測驗代碼
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 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<groupId>com.kaven</groupId>
<artifactId>kafka</artifactId>
<version>1.0-SNAPSHOT</version>
<properties>
<maven.compiler.source>8</maven.compiler.source>
<maven.compiler.target>8</maven.compiler.target>
</properties>
<dependencies>
<dependency>
<groupId>org.apache.kafka</groupId>
<artifactId>kafka-clients</artifactId>
<version>3.0.0</version>
</dependency>
</dependencies>
</project>
創建Topic:
package com.kaven.kafka.admin;
import org.apache.kafka.clients.admin.*;
import org.apache.kafka.common.KafkaFuture;
import java.util.Collections;
import java.util.Map;
import java.util.Properties;
import java.util.concurrent.CountDownLatch;
import java.util.concurrent.ExecutionException;
public class Admin {
// 基于Kafka服務地址與請求超時時間來創建AdminClient實體
private static final AdminClient adminClient = Admin.getAdminClient(
"192.168.1.9:9092,192.168.1.9:9093,192.168.1.9:9094",
"40000");
public static void main(String[] args) throws InterruptedException, ExecutionException {
Admin admin = new Admin();
// 創建Topic,Topic名稱為topic1,磁區副本數為1,復制因子為1
admin.createTopic("topic1", 1, (short) 1);
// 創建Topic,Topic名稱為topic2,磁區副本數為2,復制因子為1
admin.createTopic("topic2", 2, (short) 1);
// 創建Topic,Topic名稱為topic3,磁區副本數為2,復制因子為1
admin.createTopic("topic3", 2, (short) 1);
Thread.sleep(10000);
}
public static AdminClient getAdminClient(String address, String requestTimeoutMS) {
Properties properties = new Properties();
properties.setProperty(AdminClientConfig.BOOTSTRAP_SERVERS_CONFIG, address);
properties.setProperty(AdminClientConfig.REQUEST_TIMEOUT_MS_CONFIG, requestTimeoutMS);
return AdminClient.create(properties);
}
public void createTopic(String name, int numPartitions, short replicationFactor) throws InterruptedException {
CountDownLatch latch = new CountDownLatch(1);
CreateTopicsResult topics = adminClient.createTopics(
Collections.singleton(new NewTopic(name, numPartitions, replicationFactor))
);
Map<String, KafkaFuture<Void>> values = topics.values();
values.forEach((name__, future) -> {
future.whenComplete((a, throwable) -> {
if(throwable != null) {
System.out.println(throwable.getMessage());
}
System.out.println(name__);
latch.countDown();
});
});
latch.await();
}
}
Producer發布訊息:
package com.kaven.kafka.producer;
import org.apache.kafka.clients.producer.*;
import java.util.Properties;
import java.util.concurrent.ExecutionException;
public class ProducerTest {
public static void main(String[] args) throws ExecutionException, InterruptedException {
send("topic1");
send("topic2");
send("topic3");
}
public static void send(String name) throws ExecutionException, InterruptedException {
Producer<String, String> producer = ProducerTest.createProducer();
for (int i = 0; i < 7; i++) {
ProducerRecord<String, String> producerRecord = new ProducerRecord<>(
name,
"key-" + i,
"value-" + i
);
// 異步發送并回呼
producer.send(producerRecord, (metadata, exception) -> {
if(exception == null) {
System.out.printf("topic: %s, partition: %s, offset: %s\n", name, metadata.partition(), metadata.offset());
}
else {
exception.printStackTrace();
}
});
}
// 要關閉Producer實體
producer.close();
}
public static Producer<String, String> createProducer() {
// Producer的配置
Properties properties = new Properties();
// 服務地址
