深浅模式
Springboot中使用Kafka
1.引入依赖
xml
<dependency>
<groupId>org.springframework.kafka</groupId>
<artifactId>spring-kafka</artifactId>
</dependency>2.配置文件
yml
server:
port: 8080
spring:
kafka:
bootstrap-servers: 172.16.253.21: 9093
producer: # 生产者
retries: 3 # 设置大于 0 的值,则客户端会将发送失败的记录重新发送
batch-size: 16384
buffer-memory: 33554432
acks: 1
# 指定消息key和消息体的编解码方式
key-serializer: org.apache.kafka.common.serialization.StringSerializer
value-serializer: org.apache.kafka.common.serialization.StringSerializer
consumer:
group-id: default-group
enable-auto-commit: false
auto-offset-reset: earliest
key-deserializer: org.apache.kafka.common.serialization.StringDeserializer
value-deserializer: org.apache.kafka.common.serialization.StringDeserializer
max-poll-records: 500
listener:
# 当每一条记录被消费者监听器(ListenerConsumer)处理之后提交
# RECORD
# 当每一批poll()的数据被消费者监听器(ListenerConsumer)处理之后提交
# BATCH
# 当每一批poll()的数据被消费者监听器(ListenerConsumer)处理之后,距离上次提交时间大于TIME时提交
# TIME
# 当每一批poll()的数据被消费者监听器(ListenerConsumer)处理之后,被处理record数量大于等于COUNT时提交
# COUNT
# TIME | COUNT 有一个条件满足时提交
# COUNT_TIME
# 当每一批poll()的数据被消费者监听器(ListenerConsumer)处理之后, 手动调用Acknowledgment.acknowledge()后提交
# MANUAL
# 手动调用Acknowledgment.acknowledge()后立即提交,一般使用这种
# MANUAL_IMMEDIATE
ack-mode: MANUAL_IMMEDIATE
redis:
host: 172.16.253.213.消息生产者
- 发送消息到指定topic
java
@RestController
public class KafkaController {
private final static String TOPIC_NAME = "my-replicated-topic";
@Autowired
private KafkaTemplate<String, String> kafkaTemplate;
@RequestMapping("/send")
public void send() {
kafkaTemplate.send(TOPIC_NAME, 0 , "key", "this is a msg");
}
}4.消息消费者
- 设置消费组,消费指定topic
java
@KafkaListener(topics = "my-replicated-topic",groupId = "MyGroup1")
public void listenGroup(ConsumerRecord<String, String> record,Acknowledgment ack) {
String value = record.value();
System.out.println(value);
System.out.println(record);
//手动提交offset
ack.acknowledge();
}- 设置消费组、多topic、指定分区、指定偏移量消费及设置消费者个数。
java
@KafkaListener(groupId = "testGroup", topicPartitions = {
@TopicPartition(topic = "topic1", partitions = {"0", "1"}),
@TopicPartition(topic = "topic2", partitions = "0",partitionOffsets = @PartitionOffset(partition = "1",initialOffset = "100"))}
,concurrency = "3")//concurrency就是同组下的消费者个数,就是并发消费数,建议小于等于分区总数
public void listenGroup(ConsumerRecord<String, String> record,Acknowledgment ack) {
String value = record.value();
System.out.println(value);
System.out.println(record);
//手动提交offset
ack.acknowledge();
}