在高并发的应用场景中,秒杀系统等业务可能导致Redis与MySQL中的数据不一致。通过异步更新通知,我们可以及时发现不一致并采取相应措施,确保系统的稳定性和一致性。
我们将设计一个Java程序,定期巡检Redis和MySQL中的库存数据。当发现不一致时,通过Kafka发送异步通知,以便其他系统及时进行处理。
首先,确保在项目的pom.xml
文件中添加以下Maven依赖:
<dependencies>
<!-- MySQL连接驱动 -->
<dependency>
<groupId>mysql</groupId>
<artifactId>mysql-connector-java</artifactId>
<version>8.0.23</version>
</dependency>
<!-- Jedis:Java连接Redis的客户端库 -->
<dependency>
<groupId>redis.clients</groupId>
<artifactId>jedis</artifactId>
<version>3.7.0</version>
</dependency>
<!-- Kafka客户端 -->
<dependency>
<groupId>org.apache.kafka</groupId>
<artifactId>kafka-clients</artifactId>
<version>2.8.1</version>
</dependency>
</dependencies>
import org.apache.kafka.clients.producer.KafkaProducer;
import org.apache.kafka.clients.producer.ProducerRecord;
import redis.clients.jedis.Jedis;
import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.PreparedStatement;
import java.sql.ResultSet;
import java.sql.SQLException;
import java.util.Properties;
import java.util.Timer;
import java.util.TimerTask;
public class AsyncInventoryNotifier {
// Redis连接信息
private static final String REDIS_HOST = "localhost";
private static final int REDIS_PORT = 6379;
private static final int REDIS_DB = 0;
// MySQL连接信息
private static final String MYSQL_URL = "jdbc:mysql://localhost:3306/ecommerce";
private static final String MYSQL_USER = "user";
private static final String MYSQL_PASSWORD = "password";
// Kafka连接信息
private static final String KAFKA_BROKER = "localhost:9092";
private static final String KAFKA_TOPIC = "inventory_updates";
public static void main(String[] args) {
// 创建定时任务
Timer timer = new Timer();
timer.schedule(new InventoryNotifierTask(), 0, 30 * 60 * 1000); // 每30分钟执行一次
}
static class InventoryNotifierTask extends TimerTask {
@Override
public void run() {
System.out.println("Starting async inventory notification...");
try {
// 连接Redis
Jedis jedis = new Jedis(REDIS_HOST, REDIS_PORT);
jedis.select(REDIS_DB);
// 连接MySQL
Connection mysqlConnection = DriverManager.getConnection(MYSQL_URL, MYSQL_USER, MYSQL_PASSWORD);
// 连接Kafka
Properties kafkaProps = new Properties();
kafkaProps.put("bootstrap.servers", KAFKA_BROKER);
kafkaProps.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer");
kafkaProps.put("value.serializer", "org.apache.kafka.common.serialization.StringSerializer");
KafkaProducer<String, String> producer = new KafkaProducer<>(kafkaProps);
// 查询所有商品ID
PreparedStatement preparedStatement = mysqlConnection.prepareStatement("SELECT id FROM products");
ResultSet resultSet = preparedStatement.executeQuery();
while (resultSet.next()) {
int productId = resultSet.getInt("id");
// 从Redis获取缓存库存
int redisStock = Integer.parseInt(jedis.get("product:" + productId + ":stock"));
// 从MySQL获取实际库存
PreparedStatement stockStatement = mysqlConnection.prepareStatement("SELECT stock FROM products WHERE id = ?");
stockStatement.setInt(1, productId);
ResultSet stockResultSet = stockStatement.executeQuery();
int mysqlStock = 0;
if (stockResultSet.next()) {
mysqlStock = stockResultSet.getInt("stock");
}
// 检测库存一致性
if (redisStock != mysqlStock) {
System.out.println("Inventory inconsistency detected for product " + productId +
". Redis: " + redisStock + ", MySQL: " + mysqlStock);
// 发送异步通知到Kafka
ProducerRecord<String, String> record = new ProducerRecord<>(KAFKA_TOPIC, String.valueOf(productId), "inventory_inconsistency");
producer.send(record);
System.out.println("Async notification sent to Kafka.");
}
}
// 关闭连接
jedis.close();
mysqlConnection.close();
producer.close();
} catch (SQLException e) {
System.err.println("Error during async inventory notification: " + e.getMessage());
}
}
}
}
连接到Redis、MySQL和Kafka:
Jedis jedis = new Jedis(REDIS_HOST, REDIS_PORT);
jedis.select(REDIS_DB);
Connection mysqlConnection = DriverManager.getConnection(MYSQL_URL, MYSQL_USER, MYSQL_PASSWORD);
Properties kafkaProps = new Properties();
kafkaProps.put("bootstrap.servers", KAFKA_BROKER);
kafkaProps.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer");
kafkaProps.put("value.serializer", "org.apache.kafka.common.serialization.StringSerializer");
KafkaProducer<String, String> producer = new KafkaProducer<>(kafkaProps);
查询商品ID并检测库存一致性:
PreparedStatement preparedStatement = mysqlConnection.prepareStatement("SELECT id FROM products");
ResultSet resultSet = preparedStatement.executeQuery();
while (resultSet.next()) {
int productId = resultSet.getInt("id");
int redisStock = Integer.parseInt(jedis.get("product:" + productId + ":stock"));
PreparedStatement stockStatement = mysqlConnection.prepareStatement("SELECT stock FROM products WHERE id = ?");
stockStatement.setInt(1, productId);
ResultSet stockResultSet = stockStatement.executeQuery();
int mysqlStock = 0;
if (stockResultSet.next()) {
mysqlStock = stockResultSet.getInt("stock");
}
if (redisStock != mysqlStock) {
// 发送异步通知到Kafka
ProducerRecord<String, String> record = new ProducerRecord<>(KAFKA_TOPIC, String.valueOf(productId), "inventory_inconsistency");
producer.send(record
); System.out.println(“Async notification sent to Kafka.”); } }
3. **异步通知:**
```java
ProducerRecord<String, String> record = new ProducerRecord<>(KAFKA_TOPIC, String.valueOf(productId), "inventory_inconsistency");
producer.send(record);
System.out.println("Async notification sent to Kafka.");
关闭连接:
jedis.close();
mysqlConnection.close();
producer.close();
通过这个异步更新通知的设计,我们能够在检测到Redis与MySQL数据不一致的情况时,及时发送异步通知到Kafka,以便其他系统能够实时处理这些不一致性。这种设计适用于高并发应用场景,可以在实际生产环境中部署并根据业务需求调整执行频率。