properties.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, "192.168.1.9:9092,192.168.1.9:9093,192.168.1.9:9094");
// KEY的序列化器類
properties.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, "org.apache.kafka.common.serialization.StringSerializer");
// VALUE的序列化器類
properties.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, "org.apache.kafka.common.serialization.StringSerializer");
return new KafkaProducer<>(properties);
}
}
暫停從Partition拉取訊息
Consumer訂閱程式:
package com.kaven.kafka.consumer;
import org.apache.kafka.clients.consumer.*;
import java.time.Duration;
import java.util.*;
public class ConsumerTest {
public static void main(String[] args) throws InterruptedException {
pausePartition(Arrays.asList("topic1", "topic2", "topic3"));
}
public static void pausePartition(List<String> topicList) throws InterruptedException {
KafkaConsumer<String, String> consumer = createConsumer();
consumer.subscribe(topicList);
while (true) {
// 拉取訊息
ConsumerRecords<String, String> records = consumer.poll(Duration.ofMillis(10000));
records.partitions().forEach((partition) -> {
// 從該磁區拉取的訊息
List<ConsumerRecord<String, String>> recordsWithPartition = records.records(partition);
recordsWithPartition.forEach((record) -> {
System.out.printf("topic: %s, partition: %s, offset: %s, key: %s, value: %s\n",
record.topic(), record.partition(), record.offset(), record.key(), record.value());
});
// 暫停拉取磁區1的訊息
if(partition.partition() == 1) {
consumer.pause(Collections.singleton(partition));
}
});
}
}
public static KafkaConsumer<String, String> createConsumer() {
// Consumer的配置
Properties properties = new Properties();
// 服務地址
properties.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, "192.168.1.9:9092,192.168.1.9:9093,192.168.1.9:9094");
// 組ID,用于標識此消費者所屬的消費者組
properties.put(ConsumerConfig.GROUP_ID_CONFIG, "kaven-test");
// 開啟offset自動提交
properties.put(ConsumerConfig.ENABLE_AUTO_COMMIT_CONFIG, "true");
// 消費者offset自動提交到Kafka的頻率(以毫秒為單位)
properties.put(ConsumerConfig.AUTO_COMMIT_INTERVAL_MS_CONFIG, "1000");
// KEY的反序列化器類
properties.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, "org.apache.kafka.common.serialization.StringDeserializer");
// VALUE的反序列化器類
properties.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG, "org.apache.kafka.common.serialization.StringDeserializer");
return new KafkaConsumer<>(properties);
}
}
暫停拉取磁區1的訊息:
// 暫停拉取磁區1的訊息
if(partition.partition() == 1) {
consumer.pause(Collections.singleton(partition));
}
由于是先拉取訊息后再暫停拉取磁區1的訊息,因此開始會拉取磁區1的訊息,之后就只會拉取磁區0(測驗的Topic最多只有兩個磁區)的資訊,
先創建Topic,然后運行Consumer訂閱程式,再使用Producer發布兩次訊息,之后Consumer就可以訂閱到訊息了,輸出如下所示:
// 第一次發布的訊息
topic: topic1, partition: 0, offset: 147, key: key-0, value: value-0
topic: topic1, partition: 0, offset: 148, key: key-1, value: value-1
topic: topic1, partition: 0, offset: 149, key: key-2, value: value-2
topic: topic1, partition: 0, offset: 150, key: key-3, value: value-3
topic: topic1, partition: 0, offset: 151, key: key-4, value: value-4
topic: topic1, partition: 0, offset: 152, key: key-5, value: value-5
topic: topic1, partition: 0, offset: 153, key: key-6, value: value-6
topic: topic2, partition: 0, offset: 84, key: key-1, value: value-1
topic: topic2, partition: 0, offset: 85, key: key-2, value: value-2
topic: topic2, partition: 0, offset: 86, key: key-5, value: value-5
topic: topic2, partition: 0, offset: 87, key: key-6, value: value-6
