sh /kafka_cluster/$i/bin/kafka-server-start.sh -daemon /kafka_cluster/$i/config/server.properties"echo -e "\033[32m$i Kafka service is STARTED!\033[0m"done;;
"stop")for i in ${node_list[@]}dosu redhat -c "sh /kafka_cluster/$i/bin/kafka-server-stop.sh"echo -e "\033[31m$i Kafka service is STOPPED!\033[0m"done;;
*)echo -e "\033[31mInput ERROR,Please input \"start/stop!\"\033[0m";;
esac# 集群操作脚本使用测试
[root@master kafka_cluster]# chmod 755 cluster.sh
[root@master kafka_cluster]# ln -s /zk_cluster/cluster.sh zk_cluster.sh start
[root@master kafka_cluster]# ./zk_cluster.sh start
# 开启
[root@master kafka_cluster]# ./cluster.sh start
kafka-1 Kafka service is STARTED!
kafka-2 Kafka service is STARTED!
kafka-3 Kafka service is STARTED!# 关闭（先关闭Kafka，等进程全部退出后方可关闭ZK服务，否则Kafka将一直存在，直到被kill -9杀死进程）
[root@master kafka_cluster]# ./cluster.sh stop
kafka-1 Kafka service is STOPPED!
kafka-2 Kafka service is STOPPED!
kafka-3 Kafka service is STOPPED!# 进程验证
[root@master kafka_cluster]# jps
1459988 Kafka
1459253 Kafka
1460099 Jps
1453443 QuorumPeerMain
1459617 Kafka
1453374 QuorumPeerMain
1453529 QuorumPeerMain# 一键修改集群环境变量
[root@master kafka_cluster]# sed -i '$a # Kafka' /etc/profile && sed -i '$a export KAFKA_HOME=/kafka_cluster/kafka-1' /etc/profile && sed -i '$a export PATH=$KAFKA_HOME/bin/:$PATH' /etc/profile && source /etc/profile

2.5. 客户端命令行操作

Kafka可执行目录下存在多个脚本控制文件，常用的有topic、producer、consumer、consumer group四种，其他仅做了解即可。

[root@master kafka_cluster]# cd kafka-1/bin/
[root@master bin]# ll
total 172
-rwxr-xr-x 1 redhat redhat  1423 Jun  5 17:03 connect-distributed.sh
-rwxr-xr-x 1 redhat redhat  1396 Jun  5 17:03 connect-mirror-maker.sh
-rwxr-xr-x 1 redhat redhat  1420 Jun  5 17:03 connect-standalone.sh
-rwxr-xr-x 1 redhat redhat   861 Jun  5 17:03 kafka-acls.sh
-rwxr-xr-x 1 redhat redhat   873 Jun  5 17:03 kafka-broker-api-versions.sh				# 用于验证不同版本的Broker和Consumer之间的适配行
-rwxr-xr-x 1 redhat redhat   871 Jun  5 17:03 kafka-cluster.sh
-rwxr-xr-x 1 redhat redhat   864 Jun  5 17:03 kafka-configs.sh													# 修改配置，支持操作主题、broker、用户和客户端这3个类型的配置
-rwxr-xr-x 1 redhat redhat   945 Jun  5 17:03 kafka-console-consumer.sh					# 通过控制台订阅并接收消息
-rwxr-xr-x 1 redhat redhat   944 Jun  5 17:03 kafka-console-producer.sh					# 通过控制台发送消息
-rwxr-xr-x 1 redhat redhat   871 Jun  5 17:03 kafka-consumer-groups.sh					# kafka消费者组控制，支持查看与设置offset等操作
-rwxr-xr-x 1 redhat redhat   959 Jun  5 17:03 kafka-consumer-perf-test.sh				# 用于对消费消息的性能做测试
-rwxr-xr-x 1 redhat redhat   882 Jun  5 17:03 kafka-delegation-tokens.sh
-rwxr-xr-x 1 redhat redhat   869 Jun  5 17:03 kafka-delete-records.sh
-rwxr-xr-x 1 redhat redhat   866 Jun  5 17:03 kafka-dump-log.sh							# 用来查看消息文件的数据，--file参数为将数据读取到一个文件中，包含了消息集合位移范围、数量、创建时间、压缩算法等信息，如果想看每一条的具体信息，可以通过在命令之后添--deep-iteration参数
-rwxr-xr-x 1 redhat redhat   877 Jun  5 17:03 kafka-e2e-latency.sh
-rwxr-xr-x 1 redhat redhat   863 Jun  5 17:03 kafka-features.sh
-rwxr-xr-x 1 redhat redhat   865 Jun  5 17:03 kafka-get-offsets.sh						# 查看当前某个topic的offset位置
-rwxr-xr-x 1 redhat redhat   867 Jun  5 17:03 kafka-jmx.sh															# 修改JMX
-rwxr-xr-x 1 redhat redhat   870 Jun  5 17:03 kafka-leader-election.sh					# Leader分区重新选举
-rwxr-xr-x 1 redhat redhat   863 Jun  5 17:03 kafka-log-dirs.sh
-rwxr-xr-x 1 redhat redhat   881 Jun  5 17:03 kafka-metadata-quorum.sh
-rwxr-xr-x 1 redhat redhat   873 Jun  5 17:03 kafka-metadata-shell.sh
-rwxr-xr-x 1 redhat redhat   862 Jun  5 17:03 kafka-mirror-maker.sh
-rwxr-xr-x 1 redhat redhat   959 Jun  5 17:03 kafka-producer-perf-test.sh				# 用于对生产消息的性能做测试
-rwxr-xr-x 1 redhat redhat   874 Jun  5 17:03 kafka-reassign-partitions.sh				# 分区重分配工具
-rwxr-xr-x 1 redhat redhat   874 Jun  5 17:03 kafka-replica-verification.sh
-rwxr-xr-x 1 redhat redhat 10884 Jun  5 17:03 kafka-run-class.sh
-rwxr-xr-x 1 redhat redhat  1376 Jun  5 17:03 kafka-server-start.sh						# 启动Kafka服务
-rwxr-xr-x 1 redhat redhat  1361 Jun  5 17:03 kafka-server-stop.sh						# 停止Kafka服务
-rwxr-xr-x 1 redhat redhat   860 Jun  5 17:03 kafka-storage.sh
-rwxr-xr-x 1 redhat redhat   956 Jun  5 17:03 kafka-streams-application-reset.sh
-rwxr-xr-x 1 redhat redhat   863 Jun  5 17:03 kafka-topics.sh							# 主题管理工具，创建、查看、修改和删除等操作
-rwxr-xr-x 1 redhat redhat   879 Jun  5 17:03 kafka-transactions.sh
-rwxr-xr-x 1 redhat redhat   958 Jun  5 17:03 kafka-verifiable-consumer.sh
-rwxr-xr-x 1 redhat redhat   958 Jun  5 17:03 kafka-verifiable-producer.sh
-rwxr-xr-x 1 redhat redhat  1714 Jun  5 17:03 trogdor.sh
drwxr-xr-x 2 redhat redhat  4096 Jun  5 17:03 windows
-rwxr-xr-x 1 redhat redhat   867 Jun  5 17:03 zookeeper-security-migration.sh
-rwxr-xr-x 1 redhat redhat  1393 Jun  5 17:03 zookeeper-server-start.sh					# kafka自带zk的服务控制工具
-rwxr-xr-x 1 redhat redhat  1366 Jun  5 17:03 zookeeper-server-stop.sh
-rwxr-xr-x 1 redhat redhat  1019 Jun  5 17:03 zookeeper-shell.sh

