kafka 集群_10分钟搭建单机Kafka集群

单机版kafka集群有什么作用

练习上手用。

搭建zookeeper集群

• 首先下载zookeeper

apache zookeeper官网 apache zookeeper下载地址 apache zookeeper 3.5.5.tar.gz

• 解压

  apache zookeeper

tar -zxvf apache-zookeeper-3.5.5-bin.tar.gz           

• 将zookeeper复制三份,分别命名为zookeeper-1,zookeeper-2,zookeeper-3
• 将zookeeper-1中的zoo.example.cfg文件复制一份改名为: zoo.cfg
• 修改config/zoo.cfg文件
  • 修改端口:

    clientPort=2181

  • 修改数据目录:

    dataDir=/ashura/zookeeper-1/datalog

  • 增加以下配置:

server.1=localhost.:2887:3887 server.2=localhost.:2888:3888 server.3=localhost.:2889:3889 admin.serverPort=8000

完成的配置文件如下:

# 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=/ashura/zookeeper-1/datalog
# 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.
#
# http://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
server.1=localhost.:2887:3887
server.2=localhost.:2888:3888
server.3=localhost.:2889:3889           

• 将这份

  zoo.cfg

  分别复制到

  zookeeper-2

  ,

  zookeeper-3

  的

  config

  目录下.
  • 修改

    zookeeper2

    的

    zoo.cfg

    中

    clientPort=2183

    ,

    dataDir=/ashura/zookeeper-2/datalog

  • 修改

    zookeeper3

    的

    zoo.cfg

    中

    clientPort=2184

    ,

    dataDir=/ashura/zookeeper-3/datalog

• 创建刚才在配置文件中写的目录

mkdir /ashura/zookeeper-1/datalog
mkdir /ashura/zookeeper-2/datalog
mkdir /ashura/zookeeper-3/datalog           

• 分别{-- 在datalog目录下 --}执行以下命令,写入myid。

echo "1" > /ashura/zookeeper-1/datalog/myid
echo "2" > /ashura/zookeeper-2/datalog/myid
echo "3" > /ashura/zookeeper-3/datalog/myid           

• 最后分别启动zookeeper集群

/ashura/zookeeper-1/bin/zkServer.sh start
/ashura/zookeeper-2/bin/zkServer.sh start
/ashura/zookeeper-3/bin/zkServer.sh start           

使用如下命令判断是否启动成功

/ashura/zookeeper-1/bin/zkServer.sh status
/ashura/zookeeper-2/bin/zkServer.sh status
/ashura/zookeeper-3/bin/zkServer.sh status           

搭建Kafka集群

下载

kafka官网 kafka_2.11-2.2.1.tgz

开始安装

• 解压

tar -zxvf kafka_2.11-2.2.1.tgz           

• 将

  config/server.properties

  复制三份，分别命名为

  server1.properties

  ,

  server2.properties

  ,

  server3.properties

  。
• 修改

  server1.properties

  • broker.id=1
  • listeners=PLAINTEXT://:9092
  • advertised.listeners=PLAINTEXT://10.1.14.159:9092(其中10.1.14.159是我本机的ip)
  • log.dirs=/ashura/kafka_2.11-2.2.1/logs/kafka1-logs
  • zookeeper.connect=localhost:2181,localhost:2182,localhost:2183
• 同理,修改

  server2.properties

  • broker.id=2
  • listeners=PLAINTEXT://:9093
  • advertised.listeners=PLAINTEXT://10.1.14.159:9093(其中10.1.14.159是我本机的ip)
  • log.dirs=/ashura/kafka_2.11-2.2.1/logs/kafka2-logs
  • zookeeper.connect=localhost:2181,localhost:2182,localhost:2183

