Java使用Kafka初探

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以前用过mq，也早就听说过Kafka。

Kafka这个名字感觉好高大上，一直想着试试是怎样的，今天周末，正好有空，在家来尝试一下

以下是我今天搭建一个Kafka使用的主要步骤

环境：

1.centos7 x64(预先装好了JDK环境)

2.Kafka版本：kafka_2.10-0.10.2.1

1.Kafka下载

官方下载地址：http://kafka.apache.org/downloads

我这里选择目前最新的kafka_2.10-0.10.2.1

可用地址：https://www.apache.org/dyn/closer.cgi?path=/kafka/0.10.2.1/kafka_2.10-0.10.2.1.tgz

下载完毕后，解压

[ping@Hadoop kafka]$ lltotal 37524-rw-r--r--. 1 ping ping 38424081 Jun 10 18:28 kafka_2.10-0.10.2.1.tgz[ping@Hadoop kafka]$ tar -zxvf kafka_2.10-0.10.2.1.tgz

2.修改配置文件

[ping@Hadoop config]$ pwd/home/ping/kafka/kafka_2.10-0.10.2.1/config[ping@Hadoop config]$ lltotal 60-rw-r--r--. 1 ping ping  906 Apr 21 09:23 connect-console-sink.properties-rw-r--r--. 1 ping ping  909 Apr 21 09:23 connect-console-source.properties-rw-r--r--. 1 ping ping 2760 Apr 21 09:23 connect-distributed.properties-rw-r--r--. 1 ping ping  883 Apr 21 09:23 connect-file-sink.properties-rw-r--r--. 1 ping ping  881 Apr 21 09:23 connect-file-source.properties-rw-r--r--. 1 ping ping 1074 Apr 21 09:23 connect-log4j.properties-rw-r--r--. 1 ping ping 2061 Apr 21 09:23 connect-standalone.properties-rw-r--r--. 1 ping ping 1199 Apr 21 09:23 consumer.properties-rw-r--r--. 1 ping ping 4369 Apr 21 09:23 log4j.properties-rw-r--r--. 1 ping ping 1900 Apr 21 09:23 producer.properties-rw-r--r--. 1 ping ping 5631 Apr 21 09:23 server.properties-rw-r--r--. 1 ping ping 1032 Apr 21 09:23 tools-log4j.properties-rw-r--r--. 1 ping ping 1023 Apr 21 09:23 zookeeper.properties[ping@Hadoop config]$

为了快速演示方便，可以不用修改任何配置信息。如果需要针对不同的环境进行设置，需要做以下内容为主的修改

2.1 zookeeper配置文件

kafka的运行环境还需要zookeeper来进行协调，这里我采用默认的配置

对应的配置文件为zookeeper.properties

2.2 server.properties

Kafka程序主要的配置，在server.properties文件中修改与设置

主要关注的3点为此文件中的以下内容：

# The id of the broker. This must be set to a unique integer for each broker.
broker.id=0

# 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

# 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=localhost:2181

# Timeout in ms for connecting to zookeeper
zookeeper.connection.timeout.ms=6000

打开这个配置文件，上面也有较为详细的说明

为了演示方便，只将listeners=PLAINTEXT://:9092改为本地地址,如listeners=PLAINTEXT://192.168.0.95:9092

2.3 producer.properties

由producer这个名字可以得知，这是一个跟消息生产提供相关的配置

关心点：bootstrap.servers=localhost:9092

2.4 consumer.properties

与producer相对应，用于消费端的相关配置

关心点：

# Zookeeper connection string
# 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"
zookeeper.connect=127.0.0.1:2181

# timeout in ms for connecting to zookeeper
zookeeper.connection.timeout.ms=6000

#consumer group id
group.id=test-consumer-group

#consumer timeout
#consumer.timeout.ms=5000

3.kafka启动

3.1 zookeeper启动

zookeeper作为kafka的协调者，需要在kafka运行前最先运行

运行bin目录下的如下shell,后面跟上配置文件的地址

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

[ping@Hadoop kafka_2.10-0.10.2.1]$ pwd/home/ping/kafka/kafka_2.10-0.10.2.1[ping@Hadoop kafka_2.10-0.10.2.1]$ lltotal 52drwxr-xr-x. 3 ping ping  4096 Apr 21 09:24 bindrwxr-xr-x. 2 ping ping  4096 Jun 10 19:45 configdrwxr-xr-x. 2 ping ping  4096 Jun 10 19:17 libs-rw-r--r--. 1 ping ping 28824 Apr 21 09:23 LICENSEdrwxrwxr-x. 2 ping ping  4096 Jun 10 19:46 logs-rw-r--r--. 1 ping ping   336 Apr 21 09:23 NOTICEdrwxr-xr-x. 2 ping ping    46 Apr 21 09:24 site-docs[ping@Hadoop kafka_2.10-0.10.2.1]$ bin/zookeeper-server-start.sh config/zookeeper.properties &