2.5.1. Topic

获取参数帮助信息方法：

[root@master bin]# sh kafka-topics.sh --help

常见参数说明：

–bootstrap-server <String: server to connect to>：连接Kafka Broker主机名称和端口（高版本）；
–zookeeper <String: hosts>：连接ZK服务和端口（低版本）；
–topic <String: topic> ：操作的Topic名称；
–create：创建；
–delete：删除；
–alter：修改；
–list：列表查看；
–describe：查看详细信息；
–partitions <Integer: # of partitions>：设置分区数（分区数目客户端命令行操作只能增加不能减少）；
–replication-factor <Integer replication factor>：设置副本数；
–config <String: name=value>：修改服务配置。

2.5.2. Producer

获取参数帮助信息方法：

[root@master bin]# sh kafka-console-producer.sh --help

常见参数说明：

–bootstrap-server <String: server to connect to>：连接Kafka Broker主机名称和端口（高版本）；
–bootstrap-server <String: server toconnect to>：连接Kafka Broker主机名称和端口（低版本）；
–producer.config <String: config file>：生产者配置文件关联；
–zookeeper <String: hosts>：连接ZK服务和端口（低版本）；
–topic <String: topic> ：操作的Topic名称；

2.5.3. Consumer

获取参数帮助信息方法：

[root@master bin]# sh kafka-console-consumer.sh --help

常见参数说明：

–bootstrap-server <String: server to connect to>：连接Kafka Broker主机名称和端口（高版本）；
–zookeeper <String: hosts>：连接ZK服务和端口（低版本）；
–consumer.config <String: config file>：消费者配置文件关联；
–topic <String: topic> ：操作的Topic名称；
–from-beginning：消费历史信息；
–whitelist <String: Java regex(String)>：白名单；
–partition <Integer: partition>：指定分区；
–offset <String: consume offset>：指定offset（最新为latest）；
–max-messages <Integer: num_messages>：最大消费数量；

2.5.4. Consumer group

获取参数帮助信息方法：

[root@master bin]# sh kafka-consumer-groups.sh --help

常见参数说明：

–bootstrap-server <String: server to connect to>：连接Kafka Broker主机名称和端口；
–delete：删除消费者组；
–delete-offsets：删除到指定offset；
–describe：查看详细信息；
–execute：立刻执行；
–group <String: consumer group>：指定组名；
–list：列表查看；
–offsets：指定offset（最新为latest）；
–reset-offsets：重置offset到某个时刻；
–to-datetime <String: datetime>：恢复到指定时间的offset，时间格式：YYYY-MM-DDTHH:mm:SS.sss；
–by-duration <String: duration>：恢复到指定时间的offset，时间格式为：PnDTnHnMnS；
–to-earliest：恢复到当前保留的最早offset；
–to-latest：恢复到最新的offset；
–to-offset <Long: offset>：恢复指定的特殊offset；
–topic <String: topic>：指定topic；

