文章目錄

• 準備
• 集群安裝
• • 1、創建目錄
  • 2、解壓縮安裝包
  • 3、修改配置文件
  • 4、啟動
  • 5、查看集群是否安裝成功
• 測試Kafka
• • 1、創建測試mytopic
  • 2、查看mytopic副本信息
  • 3、查看已創建topic列表信息
  • 4、創建Producer
  • 5、創建Consumer
  • 6、刪除mytopic
  • 7、停止kafka

準備

1、首先安裝zookeeper作為為集群提供高可用
2、準備kafka按裝包kafka_2.11-2.1.1.tgz
3、準備三臺機器hadoop-slave1、hadoop-slave2、hadoop-slave3

集群安裝

1、創建目錄

創建kafka和kafkalogs目錄，并將壓縮包存放到/opt/kafka目錄下，創建后的全路徑如下所示：

/opt/kafka /opt/kafka/kafkalogs

2、解壓縮安裝包

tar -zxvf kafka_2.11-2.1.1.tgz

3、修改配置文件

首先打開配置文件位置

cd /opt/kafka/kafka_2.11-2.1.1/config/

這里主要關注server.properties文件，這里可以通過zookeeper.properties配置Kafka內帶的zk集群來啟動，但是建議使用獨立的zk集群

下面這個是hadoop-slave上的完整配置：

[root@hadoop-slave1 config]# cat 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. 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://: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 log.dirs=/opt/kafka/kafkalogs/# 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# 默認消息的最大持久化時間，168小時，7天 log.retention.hours=168 # 消息保存的最大值5M message.max.byte=5242880 # kafka保存消息的副本數，如果一個副本失效了，另一個還可以繼續提供服務 default.replication.factor=2 # 取消息的最大直接數 replica.fetch.max.bytes=5242880# 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#log.cleaner.enable=false #是否啟用log壓縮，一般不啟用，啟用的話可以提高性能 ############################# 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=hadoop-slave1:12181,hadoop-slave2:12181,hadoop-slave3:12181# 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

hadoop-slave2和hadoop-slave3配置基本和上邊一致，就是標紅的地方需要做修改成相應的值

4、啟動

進入3臺機器的bin目錄

cd /opt/kafka/kafka_2.11-2.1.1/bin

每一臺機器都執行啟動命令

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

每一臺機器都檢查是否已啟動

5、查看集群是否安裝成功

客戶端連接zookeeper

/opt/zookeeper/zookeeper-3.4.12/bin/zkCli.sh -server hadoop-slave1:12181

檢查kafka集群啟動個數

ls /brokers/ids

測試Kafka

1、創建測試mytopic

/opt/kafka/kafka_2.11-2.1.1/bin/kafka-topics.sh --create --zookeeper hadoop-slave1:12181,hadoop-slave2:12181,hadoop-slave3:12181 --replication-factor 3 --partitions 3 --topic mytopic

選項說明：

–topic 定義topic名

–replication-factor 定義副本數

–partitions 定義分區數

2、查看mytopic副本信息

/opt/kafka/kafka_2.11-2.1.1/bin/kafka-topics.sh --describe --zookeeper hadoop-slave1:12181,hadoop-slave2:12181,hadoop-slave3:12181 --topic mytopic

3、查看已創建topic列表信息

/opt/kafka/kafka_2.11-2.1.1/bin/kafka-topics.sh --list --zookeeper hadoop-slave1:12181,hadoop-slave2:12181,hadoop-slave3:12181

4、創建Producer

/opt/kafka/kafka_2.11-2.1.1/bin/kafka-console-producer.sh --broker-list hadoop-slave1:9092,hadoop-slave2:9092,hadoop-slave3:9092 --topic mytopic

基于mytopic并發送消息"hello kafka 20201228"

5、創建Consumer

注意：--bootstrap-server后面跟的是borker的地址

/opt/kafka/kafka_2.11-2.1.1/bin/kafka-console-consumer.sh --bootstrap-server hadoop-slave1:9092,hadoop-slave2:9092,hadoop-slave3:9092 --from-beginning --topic mytopic

–from-beginning：會把TestTopic主題中以往所有的數據都讀取出來。根據業務場景選擇是否增加該配置。

注意：消費者的命令跟版本有關系，本文使用的新版本命令基于kafka_2.11-2.1.1

下面是舊版本的啟動命令，注意后面跟的是zookeeper集群的地址

./bin/kafka-console-consumer.sh --zookeeper hadoop-slave1:12181,hadoop-slave2:12181,hadoop-slave3:12181 --from-beginning --topic mytopic

6、刪除mytopic

7、停止kafka

/opt/kafka/kafka_2.11-2.1.1/bin/kafka-server-stop.sh

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