• 同理,修改

  server3.properties

  • broker.id=3
  • listeners=PLAINTEXT://:9094
  • advertised.listeners=PLAINTEXT://10.1.14.159:9094(其中10.1.14.159是我本机的ip)
  • log.dirs=/ashura/kafka_2.11-2.2.1/logs/kafka3-logs
  • zookeeper.connect=localhost:2181,localhost:2182,localhost:2183
• 然后执行以下命令

nohup /ashura/kafka_2.11-2.2.1/bin/kafka-server-start.sh /ashura/kafka_2.11-2.2.1/config/server3.properties > /ashura/kafka_2.11-2.2.1/logs/kafka3-logs/startup.log 2>&1 &
nohup /ashura/kafka_2.11-2.2.1/bin/kafka-server-start.sh /ashura/kafka_2.11-2.2.1/config/server2.properties > /ashura/kafka_2.11-2.2.1/logs/kafka2-logs/startup.log 2>&1 &
nohup /ashura/kafka_2.11-2.2.1/bin/kafka-server-start.sh /ashura/kafka_2.11-2.2.1/config/server1.properties > /ashura/kafka_2.11-2.2.1/logs/kafka1-logs/startup.log 2>&1 &           

• 通过startup.log,或者同级目录下的server.log查看是否有报错即可。
• 检测
  • 创建主题:

    ./kafka-topics.sh --bootstrap-server 127.0.0.1:9092 --create --topic fxb_test1 --replication-factor 3 --partitions 3

  • 启动消费者:

    ./kafka-console-producer.sh --broker-list 10.1.14.159:9092 --topic fxb_test1

  • 新开窗口个,启动生产者:

    kafka-console-producer.sh --bootstrap-server 127.0.0.1 --create --topic fxb_test1

    在生产者窗口中输入消息，查看消费者的窗口，是否有消息产生。

参考文档

Java DOC

使用java client进行测试

• 引入依赖

<dependencies>
    <dependency>
        <groupId>org.apache.kafka</groupId>
        <artifactId>kafka-clients</artifactId>
        <version>2.3.0</version>
    </dependency>
</dependencies>
           

• 创建生产者

package com.fxb.learn.kafka.producer;

import org.apache.kafka.clients.producer.KafkaProducer;
import org.apache.kafka.clients.producer.Producer;
import org.apache.kafka.clients.producer.ProducerConfig;
import org.apache.kafka.clients.producer.ProducerRecord;

import java.util.Properties;

/***
 * 生产者
 */
public class ProducerDemo {

    public static void main(String[] args) {

        Properties props = new Properties();
        props.put("bootstrap.servers", "10.127.138.75:9092");
        props.put("acks", "all");
        props.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer");
        props.put("value.serializer", "org.apache.kafka.common.serialization.StringSerializer");
//        props.put(ProducerConfig.Re)

        Producer<String, String> producer = new KafkaProducer<>(props);
        for (int i = 0; i < 10; i++) {
            producer.send(new ProducerRecord<String, String>("fxb_test1", Integer.toString(i), Integer.toString(i)));
            System.out.println("has sent msg [" + i + "]");
        }
        producer.close();
    }
}
           

• 创建消费者

package com.fxb.learn.kafka.consumer;

import org.apache.kafka.clients.consumer.ConsumerRecord;
import org.apache.kafka.clients.consumer.ConsumerRecords;
import org.apache.kafka.clients.consumer.KafkaConsumer;

import java.time.Duration;
import java.util.Arrays;
import java.util.Properties;

/***
 * 消费者
 */
public class ConsumerDemo {

    public static void main(String[] args) {
        Properties props = new Properties();
        props.setProperty("bootstrap.servers", "10.127.138.75:9092");
        props.setProperty("group.id", "test");
        props.setProperty("enable.auto.commit", "true");
        props.setProperty("auto.commit.interval.ms", "1000");
        props.setProperty("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
        props.setProperty("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
        KafkaConsumer<String, String> consumer = new KafkaConsumer<>(props);
        consumer.subscribe(Arrays.asList("fxb_test1", "bar"));
        while (true) {
            ConsumerRecords<String, String> records = consumer.poll(Duration.ofMillis(100));
            for (ConsumerRecord<String, String> record : records)
                System.out.printf("offset = %d, key = %s, value = %s%n", record.offset(), record.key(), record.value());
        }
    }
}