2.5.5. 操作案例

2.5.5.1. Topic

# 查看当前已有的Topic（__consumer_offsets为消费者offset存储topic，详见本文1.4.5.2章节内容）
[root@master kafka_cluster]# sh kafka-1/bin/kafka-topics.sh --bootstrap-server 127.0.0.1:9092 --list
__consumer_offsets# 创建一个名称为hello_test，分区为5，副本为2的Topic
[root@master kafka_cluster]# sh kafka-1/bin/kafka-topics.sh --bootstrap-server 127.0.0.1:9092 --create --topic hello_test --partitions 5 --replication-factor 2
WARNING: Due to limitations in metric names, topics with a period ('.') or underscore ('_') could collide. To avoid issues it is best to use either, but not both.
# 注意：带有句号('.')或下划线('_')的主题可能会发生冲突。为了避免问题，最好使用其中之一，但不要同时使用
Created topic hello_test.
[root@master kafka_cluster]# sh kafka-1/bin/kafka-topics.sh --bootstrap-server 127.0.0.1:9092 --list
__consumer_offsets
hello_test
[root@master kafka_cluster]# sh kafka-1/bin/kafka-topics.sh --bootstrap-server 127.0.0.1:9092 --topic hello_test --describe
Topic: hello_test       TopicId: uo-PiyMRQAOQhGumh6Dmpg PartitionCount: 5       ReplicationFactor: 2    Configs: Topic: hello_test       Partition: 0    Leader: 1       Replicas: 1,2   Isr: 1,2Topic: hello_test       Partition: 1    Leader: 0       Replicas: 0,1   Isr: 0,1Topic: hello_test       Partition: 2    Leader: 2       Replicas: 2,0   Isr: 2,0Topic: hello_test       Partition: 3    Leader: 1       Replicas: 1,0   Isr: 1,0Topic: hello_test       Partition: 4    Leader: 0       Replicas: 0,2   Isr: 0,2
# 表头介绍：
# Topic：主题名称
# TopicId：主题ID
# PartitionCount：分区总数
# ReplicationFactor：副本数
# Configs：主题配置
# 数据列：主题名称、分区编号、Leader分区在哪个Broker、副本分布在哪个Broker、ISR列表# 更新Topic分区为7
[root@master kafka_cluster]# sh kafka-1/bin/kafka-topics.sh --bootstrap-server 127.0.0.1:9092 --alter --topic hello_test --partitions 7
[root@master kafka_cluster]# sh kafka-1/bin/kafka-topics.sh --bootstrap-server 127.0.0.1:9092 --topic hello_test --describe
Topic: hello_test       TopicId: uo-PiyMRQAOQhGumh6Dmpg PartitionCount: 7       ReplicationFactor: 2    Configs: Topic: hello_test       Partition: 0    Leader: 1       Replicas: 1,2   Isr: 1,2Topic: hello_test       Partition: 1    Leader: 0       Replicas: 0,1   Isr: 0,1Topic: hello_test       Partition: 2    Leader: 2       Replicas: 2,0   Isr: 2,0Topic: hello_test       Partition: 3    Leader: 1       Replicas: 1,0   Isr: 1,0Topic: hello_test       Partition: 4    Leader: 0       Replicas: 0,2   Isr: 0,2Topic: hello_test       Partition: 5    Leader: 0       Replicas: 0,2   Isr: 0,2Topic: hello_test       Partition: 6    Leader: 1       Replicas: 1,2   Isr: 1,2# 删除前面创建好的Topic
[root@master kafka_cluster]# sh kafka-1/bin/kafka-topics.sh --bootstrap-server 127.0.0.1:9092 --delete --topic hello_test
[root@master kafka_cluster]# sh kafka-1/bin/kafka-topics.sh --bootstrap-server 127.0.0.1:9092 --list
__consumer_offsets

2.5.5.2. Producer + Consumer

# 准备环境（3个终端窗口，创建关联topic）
[root@master kafka_cluster]# sh kafka-1/bin/kafka-topics.sh --bootstrap-server 127.0.0.1:9092 --create --topic test001 --partitions 3 --replication-factor 2
Created topic test001.# 1号窗口代表producer，先输入一些数据
[root@master kafka_cluster]# sh kafka-1/bin/kafka-console-producer.sh --bootstrap-server 127.0.0.1:9092 --topic test001
>111
>222
>333
>444
># 2号窗口代表consumer，此时连接后无任何返回
[root@master kafka_cluster]# sh kafka-1/bin/kafka-console-consumer.sh --bootstrap-server 127.0.0.1:9092 --topic test001# 在1号窗口继续输入
[root@master kafka_cluster]# sh kafka-1/bin/kafka-console-producer.sh --bootstrap-server 127.0.0.1:9092 --topic test001
>111
>222
>333
>444															# consumer连接前输入数据位置
>
>555
>666
>777
>888
># 2号窗口自动输出（不包含连接前数据，如测试内数据111-444）
[root@master kafka_cluster]# sh kafka-1/bin/kafka-console-consumer.sh --bootstrap-server 127.0.0.1:9092 --topic test001555
666
777
888# 使用3号窗口查看历史数据，需要携带参数--from-beginning
[root@master kafka_cluster]# sh kafka-1/bin/kafka-console-consumer.sh --bootstrap-server 127.0.0.1:9092 --topic test001 --from-beginning
111
222
333
444555
666
777
888
# 此时不要关闭3号窗口，保留consumer存在，继续进行Consumer group相关操作