3.2 kafka服务启动

kafka服务的启动主要执行如下shell

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

[ping@Hadoop kafka_2.10-0.10.2.1]$ bin/kafka-server-start.sh config/server.properties

3.3创建topic

作为消息的创建与消费，需要制定一个topic，跟分组类似

bin/kafka-topics.sh --create --zookeeper localhost:2181 --replication-factor 1 --partitions 1 --topic test

最后的test代表topic的名字

[ping@Hadoop kafka_2.10-0.10.2.1]$ bin/kafka-topics.sh --create --zookeeper localhost:2181 --replication-factor 1 --partitions 1 --topic testCreated topic "test".

如要查看目前已经创建了的topic，用如下命令

bin/kafka-topics.sh --list --zookeeper localhost:2181

如：

[ping@Hadoop kafka_2.10-0.10.2.1]$  bin/kafka-topics.sh --list --zookeeper localhost:2181test

4.kafka消息创建与消费测试

4.1 kafka消息生产启动

用下以命令指定将要产生的消息对应的kafka服务和topic是什么

[ping@Hadoop kafka_2.10-0.10.2.1]$ bin/kafka-console-producer.sh --broker-list localhost:9092 --topic test

运行成功后，控制台将会进入阻塞状态，等待用户在此控制台上输入将要发送的内容，提交给kafka服务

如：

[ping@Hadoop kafka_2.10-0.10.2.1]$ bin/kafka-console-producer.sh --broker-list localhost:9092 --topic test 123abchaha

通过回车换行后，消息将会发送到kafka中，等待其消息

4.2 kafka消息消费启动

用以下命令来消费消息

bin/kafka-console-consumer.sh --zookeeper localhost:2181 --topic test --from-beginning

其中指定了kafka的协调者是哪个zookeeper和topic是哪个

运行上面的命令后，就会消费kafka中的test这个topic的消息了

如下：

[ping@Hadoop kafka_2.10-0.10.2.1]$ bin/kafka-console-consumer.sh --zookeeper localhost:2181 --topic test --from-beginningUsing the ConsoleConsumer with old consumer is deprecated and will be removed in a future major release. Consider using the new consumer by passing [bootstrap-server] instead of [zookeeper].123abchaha

5.Java客户端程序调用

kafka的启动主要占用了如下端口，确保如下端口是运行了的,并且端口所开放的网卡是开放出来的

tcp6 0 0 :::9092 :::* LISTEN 33492/java

tcp6 0 0 :::2181 :::* LISTEN 33123/java

5.1 SpringBoot消费测试

在springBoot工程中添加maven依赖

<dependency><groupId>org.springframework.kafka</groupId><artifactId>spring-kafka</artifactId></dependency>

在application.yml中加入配置信息：

haiyang:  kafka:    binder:      brokers: 192.168.31.222:9092      zk-nodes: 192.168.31.222:2181    group: test-group

创建kafkaProducersConfig

package com.haiyang.config;import org.apache.kafka.clients.producer.ProducerConfig;import org.apache.kafka.common.serialization.StringSerializer;import org.springframework.beans.factory.annotation.Value;import org.springframework.context.annotation.Bean;import org.springframework.context.annotation.Configuration;import org.springframework.kafka.annotation.EnableKafka;import org.springframework.kafka.core.DefaultKafkaProducerFactory;import org.springframework.kafka.core.KafkaTemplate;import org.springframework.kafka.core.ProducerFactory;import java.util.HashMap;import java.util.Map;@Configuration@EnableKafkapublic class KafkaProducersConfig {    @Value("${haiyang.kafka.binder.brokers}")    private String brokers;    @Bean("kafkaTemplate")    public KafkaTemplate<String, String> kafkaTemplate() {        KafkaTemplate<String, String> kafkaTemplate = new KafkaTemplate<String, String>(producerFactory());        return kafkaTemplate;    }    public ProducerFactory<String, String> producerFactory() {        Map<String, Object> properties = new HashMap<String, Object>();        properties.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, brokers);        properties.put(ProducerConfig.BATCH_SIZE_CONFIG, 4096);        properties.put(ProducerConfig.LINGER_MS_CONFIG, 1);        properties.put(ProducerConfig.BUFFER_MEMORY_CONFIG, 40960);        properties.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, StringSerializer.class);        properties.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, StringSerializer.class);        return new DefaultKafkaProducerFactory<String, String>(properties);    }}