topic: topic2, partition: 1, offset: 63, key: key-0, value: value-0
topic: topic2, partition: 1, offset: 64, key: key-3, value: value-3
topic: topic2, partition: 1, offset: 65, key: key-4, value: value-4
topic: topic3, partition: 0, offset: 84, key: key-1, value: value-1
topic: topic3, partition: 0, offset: 85, key: key-2, value: value-2
topic: topic3, partition: 0, offset: 86, key: key-5, value: value-5
topic: topic3, partition: 0, offset: 87, key: key-6, value: value-6
topic: topic3, partition: 1, offset: 63, key: key-0, value: value-0
topic: topic3, partition: 1, offset: 64, key: key-3, value: value-3
topic: topic3, partition: 1, offset: 65, key: key-4, value: value-4
// 第二次發布的訊息
topic: topic1, partition: 0, offset: 154, key: key-0, value: value-0
topic: topic1, partition: 0, offset: 155, key: key-1, value: value-1
topic: topic1, partition: 0, offset: 156, key: key-2, value: value-2
topic: topic1, partition: 0, offset: 157, key: key-3, value: value-3
topic: topic1, partition: 0, offset: 158, key: key-4, value: value-4
topic: topic1, partition: 0, offset: 159, key: key-5, value: value-5
topic: topic1, partition: 0, offset: 160, key: key-6, value: value-6
topic: topic2, partition: 0, offset: 88, key: key-1, value: value-1
topic: topic2, partition: 0, offset: 89, key: key-2, value: value-2
topic: topic2, partition: 0, offset: 90, key: key-5, value: value-5
topic: topic2, partition: 0, offset: 91, key: key-6, value: value-6
topic: topic3, partition: 0, offset: 88, key: key-1, value: value-1
topic: topic3, partition: 0, offset: 89, key: key-2, value: value-2
topic: topic3, partition: 0, offset: 90, key: key-5, value: value-5
topic: topic3, partition: 0, offset: 91, key: key-6, value: value-6
輸出符合預期,
恢復從Partition拉取訊息
修改Consumer訂閱程式:
public static void pausePartition(List<String> topicList) throws InterruptedException {
KafkaConsumer<String, String> consumer = createConsumer();
consumer.subscribe(topicList);
// 恢復被暫停拉取訊息的磁區
resume(consumer);
while (true) {
// 拉取訊息
ConsumerRecords<String, String> records = consumer.poll(Duration.ofMillis(10000));
records.partitions().forEach((partition) -> {
// 從該磁區拉取的訊息
List<ConsumerRecord<String, String>> recordsWithPartition = records.records(partition);
recordsWithPartition.forEach((record) -> {
System.out.printf("topic: %s, partition: %s, offset: %s, key: %s, value: %s\n",
record.topic(), record.partition(), record.offset(), record.key(), record.value());
});
});
}
}
// 用于恢復被暫停拉取訊息的磁區
public static void resume(KafkaConsumer<String, String> consumer) {
consumer.resume(consumer.paused());
}
下面這行代碼會恢復所有被暫停拉取的磁區,
consumer.resume(consumer.paused());
運行Consumer訂閱程式,Producer不發布訊息,而Consumer也可以訂閱到訊息,輸出如下所示(可能需要等一會):
topic: topic3, partition: 1, offset: 66, key: key-0, value: value-0
topic: topic3, partition: 1, offset: 67, key: key-3, value: value-3
topic: topic3, partition: 1, offset: 68, key: key-4, value: value-4
topic: topic2, partition: 1, offset: 66, key: key-0, value: value-0
topic: topic2, partition: 1, offset: 67, key: key-3, value: value-3
topic: topic2, partition: 1, offset: 68, key: key-4, value: value-4
很顯然這些訊息是之前被暫停拉取的磁區中的訊息,現在恢復拉取了,訊息就又可以被消費了,因此,可以基于暫停與恢復從Partition拉取訊息來實作Kafka的限流邏輯,Consumer暫停與恢復從Partition拉取訊息就介紹到這里,如果博主有說錯的地方或者大家有不同的見解,歡迎大家評論補充,
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