2.5.5.3. Consumer group

# 查看消费者组
[root@master kafka_cluster]# sh kafka-1/bin/kafka-consumer-groups.sh --bootstrap-server 127.0.0.1:9092 --list
console-consumer-11605# 查看详细信息
[root@master kafka_cluster]# sh kafka-1/bin/kafka-consumer-groups.sh --bootstrap-server 127.0.0.1:9092 --group console-consumer-11605  --describeGROUP                  TOPIC           PARTITION  CURRENT-OFFSET  LOG-END-OFFSET  LAG             CONSUMER-ID                                           HOST            CLIENT-ID
console-consumer-11605 test001         0          -               0               -               console-consumer-401f8ac4-932d-4a18-97ea-45677d9d2f2d /9.134.244.180  console-consumer
console-consumer-11605 test001         1          -               9               -               console-consumer-401f8ac4-932d-4a18-97ea-45677d9d2f2d /9.134.244.180  console-consumer
console-consumer-11605 test001         2          -               0               -               console-consumer-401f8ac4-932d-4a18-97ea-45677d9d2f2d /9.134.244.180  console-consumer
# 表头介绍：
# GROUP：消费者组的名称
# TOPIC：消费者组订阅的主题名称
# PARTITION：主题的分区编号
# CURRENT-OFFSET：消费者组当前的偏移量（offset），即该分区下一个将要被消费的消息的偏移量
# LOG-END-OFFSET：该分区最新一条消息的偏移量
# LAG：消费者组滞后的消息数量，即当前的偏移量与最新一条消息的偏移量之间的差值
# CONSUMER-ID：消费者客户端的唯一标识符
# HOST：消费者客户端所在的主机名称或 IP 地址

2.5.4. 分区与副本调整

# 准备topic
[root@master kafka_cluster]# sh kafka-1/bin/kafka-topics.sh --bootstrap-server 127.0.0.1:9092 --create --topic hello_test --partitions 2 --replication-factor 2
WARNING: Due to limitations in metric names, topics with a period ('.') or underscore ('_') could collide. To avoid issues it is best to use either, but not both.
Created topic hello_test.
[root@master kafka_cluster]# ./kafka-1/bin/kafka-topics.sh --bootstrap-server 127.0.0.1:9092 --topic hello_test --describe
Topic: hello_test       TopicId: hQ7vPPgRQF2XEwhRSxO7nA PartitionCount: 2       ReplicationFactor: 2    Configs: Topic: hello_test       Partition: 0    Leader: 0       Replicas: 1,0   Isr: 0,1Topic: hello_test       Partition: 1    Leader: 0       Replicas: 0,2   Isr: 0,2# 编辑需要修改的topic（注意文件内容为json格式）
[root@master kafka_cluster]# vim topic_change.json
{"topics":[{"topic":"hello_test"}],"version":1}# 使用重新分配分区脚本生成分配计划
[root@master kafka_cluster]# ./kafka-1/bin/kafka-reassign-partitions.sh --bootstrap-server 127.0.0.1:9092 --topics-to-move-json-file ./topic_change.json --generate --broker-list "0,1,2"
Current partition replica assignment									# 当前分区配置
{"version":1,"partitions":[{"topic":"hello_test","partition":0,"replicas":[1,0],"log_dirs":["any","any"]},{"topic":"hello_test","partition":1,"replicas":[0,2],"log_dirs":["any","any"]}]}Proposed partition reassignment configuration					# 推荐的分区配置
{"version":1,"partitions":[{"topic":"hello_test","partition":0,"replicas":[1,2],"log_dirs":["any","any"]},{"topic":"hello_test","partition":1,"replicas":[2,0],"log_dirs":["any","any"]}]}# 将推荐的分配计划保存在本地新文件内
[root@master kafka_cluster]# vim replication-factor.json 
{"version":1,"partitions":[{"topic":"hello_test","partition":0,"replicas":[1,2],"log_dirs":["any","any"]},{"topic":"hello_test","partition":1,"replicas":[2,0],"log_dirs":["any","any"]}]}# 使用重新分配分区脚本执行分配计划
[root@master kafka_cluster]# ./kafka-1/bin/kafka-reassign-partitions.sh --bootstrap-server 127.0.0.1:9092 --reassignment-json-file ./replication-factor.json --execute
Current partition replica assignment{"version":1,"partitions":[{"topic":"hello_test","partition":0,"replicas":[1,0],"log_dirs":["any","any"]},{"topic":"hello_test","partition":1,"replicas":[0,2],"log_dirs":["any","any"]}]}Save this to use as the --reassignment-json-file option during rollback
Successfully started partition reassignments for hello_test-0,hello_test-1			# 成功启动分区标识# 验证分配计划是否执行成功
[root@master kafka_cluster]# ./kafka-1/bin/kafka-reassign-partitions.sh --bootstrap-server 127.0.0.1:9092 --reassignment-json-file ./replication-factor.json --verify
Status of partition reassignment:
Reassignment of partition hello_test-0 is completed.														# 重新分配分区完成标识
Reassignment of partition hello_test-1 is completed.Clearing broker-level throttles on brokers 0,1,2
Clearing topic-level throttles on topic hello_test# 查看topic详情
[root@master kafka_cluster]# ./kafka-1/bin/kafka-topics.sh --bootstrap-server 127.0.0.1:9092 --topic hello_test --describe
Topic: hello_test       TopicId: hQ7vPPgRQF2XEwhRSxO7nA PartitionCount: 2       ReplicationFactor: 2    Configs: Topic: hello_test       Partition: 0    Leader: 1       Replicas: 1,2   Isr: 1,2Topic: hello_test       Partition: 1    Leader: 0       Replicas: 2,0   Isr: 0,2