创建KafkaConsumerConfig

package com.haiyang.config;import org.apache.kafka.clients.consumer.ConsumerConfig;import org.apache.kafka.common.serialization.StringDeserializer;import org.springframework.beans.factory.annotation.Value;import org.springframework.context.annotation.Bean;import org.springframework.context.annotation.Configuration;import org.springframework.kafka.annotation.EnableKafka;import org.springframework.kafka.config.ConcurrentKafkaListenerContainerFactory;import org.springframework.kafka.config.KafkaListenerContainerFactory;import org.springframework.kafka.core.ConsumerFactory;import org.springframework.kafka.core.DefaultKafkaConsumerFactory;import org.springframework.kafka.listener.ConcurrentMessageListenerContainer;import java.util.HashMap;import java.util.Map;@Configuration@EnableKafkapublic class KafkaConsumerConfig {    @Value("${haiyang.kafka.binder.brokers}")    private String brokers;    @Value("${haiyang.kafka.group}")    private String group;    @Bean    public KafkaListenerContainerFactory<ConcurrentMessageListenerContainer<String, String>> kafkaListenerContainerFactory() {        ConcurrentKafkaListenerContainerFactory<String, String> factory = new ConcurrentKafkaListenerContainerFactory<String, String>();        factory.setConsumerFactory(consumerFactory());        factory.setConcurrency(4);        factory.getContainerProperties().setPollTimeout(4000);        return factory;    }    @Bean    public KafkaListeners kafkaListeners() {        return new KafkaListeners();    }    public ConsumerFactory<String, String> consumerFactory() {        Map<String, Object> properties = new HashMap<String, Object>();        properties.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, brokers);        properties.put(ConsumerConfig.ENABLE_AUTO_COMMIT_CONFIG, false);        properties.put(ConsumerConfig.AUTO_COMMIT_INTERVAL_MS_CONFIG, "100");        properties.put(ConsumerConfig.SESSION_TIMEOUT_MS_CONFIG, "15000");        properties.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class);        properties.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class);        properties.put(ConsumerConfig.GROUP_ID_CONFIG, group);        properties.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "latest");        return new DefaultKafkaConsumerFactory<String, String>(properties);    }}

创建KafkaListeners

用于监听Kafka，进行消费

package com.haiyang.config;import org.apache.kafka.clients.consumer.ConsumerRecord;import org.springframework.kafka.annotation.KafkaListener;import java.util.Optional;public class KafkaListeners {    @KafkaListener(topics = {"test"})    public void testListener(ConsumerRecord<?, ?> record) {        Optional<?> messages = Optional.ofNullable(record.value());        if (messages.isPresent()) {            Object msg = messages.get();            System.out.println("get message from kafka: " + msg);        }    }}

以上配置完成了一个简单的Kafka配置

发送测试controller

为了测试方便，再创建就一个controller，用于发送消息

package com.haiyang.controller;import org.springframework.beans.factory.annotation.Autowired;import org.springframework.kafka.core.KafkaTemplate;import org.springframework.web.bind.annotation.RequestMapping;import org.springframework.web.bind.annotation.RestController;@RestControllerpublic class FeignController {    @Autowired    KafkaTemplate kafkaTemplate;    private static int index = 0;    @RequestMapping("/testKafka")    public void testkafka(String message) {        kafkaTemplate.send("test", "haha" + index++);    }}

5.2测试

package com.haiyang;import org.springframework.boot.SpringApplication;import org.springframework.boot.autoconfigure.SpringBootApplication;@SpringBootApplicationpublic class SpringbootWithKafkaApplication {   public static void main(String[] args) {      SpringApplication.run(SpringbootWithKafkaApplication.class, args);   }}

运行springBoot测试类,再通过浏览器发送几条消息，截图如下:

简单试了下，通过springBoot来调用kafka还是挺方便简单的

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