创建工程
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这里需要注意一下,我们导入的Spring-Kafka为2.1.8版本,SpringBoot为2.0.4的正式版,请保持版本一致、
好了,已经三秒了,真男人,你可以关闭屏幕冷静一下了,停止你那颤抖的身体。
编写第一个Demo
实现顺序
- 创建消费者和生产者的Map配置
- 根据Map配置创建对应的消费者工厂(consumerFactory)和生产者工厂(producerFactory)
- 根据consumerFactory创建监听器的监听器工厂
- 根据producerFactory创建KafkaTemplate(Kafka操作类)
- 创建监听容器
先给你们瞄一眼项目结构,记得把Kafka 启动...
创建KafkaConfiguration配置类
都是一些配置参数,具体的作用也在代码中写明了,值得注意的是,KafkaTemplate的类型为<Integer,String>,我们可以找kafkaTemplate的send方法,有多个重载方法,其中有个方法如下,key和data参数都为泛型,这其实就是对应着KafkaTemplate<Integer,String>。那具体有什么用呢,还记得我们的Topic中可以包含多个Partition(分区)吗,那我们如果不想手动指定发送到哪个分区,我们则可以利用key去实现。这里我们的key是Integer类型,template会根据 key 路由到对应的partition中,如果key存在对应的partitionID则发送到该partition中,否则由算法选择发送到哪个partition。
public ListenableFuture<SendResult<K, V>> send(String topic, K key, V data) {
ProducerRecord<K, V> producerRecord = new ProducerRecord(topic, key, data);
return this.doSend(producerRecord);
}
@Configuration
@EnableKafka
public class KafkaConfiguration {
//ConcurrentKafkaListenerContainerFactory为创建Kafka监听器的工程类,这里只配置了消费者
@Bean
public ConcurrentKafkaListenerContainerFactory<Integer, String> kafkaListenerContainerFactory() {
ConcurrentKafkaListenerContainerFactory<Integer, String> factory = new ConcurrentKafkaListenerContainerFactory<>();
factory.setConsumerFactory(consumerFactory());
return factory;
}
//根据consumerProps填写的参数创建消费者工厂
@Bean
public ConsumerFactory<Integer, String> consumerFactory() {
return new DefaultKafkaConsumerFactory<>(consumerProps());
}
//根据senderProps填写的参数创建生产者工厂
@Bean
public ProducerFactory<Integer, String> producerFactory() {
return new DefaultKafkaProducerFactory<>(senderProps());
}
//kafkaTemplate实现了Kafka发送接收等功能
@Bean
public KafkaTemplate<Integer, String> kafkaTemplate() {
KafkaTemplate template = new KafkaTemplate<Integer, String>(producerFactory());
return template;
}
//消费者配置参数
private Map<String, Object> consumerProps() {
Map<String, Object> props = new HashMap<>();
//连接地址
props.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, "localhost:9092");
//GroupID
props.put(ConsumerConfig.GROUP_ID_CONFIG, "bootKafka");
//是否自动提交
props.put(ConsumerConfig.ENABLE_AUTO_COMMIT_CONFIG, true);
//自动提交的频率
props.put(ConsumerConfig.AUTO_COMMIT_INTERVAL_MS_CONFIG, "100");
//Session超时设置
props.put(ConsumerConfig.SESSION_TIMEOUT_MS_CONFIG, "15000");
//键的反序列化方式
props.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, IntegerDeserializer.class);
//值的反序列化方式
props.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class);
return props;
}
//生产者配置
private Map<String, Object> senderProps (){
Map<String, Object> props = new HashMap<>();
//连接地址
props.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, "localhost:9092");
//重试,0为不启用重试机制
props.put(ProducerConfig.RETRIES_CONFIG, 1);
//控制批处理大小,单位为字节
props.put(ProducerConfig.BATCH_SIZE_CONFIG, 16384);
//批量发送,延迟为1毫秒,启用该功能能有效减少生产者发送消息次数,从而提高并发量
props.put(ProducerConfig.LINGER_MS_CONFIG, 1);
//生产者可以使用的总内存字节来缓冲等待发送到服务器的记录
props.put(ProducerConfig.BUFFER_MEMORY_CONFIG, 1024000);
//键的序列化方式
props.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, IntegerSerializer.class);
//值的序列化方式
props.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, StringSerializer.class);
return props;
}
}
创建DemoListener消费者
这里的消费者其实就是一个监听类,指定监听名为topic.quick.demo的Topic,consumerID为demo。
@Component
public class DemoListener {
private static final Logger log= LoggerFactory.getLogger(DemoListener.class);
//声明consumerID为demo,监听topicName为topic.quick.demo的Topic
@KafkaListener(id = "demo", topics = "topic.quick.demo")
public void listen(String msgData) {
log.info("demo receive : "+msgData);
}
}
创建测试类
这里的send方法第一参数为TopicName,第二个参数则是发送的数据
@SpringBootTest
@RunWith(SpringRunner.class)
public class DemoTest {
@Autowired
private KafkaTemplate kafkaTemplate;
@Test
public void testDemo() throws InterruptedException {
kafkaTemplate.send("topic.quick.demo", "this is my first demo");
//休眠5秒,为了使监听器有足够的时间监听到topic的数据
Thread.sleep(5000);
}
}
接下来直接运行这个测试方法,我们可以看到日志中输出了我们发送的消息,这就代表我们成功的消费了测试方法中发送的消息。