2.5.4.1. 分区扩容

[root@master kafka_cluster]# ./kafka-1/bin/kafka-topics.sh --bootstrap-server 127.0.0.1:9092 --topic hello_test --describe
Topic: hello_test       TopicId: hQ7vPPgRQF2XEwhRSxO7nA PartitionCount: 2       ReplicationFactor: 2    Configs: Topic: hello_test       Partition: 0    Leader: 1       Replicas: 1,2   Isr: 1,2Topic: hello_test       Partition: 1    Leader: 0       Replicas: 2,0   Isr: 0,2# 使用topic脚本可以直接扩容分区，但不支持缩容（缩容需要使用分配计划修改）
[root@master kafka_cluster]# ./kafka-1/bin/kafka-topics.sh --alter --bootstrap-server 127.0.0.1:9092 --topic hello_test --partitions 8
[root@master kafka_cluster]# ./kafka-1/bin/kafka-topics.sh --bootstrap-server 127.0.0.1:9092 --topic hello_test --describe
Topic: hello_test       TopicId: hQ7vPPgRQF2XEwhRSxO7nA PartitionCount: 8       ReplicationFactor: 2    Configs: Topic: hello_test       Partition: 0    Leader: 1       Replicas: 1,2   Isr: 1,2Topic: hello_test       Partition: 1    Leader: 0       Replicas: 2,0   Isr: 0,2Topic: hello_test       Partition: 2    Leader: 0       Replicas: 0,2   Isr: 0,2Topic: hello_test       Partition: 3    Leader: 1       Replicas: 1,2   Isr: 1,2Topic: hello_test       Partition: 4    Leader: 2       Replicas: 2,0   Isr: 2,0Topic: hello_test       Partition: 5    Leader: 0       Replicas: 0,1   Isr: 0,1Topic: hello_test       Partition: 6    Leader: 1       Replicas: 1,0   Isr: 1,0Topic: hello_test       Partition: 7    Leader: 2       Replicas: 2,1   Isr: 2,1

2.5.4.2. 副本扩容

# 生成分配计划
[root@master kafka_cluster]# ./kafka-1/bin/kafka-reassign-partitions.sh --bootstrap-server 127.0.0.1:9092 --topics-to-move-json-file ./topic_change.json --generate --broker-list "1,2"
Current partition replica assignment
{"version":1,"partitions":[{"topic":"hello_test","partition":0,"replicas":[1,2],"log_dirs":["any","any"]},{"topic":"hello_test","partition":1,"replicas":[2,0],"log_dirs":["any","any"]},{"topic":"hello_test","partition":2,"replicas":[0,2],"log_dirs":["any","any"]},{"topic":"hello_test","partition":3,"replicas":[1,2],"log_dirs":["any","any"]},{"topic":"hello_test","partition":4,"replicas":[2,0],"log_dirs":["any","any"]},{"topic":"hello_test","partition":5,"replicas":[0,1],"log_dirs":["any","any"]},{"topic":"hello_test","partition":6,"replicas":[1,0],"log_dirs":["any","any"]},{"topic":"hello_test","partition":7,"replicas":[2,1],"log_dirs":["any","any"]}]}Proposed partition reassignment configuration
{"version":1,"partitions":[{"topic":"hello_test","partition":0,"replicas":[2,1],"log_dirs":["any","any"]},{"topic":"hello_test","partition":1,"replicas":[1,2],"log_dirs":["any","any"]},{"topic":"hello_test","partition":2,"replicas":[2,1],"log_dirs":["any","any"]},{"topic":"hello_test","partition":3,"replicas":[1,2],"log_dirs":["any","any"]},{"topic":"hello_test","partition":4,"replicas":[2,1],"log_dirs":["any","any"]},{"topic":"hello_test","partition":5,"replicas":[1,2],"log_dirs":["any","any"]},{"topic":"hello_test","partition":6,"replicas":[2,1],"log_dirs":["any","any"]},{"topic":"hello_test","partition":7,"replicas":[1,2],"log_dirs":["any","any"]}]}# 保存分配计划
[root@master kafka_cluster]# vim replication-factor.json  
