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kafka分布式消息队列部署

      2020年11月08日   阅读 383 次     0 评论   Tags:

Kafka是由Apache软件基金会开发的一个开源流处理平台,由Scala和Java编写。Kafka是一种高吞吐量的分布式发布订阅消息系统,它可以处理消费者在网站中的所有动作流数据。 这种动作(网页浏览,搜索和其他用户的行动)是在现代网络上的许多社会功能的一个关键因素。 这些数据通常是由于吞吐量的要求而通过处理日志和日志聚合来解决。 对于像Hadoop一样的日志数据和离线分析系统,但又要求实时处理的限制,这是一个可行的解决方案。Kafka的目的是通过Hadoop的并行加载机制来统一线上和离线的消息处理,也是为了通过集群来提供实时的消息。

更多参考:https://www.cnblogs.com/qingyunzong/p/9004509.html

一、zookeeper集群部署:参考上一篇博文:zookeeper单机和集群部署

二、Kafka部署


### 1、下载kafka软件
[root@zk02 ~]# wget https://mirrors.tuna.tsinghua.edu.cn/apache/kafka/2.6.0/kafka_2.13-2.6.0.tgz
[root@zk02 ~]# tar xf kafka_2.13-2.6.0.tgz 
[root@zk02 ~]# mv kafka_2.13-2.6.0 /data/kafka-2.6.0
[root@zk02 ~]# cd kafka-2.6.0/
[root@zk02 ~]# mkdir kafka-logs

### 2、修改配置文件和zookeeper集成
[root@zk01 config]# vi 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.

# 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.
### 设置broker id 唯一值并且为整数
broker.id=1

delete.topic.enable=true 

############################# 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
#设置监听端口和IP地址
listeners=PLAINTEXT://204.13.155.226:9092

# 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://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
#设置数据目录
log.dirs=/data/kafka-2.6.0/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.

#设置zookeeper服务器的地址
zookeeper.connect=zk01:2181,zk02:2181,zk03:2181

# 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

3、启动和停止Kafka
### 前台启动
[root@zk02 ~]# kafka-server-start.sh  config/server.properties 
### 后台启动
[root@zk02 ~]# kafka-server-start.sh -daemon  /data/kafka-2.6.0/config/server.properties

### 停止Kafka
[root@zk02 ~]# kafka-server-stop.sh

三、Kafka简单测试



### 创建3副本1分区topic名为test

kafka-topics.sh --create --zookeeper zk01:2181 --replication-factor 3 --partitions 1 --topic test

### 删除topic
kafka-topics.sh --delete --zookeeper zk01:2181 --topic test

### 显示topic

kafka-topics.sh -list -zookeeper  zk01:2181
kafka-topics.sh -list -zookeeper  zk02:2181
kafka-topics.sh -list -zookeeper  zk03:2181

### 创建生产者和消费者

创建kafka生产者:
kafka-console-producer.sh --broker-list zk01:9092 --topic test

创建kafka消费者:
kafka-console-consumer.sh --bootstrap-server zk01:9092 --topic test --from-beginning

设置kafka消费组名:
kafka-console-consumer.sh --bootstrap-server zk01:9092 --topic test --from-beginning --consumer-property group.id=test-group


3,生产者操作,在zk01发布消息,测试发布两条消息 abc 和 test:
[root@zk01 config]# kafka-console-producer.sh --broker-list zk01:9092 --topic my-kafka-topic  //my-kafka-topic时topic的名字
>abc
>test
  
 
4,消费者操作,在另外两台kafka集群,可以看到在zk02 会获取到两条消息abc和test,说明分布式消息队列生效,通过zookeeper已经同步。
[root@zk02 ~]# kafka-console-consumer.sh --bootstrap-server zk02:9092 --topic my-kafka-topic
abc
test

至此Kafka分布式部署和简单测试完成。

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