2018-09-06 17:26:20.850 INFO 6232 --- [ demo-0-C-1] com.viu.kafka.listen.DemoListener : demo receive : this is my first demo
启动项目
看清楚了是启动项目,不是测试类,我们来观察一下控制台的输出日志
首先这个是KafkaConsumer的配置信息,每个消费者都会输出该配置信息,配置太多就不做讲解了
2018-09-06 17:40:15.258 INFO 9944 --- [ main] o.a.k.clients.consumer.ConsumerConfig : ConsumerConfig values:
auto.commit.interval.ms = 100
auto.offset.reset = latest
bootstrap.servers = [localhost:9092]
check.crcs = true
client.id =
connections.max.idle.ms = 540000
enable.auto.commit = true
exclude.internal.topics = true
fetch.max.bytes = 52428800
fetch.max.wait.ms = 500
fetch.min.bytes = 1
group.id = demo
heartbeat.interval.ms = 3000
interceptor.classes = null
internal.leave.group.on.close = true
isolation.level = read_uncommitted
key.deserializer = class org.apache.kafka.common.serialization.IntegerDeserializer
max.partition.fetch.bytes = 1048576
max.poll.interval.ms = 300000
max.poll.records = 500
metadata.max.age.ms = 300000
metric.reporters = []
metrics.num.samples = 2
metrics.recording.level = INFO
metrics.sample.window.ms = 30000
partition.assignment.strategy = [class org.apache.kafka.clients.consumer.RangeAssignor]
receive.buffer.bytes = 65536
reconnect.backoff.max.ms = 1000
reconnect.backoff.ms = 50
request.timeout.ms = 305000
retry.backoff.ms = 100
sasl.jaas.config = null
sasl.kerberos.kinit.cmd = /usr/bin/kinit
sasl.kerberos.min.time.before.relogin = 60000
sasl.kerberos.service.name = null
sasl.kerberos.ticket.renew.jitter = 0.05
sasl.kerberos.ticket.renew.window.factor = 0.8
sasl.mechanism = GSSAPI
security.protocol = PLAINTEXT
send.buffer.bytes = 131072
session.timeout.ms = 15000
ssl.cipher.suites = null
ssl.enabled.protocols = [TLSv1.2, TLSv1.1, TLSv1]
ssl.endpoint.identification.algorithm = null
ssl.key.password = null
ssl.keymanager.algorithm = SunX509
ssl.keystore.location = null
ssl.keystore.password = null
ssl.keystore.type = JKS
ssl.protocol = TLS
ssl.provider = null
ssl.secure.random.implementation = null
ssl.trustmanager.algorithm = PKIX
ssl.truststore.location = null
ssl.truststore.password = null
ssl.truststore.type = JKS
value.deserializer = class org.apache.kafka.common.serialization.StringDeserializer
2018-09-06 17:40:15.274 INFO 9944 --- [ main] o.a.kafka.common.utils.AppInfoParser : Kafka version : 1.0.2
2018-09-06 17:40:15.274 INFO 9944 --- [ main] o.a.kafka.common.utils.AppInfoParser : Kafka commitId : 2a121f7b1d402825
这些日志就代表我们成功的创建了Consumer,由于没有做并发配置,所以现在为单个消费者模式,系统会做一个分配Partition的操作,也就是将某个Partition指定给某个消费者消费。 这里有个地方需要注意一下,
看到日志中有输出[Consumer clientId=consumer-1, groupId=demo],我们之前在监听中@KafkaListener注解中配置的id=demo,怎么就变成了groupId=demo,这是因为@KafkaListener注解如果没有指定groupId这个属性的值,则会默认把id作为groupId。
2018-09-06 17:40:15.287 INFO 9944 --- [ demo-0-C-1] o.a.k.c.c.internals.AbstractCoordinator : [Consumer clientId=consumer-1, groupId=demo] Discovered group coordinator admin-PC:9092 (id: 2147483647 rack: null)
2018-09-06 17:40:15.290 INFO 9944 --- [ demo-0-C-1] o.a.k.c.c.internals.ConsumerCoordinator : [Consumer clientId=consumer-1, groupId=demo] Revoking previously assigned partitions []
2018-09-06 17:40:15.290 INFO 9944 --- [ demo-0-C-1] o.s.k.l.KafkaMessageListenerContainer : partitions revoked: []
2018-09-06 17:40:15.290 INFO 9944 --- [ demo-0-C-1] o.a.k.c.c.internals.AbstractCoordinator : [Consumer clientId=consumer-1, groupId=demo] (Re-)joining group
2018-09-06 17:40:15.301 INFO 9944 --- [ main] o.s.b.w.embedded.tomcat.TomcatWebServer : Tomcat started on port(s): 8080 (http) with context path ''
2018-09-06 17:40:15.302 INFO 9944 --- [ demo-0-C-1] o.a.k.c.c.internals.AbstractCoordinator : [Consumer clientId=consumer-1, groupId=demo] Successfully joined group with generation 33
2018-09-06 17:40:15.303 INFO 9944 --- [ demo-0-C-1] o.a.k.c.c.internals.ConsumerCoordinator : [Consumer clientId=consumer-1, groupId=demo] Setting newly assigned partitions [topic.quick.demo-0]
结束
SpringBoot2.0已经提供了Kafka的自动配置,可以在application.properties文件中配置,别问我为什么要写一堆代码来创建这些工厂,相对于properties方式我更喜欢java Config方法创建这些配置,因为很直观,虽然是有点麻烦。