{"version":1,"partitions":[{"topic":"hello_test","partition":0,"replicas":[2,1,0],"log_dirs":["any","any","any"]},{"topic":"hello_test","partition":1,"replicas":[1,2,0],"log_dirs":["any","any","any"]},{"topic":"hello_test","partition":2,"replicas":[2,1,0],"log_dirs":["any","any","any"]},{"topic":"hello_test","partition":3,"replicas":[1,2,0],"log_dirs":["any","any","any"]},{"topic":"hello_test","partition":4,"replicas":[2,1,0],"log_dirs":["any","any","any"]},{"topic":"hello_test","partition":5,"replicas":[1,2,0],"log_dirs":["any","any","any"]},{"topic":"hello_test","partition":6,"replicas":[2,1,0],"log_dirs":["any","any","any"]},{"topic":"hello_test","partition":7,"replicas":[1,2,0],"log_dirs":["any","any","any"]}]}# 立即执行
[root@master kafka_cluster]# ./kafka-1/bin/kafka-reassign-partitions.sh --bootstrap-server 127.0.0.1:9092 --reassignment-json-file ./replication-factor.json --execute
Current partition replica assignment{"version":1,"partitions":[{"topic":"hello_test","partition":0,"replicas":[1,2],"log_dirs":["any","any"]},{"topic":"hello_test","partition":1,"replicas":[2,0],"log_dirs":["any","any"]},{"topic":"hello_test","partition":2,"replicas":[0,2],"log_dirs":["any","any"]},{"topic":"hello_test","partition":3,"replicas":[1,2],"log_dirs":["any","any"]},{"topic":"hello_test","partition":4,"replicas":[2,0],"log_dirs":["any","any"]},{"topic":"hello_test","partition":5,"replicas":[0,1],"log_dirs":["any","any"]},{"topic":"hello_test","partition":6,"replicas":[1,0],"log_dirs":["any","any"]},{"topic":"hello_test","partition":7,"replicas":[2,1],"log_dirs":["any","any"]}]}Save this to use as the --reassignment-json-file option during rollback
Successfully started partition reassignments for hello_test-0,hello_test-1,hello_test-2,hello_test-3,hello_test-4,hello_test-5,hello_test-6,hello_test-7# 验证结果
[root@master kafka_cluster]# ./kafka-1/bin/kafka-reassign-partitions.sh --bootstrap-server 127.0.0.1:9092 --reassignment-json-file ./replication-factor.json --verify
Status of partition reassignment:
Reassignment of partition hello_test-0 is completed.
Reassignment of partition hello_test-1 is completed.
Reassignment of partition hello_test-2 is completed.
Reassignment of partition hello_test-3 is completed.
Reassignment of partition hello_test-4 is completed.
Reassignment of partition hello_test-5 is completed.
Reassignment of partition hello_test-6 is completed.
Reassignment of partition hello_test-7 is completed.Clearing broker-level throttles on brokers 0,1,2
Clearing topic-level throttles on topic hello_test# 查看详情
[root@master kafka_cluster]# ./kafka-1/bin/kafka-topics.sh --bootstrap-server 127.0.0.1:9092 --topic hello_test --describeTopic: hello_test       TopicId: hQ7vPPgRQF2XEwhRSxO7nA PartitionCount: 8       ReplicationFactor: 3    Configs:         Topic: hello_test       Partition: 0    Leader: 1       Replicas: 2,1,0 Isr: 1,2,0        Topic: hello_test       Partition: 1    Leader: 0       Replicas: 1,2,0 Isr: 0,2,1Topic: hello_test       Partition: 2    Leader: 0       Replicas: 2,1,0 Isr: 0,2,1Topic: hello_test       Partition: 3    Leader: 1       Replicas: 1,2,0 Isr: 1,2,0Topic: hello_test       Partition: 4    Leader: 2       Replicas: 2,1,0 Isr: 2,0,1Topic: hello_test       Partition: 5    Leader: 0       Replicas: 1,2,0 Isr: 0,1,2Topic: hello_test       Partition: 6    Leader: 1       Replicas: 2,1,0 Isr: 1,0,2Topic: hello_test       Partition: 7    Leader: 2       Replicas: 1,2,0 Isr: 2,1,0

