kafka的ack&retries
consumer
package com.soul.kafka.level08;
import org.apache.kafka.clients.consumer.ConsumerConfig;
import org.apache.kafka.clients.consumer.ConsumerRecord;
import org.apache.kafka.clients.consumer.ConsumerRecords;
import org.apache.kafka.clients.consumer.KafkaConsumer;
import org.apache.kafka.common.serialization.StringDeserializer;
import java.time.Duration;
import java.util.Iterator;
import java.util.Properties;
import java.util.regex.Pattern;
public class _19KafkaConsumerAck {
public static void main(String[] args) {
//1.创建Kafka链接参数
Properties props = new Properties();
props.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, "kafka01:9092,kafka02:9092,kafka03:9092");
props.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class.getName());
props.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class.getName());
props.put(ConsumerConfig.GROUP_ID_CONFIG, "group01");
//2.创建Topic消费者
KafkaConsumer<String, String> consumer = new KafkaConsumer<>(props);
//3.订阅topic开头的消息队列
consumer.subscribe(Pattern.compile("^topic.*$"));
while (true) {
ConsumerRecords<String, String> consumerRecords = consumer.poll(Duration.ofSeconds(1));
Iterator<ConsumerRecord<String, String>> recordIterator = consumerRecords.iterator();
while (recordIterator.hasNext()) {
ConsumerRecord<String, String> record = recordIterator.next();
String key = record.key();
String value = record.value();
long offset = record.offset();
int partition = record.partition();
System.out.println("key:" + key + ", val:" + value
+ ", partition:" + partition + ", offset:" + offset);
}
}
}
}
producer
package com.soul.kafka.level08;
import org.apache.kafka.clients.producer.KafkaProducer;
import org.apache.kafka.clients.producer.ProducerConfig;
import org.apache.kafka.clients.producer.ProducerRecord;
import org.apache.kafka.common.serialization.StringSerializer;
import java.util.Properties;
/**
*
Kafka生产者在发送完一个的消息之后,要求Broker在规定的额时间Ack应答答,
如果没有在规定时间内应答,Kafka生产者会尝试n次重新发送消息。
acks=1 默认
acks=1 - Leader会将Record写到其本地日志中,但会在不等待所有Follower的完全确认的情况下做出响应。
在这种情况下,如果Leader在确认记录后立即失败,但在Follower复制记录之前失败,则记录将丢失。
acks=0 - 生产者根本不会等待服务器的任何确认。该记录将立即添加到套接字缓冲区中并视为已发送。
在这种情况下,不能保证服务器已收到记录。
acks=all - 这意味着Leader将等待全套同步副本确认记录。
这保证了只要至少一个同步副本仍处于活动状态,记录就不会丢失。这是最有力的保证。这等效于acks = -1设置。
如果生产者在规定的时间内,并没有得到Kafka的Leader的Ack应答,Kafka可以开启reties机制。
request.timeout.ms = 30000 默认
retries = 2147483647 默认
*
*/
public class _20KafkaProducerAck {
//测试
//启动 _19KafkaConsumerAck 消费端服务器
//启动 _20KafkaProducerAck 生产端服务器, 发送1条消息
//发现 _19KafkaConsumerAck 消费了4次(正常1次+重试3次)
public static void main(String[] args) {
//创建链接参数
Properties props = new Properties();
//hostname:port
props.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, "kafka01:9092,kafka02:9092,kafka03:9092");
//序列化反序列化
props.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, StringSerializer.class.getName());
props.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, StringSerializer.class.getName());
// -1 等价于 all, Leader将等待全套同步副本确认记录
//props.put(ProducerConfig.ACKS_CONFIG, "all");
props.put(ProducerConfig.ACKS_CONFIG, "-1");
//重试3次
props.put(ProducerConfig.RETRIES_CONFIG, 3);
//设置1ms未收到ack则重试, 便于出现消费端重复消费问题
props.put(ProducerConfig.REQUEST_TIMEOUT_MS_CONFIG, 1);
//创建生产者
KafkaProducer<String, String> producer = new KafkaProducer<>(props);
//消息队列发送消息, 仅仅发送一条
for (int i = 0; i < 1; i++) {
ProducerRecord<String, String> record = new ProducerRecord<>("topic02",
"K" + i, "V" + i);
producer.send(record);
}
producer.close();
}
}
pom.xml
<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 https://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<groupId>com.soul</groupId>
<artifactId>kafka</artifactId>
<version>0.0.1</version>
<name>kafka</name>
<properties>
<java.version>1.8</java.version>
</properties>
<dependencies>
<!-- kafka begin -->
<!--https://mvnrepository.com/artifact/org.apache.kafka/kafka-clients-->
<dependency>
<groupId>org.apache.kafka</groupId>
<artifactId>kafka-clients</artifactId>
<version>2.2.0</version>
</dependency>
<!-- https://mvnrepository.com/artifact/log4j/log4j -->
<dependency>
<groupId>log4j</groupId>
<artifactId>log4j</artifactId>
<version>1.2.17</version>
</dependency>
<!-- https://mvnrepository.com/artifact/org.slf4j/slf4j-api -->
<dependency>
<groupId>org.slf4j</groupId>
<artifactId>slf4j-api</artifactId>
<version>1.7.25</version>
</dependency>
<!-- https://mvnrepository.com/artifact/org.slf4j/slf4j-log4j12 -->
<dependency>
<groupId>org.slf4j</groupId>
<artifactId>slf4j-log4j12</artifactId>
<version>1.7.25</version>
</dependency>
<!-- https://mvnrepository.com/artifact/org.apache.commons/commons-lang3 -->
<dependency>
<groupId>org.apache.commons</groupId>
<artifactId>commons-lang3</artifactId>
<version>3.9</version>
</dependency>
<!-- kafka end -->
</dependencies>
<build>
<plugins>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-compiler-plugin</artifactId>
<configuration>
<source>8</source>
<target>8</target>
</configuration>
</plugin>
</plugins>
</build>
</project>
log4j.properties
log4j.rootLogger = info,console
log4j.appender.console = org.apache.log4j.ConsoleAppender
log4j.appender.console.Target = System.out
log4j.appender.console.layout = org.apache.log4j.PatternLayout
log4j.appender.console.layout.ConversionPattern = %p %d{yyyy-MM-dd HH:mm:ss} %c - %m%n
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