2.5.5. 消息积压清理

使用Kafka自带的测试工具进行测试。

# 创建一个测试topic
[root@master kafka_cluster]# sh kafka-1/bin/kafka-topics.sh --bootstrap-server 127.0.0.1:9092 --create --topic test --partitions 5 --replication-factor 2
Created topic test.# 生产者
[root@master kafka_cluster]# sh kafka-1/bin/kafka-producer-perf-test.sh --topic test --num-records=100000000 --producer-props bootstrap.servers=127.0.0.1:9092 batch.size=10000 --throughput -1 --record-size 100
1502928 records sent, 300585.6 records/sec (28.67 MB/sec), 566.8 ms avg latency, 1350.0 ms max latency.
～
100000000 records sent, 555632.726768 records/sec (52.99 MB/sec), 538.13 ms avg latency, 3616.00 ms max latency, 489 ms 50th, 824 ms 95th, 1240 ms 99th, 3300 ms 99.9th.																									# 传输完成标识，展示了每秒发送的消息数、吞吐量、平均延时，以及几个分位数，重点关注末尾的分位数，3300 ms 99.9th表示99.9%的消息延时都在3300 ms之内
# --num-records=100000000:将要发送的消息数量
# batch.size=10000:批处理大小
# --throughput -1:设置生产者的期望吞吐量。"-1"表示生产者将尽可能快地发送消息
# --record-size 100:每条消息的大小为100字节# 消费者
[root@master kafka_cluster]# sh kafka-1/bin/kafka-consumer-perf-test.sh --topic test --broker-list 127.0.0.1:9092 --messages=100000000 --num-fetch-threads 1 --fetch-size=1000
WARNING: option [threads] and [num-fetch-threads] have been deprecated and will be ignored by the test
start.time, end.time, data.consumed.in.MB, MB.sec, data.consumed.in.nMsg, nMsg.sec, rebalance.time.ms, fetch.time.ms, fetch.MB.sec, fetch.nMsg.sec
2023-08-30 19:33:27:781, 2023-08-30 19:36:27:457, 9536.7437, 53.0774, 100000014, 556557.4367, 351, 179325, 53.1813, 557646.8089																																														# 完成标识
# --messages=100000000:指定测试消息的总数
# --num-fetch-threads 1:指定拉取消息的线程数为1个
# --fetch-size=1000:指定每次拉取消息的大小为1000字节# 查看消息积压
[root@master kafka_cluster]# sh kafka-1/bin/kafka-consumer-groups.sh  --bootstrap-server 127.0.0.1:9092 --list
perf-consumer-63840
[root@master kafka_cluster]# sh kafka-1/bin/kafka-consumer-groups.sh  --bootstrap-server 127.0.0.1:9092 --describe --group perf-consumer-99520GROUP               TOPIC           PARTITION  CURRENT-OFFSET  LOG-END-OFFSET  LAG             CONSUMER-ID                                               HOST            CLIENT-ID
perf-consumer-99520 test            0          3596220         4426920         830700          perf-consumer-client-f7810e67-2129-44e4-aabd-1f1789119c04 /9.134.244.180  perf-consumer-client
perf-consumer-99520 test            1          3104236         4129066         1024830         perf-consumer-client-f7810e67-2129-44e4-aabd-1f1789119c04 /9.134.244.180  perf-consumer-client
perf-consumer-99520 test            4          3104522         4129172         1024650         perf-consumer-client-f7810e67-2129-44e4-aabd-1f1789119c04 /9.134.244.180  perf-consumer-client
perf-consumer-99520 test            3          3596115         4426905         830790          perf-consumer-client-f7810e67-2129-44e4-aabd-1f1789119c04 /9.134.244.180  perf-consumer-client
perf-consumer-99520 test            2          5437555         5465005         27450           perf-consumer-client-f7810e67-2129-44e4-aabd-1f1789119c04 /9.134.244.180  perf-consumer-client
# LAG越大积压越多# 恢复到最新的offset，LAG = 0，未消费的数据将直接被放弃消费，从最新offset继续开始进行消费
[root@master kafka_cluster]# sh kafka-1/bin/kafka-consumer-groups.sh --bootstrap-server 127.0.0.1:9092 --group perf-consumer-99520 --reset-offsets --topic test --to-latest --executeGROUP                          TOPIC                          PARTITION  NEW-OFFSET     
perf-consumer-99520            test                           0          25377165       
perf-consumer-99520            test                           1          27216340       
perf-consumer-99520            test                           4          27214992       
perf-consumer-99520            test                           3          25377341       
perf-consumer-99520            test                           2          32609516       
[root@master kafka_cluster]# sh kafka-1/bin/kafka-consumer-groups.sh  --bootstrap-server 127.0.0.1:9092 --describe --group perf-consumer-99520Consumer group 'perf-consumer-99520' has no active members.GROUP               TOPIC           PARTITION  CURRENT-OFFSET  LOG-END-OFFSET  LAG             CONSUMER-ID     HOST            CLIENT-ID
perf-consumer-99520 test            0          25377165        25377165        0               -               -               -
perf-consumer-99520 test            1          27216340        27216340        0               -               -               -
perf-consumer-99520 test            4          27214992        27214992        0               -               -               -
perf-consumer-99520 test            3          25377341        25377341        0               -               -               -
perf-consumer-99520 test            2          32609516        32609516        0               -               -               -

2.5.6. 重选选举Leader主分区

[root@master kafka_cluster]# sh kafka-1/bin/kafka-topics.sh --bootstrap-server 127.0.0.1:9092 --describe --topic test
Topic: test     TopicId: 2_bqk7HcTzWIDNAqkNondQ PartitionCount: 5       ReplicationFactor: 2    Configs: Topic: test     Partition: 0    Leader: 1       Replicas: 1,2   Isr: 1,2Topic: test     Partition: 1    Leader: 0       Replicas: 0,1   Isr: 0,1Topic: test     Partition: 2    Leader: 2       Replicas: 2,0   Isr: 2,0Topic: test     Partition: 3    Leader: 1       Replicas: 1,0   Isr: 1,0Topic: test     Partition: 4    Leader: 0       Replicas: 0,2   Isr: 0,2# 指定topic与partition
[root@master kafka_cluster]# sh kafka-1/bin/kafka-leader-election.sh --bootstrap-server 127.0.0.1:9092 --topic test --partition 1 --election-type preferred
Valid replica already elected for partitions test-1
# "preferred"或者"unclean"分别表示优先选举副本、或者允许选举副本状态不一致的节点作为Leader# 使用json文件
[root@master kafka_cluster]# cat replica-election.json 
{"partitions": [{"topic": "test","partition": 0},{"topic": "test001","partition": 1}]}[root@master kafka_cluster]# sh kafka-1/bin/kafka-leader-election.sh --bootstrap-server 127.0.0.1:9092 --path-to-json-file ./replica-election.json --election-type UNCLEAN
Valid replica already elected for partitions test-1, test-0

2.6. 报错记录

2.6.1. 创建topic时报错

[root@master kafka_cluster]# sh kafka-1/bin/kafka-topics.sh --bootstrap-server 127.0.0.1:9092 --create --topic test --partitions 5 --replication-factor 2
Error while executing topic command : Replication factor: 2 larger than available brokers: 1.
[2023-08-31 11:35:06,656] ERROR org.apache.kafka.common.errors.InvalidReplicationFactorException: Replication factor: 2 larger than available brokers: 1.

出现这样情况是因为kafka的节点只有1个，但是备份却大于1个，查看zk下/kafka/brokers/ids时发现只有[0]，ids缺失1和2，重启Kafka服务解决该问题。

2.6.2. 使用工具时直接返回参数列表

这种情况一般都是命令参数使用错误导致，需要查看参数列表重新配置工具参数进行使用。

2.6.3. 未知的选项

[root@master kafka_cluster]# sh kafka-1/bin/kafka-topics.sh --broker-list 127.0.0.1:9092 --topic test --describe
Exception in thread "main" joptsimple.UnrecognizedOptionException: broker-list is not a recognized option～

报错提示：broker-list不是一个可以识别的选项，正确参数为–bootstrap-server。

2.6.4. 重置offset时异常

[root@master kafka_cluster]# sh kafka-1/bin/kafka-consumer-groups.sh --bootstrap-server 127.0.0.1:9092 --group perf-consumer-83143 --reset-offsets --topic test001 --to-latest
WARN: No action will be performed as the --execute option is missing.In a future major release, the default behavior of this command will be to prompt the user before executing the reset rather than doing a dry run. You should add the --dry-run option explicitly if you are scripting this command and want to keep the current default behavior without prompting.Error: Assignments can only be reset if the group 'perf-consumer-83143' is inactive, but the current state is Stable.GROUP                          TOPIC                          PARTITION  NEW-OFFSET

该报错是因为消费者组有消费者正在消费，没有关闭，把消费者关闭之后，重新移动指定分区的偏移量即可。

[root@master kafka_cluster]# sh kafka-1/bin/kafka-consumer-groups.sh --bootstrap-server 127.0.0.1:9092 --group perf-consumer-83143 --reset-offsets --topic test --to-latest
WARN: No action will be performed as the --execute option is missing.In a future major release, the default behavior of this command will be to prompt the user before executing the reset rather than doing a dry run. You should add the --dry-run option explicitly if you are scripting this command and want to keep the current default behavior without prompting.Error: Executing consumer group command failed due to org.apache.kafka.common.errors.UnknownTopicOrPartitionException: This server does not host this topic-partition.
java.util.concurrent.ExecutionException: org.apache.kafka.common.errors.UnknownTopicOrPartitionException: This server does not host this topic-partition.～
Caused by: org.apache.kafka.common.errors.UnknownTopicOrPartitionException: This server does not host this topic-partition.

UnknownTopicOrPartitionException报错是因为topic或partition不存在。

2.6.5. json格式文件工具

参考文章：JSON数据格式与格式化操作详解

2.6.6. Leader重新选举报错

[root@master kafka_cluster]# sh kafka-1/bin/kafka-leader-election.sh --bootstrap-server 127.0.0.1:9092 --topic test --election-type PREFERRED --all-topic-partitions
Exception in thread "main" kafka.common.AdminCommandFailedException: One and only one of the following options is required: topic, all-topic-partitions, path-to-json-file~

该报错是因为–all-topic-partitions参数只能通过–path-to-json-file引入文件进行重新选举操作。

[root@master kafka_cluster]# sh kafka-1/bin/kafka-leader-election.sh --bootstrap-server 127.0.0.1:9092 --path-to-json-file ./replica-election.json --election-type UNCLEAN
Valid replica already elected for partitions test-1, test-0

3、Python连接Kafka

清理环境，避免现象冲突：

[root@master kafka_cluster]# sh kafka-1/bin/kafka-topics.sh --bootstrap-server 127.0.0.1:9092 --list
__consumer_offsets

下载所需python依赖包：kafka-python

pip install kafka-python
pip list

3.1. 生产者

from kafka import KafkaProducer# 连接kafka
producer = KafkaProducer(bootstrap_servers='9.134.244.180:9092')msg = 'Hello test!'.encode('utf-8')for _ in range(100):# 发送100条消息到topic ceshi，消息内容为utf-8编码的Hello test!producer.send('ceshi',msg)producer.flush(timeout=60)		# 重试时间60s
# 关闭连接
producer.close()

运行生产者代码后，查看topic，此时已经创建出来了ceshi topic，代表代码生效，等待代码执行完成即可（提示：进程已结束，退出代码为 0）。

[root@master kafka_cluster]# sh kafka-1/bin/kafka-topics.sh --bootstrap-server 127.0.0.1:9092 --list
__consumer_offsets
ceshi

3.2. 消费者

from kafka import KafkaConsumer# 连接kafka，topic为ceshi，group为ceshi，消费位置从最小开始（包含历史数据）
consumer = KafkaConsumer('ceshi',bootstrap_servers='9.134.244.180:9092',group_id='ceshi',auto_offset_reset='smallest'
)for msg in consumer:recv = '%s:%d:%d:key=%s,value=%s' %(msg.topic,msg.partition,msg.offset,msg.key,msg.value.decode('utf-8'))print(recv)

再执行消费者代码，即可查看到弹出内容：

3.3. 执行结果

ceshi:0:188:key=None,value=Hello test!
~
# 应该弹出100次# 查看消费者组与其消费offset
[root@master kafka_cluster]# sh kafka-1/bin/kafka-consumer-groups.sh --bootstrap-server 127.0.0.1:9092 --list
ceshi
[root@master kafka_cluster]# sh kafka-1/bin/kafka-consumer-groups.sh --bootstrap-server 127.0.0.1:9092 --describe --group ceshiGROUP           TOPIC           PARTITION  CURRENT-OFFSET  LOG-END-OFFSET  LAG             CONSUMER-ID                                             HOST            CLIENT-ID
ceshi           ceshi           0          100             100             0               kafka-python-2.0.2-90fcfcc8-3049-4628-9783-b880e6cf8800 /10.99.17.133   kafka-python-2.0.2