一、Bug 场景
在一个基于 Java 的日志收集系统中,使用 RabbitMQ 作为消息队列来接收各个应用节点发送的日志消息。随着系统规模的扩大和业务量的增长,日志产生的频率和数据量不断增加。
二、代码示例
生产者代码(简化示例)
java
import com.rabbitmq.client.ConnectionFactory;
import com.rabbitmq.client.Connection;
import com.rabbitmq.client.Channel;
public class LogProducer {
private static final String QUEUE_NAME = "log_queue";
public static void main(String[] argv) throws Exception {
ConnectionFactory factory = new ConnectionFactory();
factory.setHost("localhost");
try (Connection connection = factory.newConnection();
Channel channel = connection.createChannel()) {
channel.queueDeclare(QUEUE_NAME, false, false, false, null);
while (true) {
String logMessage = generateLogMessage();
channel.basicPublish("", QUEUE_NAME, null, logMessage.getBytes("UTF - 8"));
}
}
}
private static String generateLogMessage() {
// 模拟生成日志消息,这里简单返回一个字符串
return "This is a log message";
}
}
消费者代码(简化示例)
java
import com.rabbitmq.client.ConnectionFactory;
import com.rabbitmq.client.Connection;
import com.rabbitmq.client.Channel;
import com.rabbitmq.client.DefaultConsumer;
import com.rabbitmq.client.Envelope;
import com.rabbitmq.client.AMQP;
import java.util.concurrent.TimeUnit;
public class LogConsumer {
private static final String QUEUE_NAME = "log_queue";
public static void main(String[] argv) throws Exception {
ConnectionFactory factory = new ConnectionFactory();
factory.setHost("localhost");
Connection connection = factory.newConnection();
Channel channel = connection.createChannel();
channel.queueDeclare(QUEUE_NAME, false, false, false, null);
channel.basicConsume(QUEUE_NAME, true,
"logConsumerTag",
(consumerTag, delivery) -> {
String logMessage = new String(delivery.getBody(), "UTF - 8");
// 模拟复杂的日志处理逻辑,这里简单休眠一段时间
TimeUnit.SECONDS.sleep(1);
processLogMessage(logMessage);
},
consumerTag -> {
System.out.println("Consumer cancelled: " + consumerTag);
});
}
private static void processLogMessage(String logMessage) {
System.out.println("Processing log message: " + logMessage);
}
}
三、问题描述
- 预期行为:生产者持续发送日志消息到 RabbitMQ 队列,消费者从队列中获取消息并进行处理,系统能够稳定运行,不会出现内存相关的错误。
- 实际行为 :经过一段时间运行后,消费者应用程序抛出
OutOfMemoryError异常。这是因为消费者处理日志消息的速度较慢(这里通过TimeUnit.SECONDS.sleep(1)模拟复杂处理逻辑导致处理速度慢),而生产者发送消息的速度较快,导致 RabbitMQ 队列中的消息不断积压。随着积压消息数量的增加,RabbitMQ 会占用越来越多的内存来存储这些消息。当内存使用达到一定阈值时,RabbitMQ 可能会尝试将部分消息换页到磁盘,但如果换页操作频繁或者磁盘 I/O 性能不佳,再加上 Java 应用自身的内存使用,最终会导致整个 Java 应用出现内存溢出错误。
四、解决方案
- 提高消费者处理能力:优化消费者的日志处理逻辑,减少每条消息的处理时间,从而提高消费者从队列中获取和处理消息的速度,避免消息积压。例如,可以对复杂的日志处理逻辑进行异步化处理,或者采用多线程方式并行处理日志消息。
修改后的消费者代码(多线程处理)
java
import com.rabbitmq.client.ConnectionFactory;
import com.rabbitmq.client.Connection;
import com.rabbitmq.client.Channel;
import com.rabbitmq.client.DefaultConsumer;
import com.rabbitmq.client.Envelope;
import com.rabbitmq.client.AMQP;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
public class LogConsumer {
private static final String QUEUE_NAME = "log_queue";
private static final ExecutorService executor = Executors.newFixedThreadPool(10);
public static void main(String[] argv) throws Exception {
ConnectionFactory factory = new ConnectionFactory();
factory.setHost("localhost");
Connection connection = factory.newConnection();
Channel channel = connection.createChannel();
channel.queueDeclare(QUEUE_NAME, false, false, false, null);
channel.basicConsume(QUEUE_NAME, true,
"logConsumerTag",
(consumerTag, delivery) -> {
String logMessage = new String(delivery.getBody(), "UTF - 8");
executor.submit(() -> processLogMessage(logMessage));
},
consumerTag -> {
System.out.println("Consumer cancelled: " + consumerTag);
});
}
private static void processLogMessage(String logMessage) {
System.out.println("Processing log message: " + logMessage);
}
}
- 设置队列长度限制:在 RabbitMQ 中设置队列的最大长度,当队列达到最大长度时,生产者发送的新消息将被丢弃或者以其他方式处理(如发送到死信队列),防止队列无限增长导致内存耗尽。
修改后的生产者代码(设置队列参数)
java
import com.rabbitmq.client.ConnectionFactory;
import com.rabbitmq.client.Connection;
import com.rabbitmq.client.Channel;
import com.rabbitmq.client.MessageProperties;
import java.util.HashMap;
import java.util.Map;
public class LogProducer {
private static final String QUEUE_NAME = "log_queue";
public static void main(String[] argv) throws Exception {
ConnectionFactory factory = new ConnectionFactory();
factory.setHost("localhost");
try (Connection connection = factory.newConnection();
Channel channel = connection.createChannel()) {
Map<String, Object> args = new HashMap<>();
args.put("x-max-length", 1000); // 设置队列最大长度为 1000
channel.queueDeclare(QUEUE_NAME, false, false, false, args);
while (true) {
String logMessage = generateLogMessage();
channel.basicPublish("", QUEUE_NAME, MessageProperties.PERSISTENT_TEXT_PLAIN, logMessage.getBytes("UTF - 8"));
}
}
}
private static String generateLogMessage() {
// 模拟生成日志消息,这里简单返回一个字符串
return "This is a log message";
}
}
- 启用消息持久化并合理配置磁盘空间:将消息设置为持久化,使 RabbitMQ 在内存不足时可以更有效地将消息持久化到磁盘。同时,确保服务器有足够的磁盘空间来存储这些持久化的消息,并且优化磁盘 I/O 性能。
修改后的生产者代码(消息持久化)
java
import com.rabbitmq.client.ConnectionFactory;
import com.rabbitmq.client.Connection;
import com.rabbitmq.client.Channel;
import com.rabbitmq.client.MessageProperties;
public class LogProducer {
private static final String QUEUE_NAME = "log_queue";
public static void main(String[] argv) throws Exception {
ConnectionFactory factory = new ConnectionFactory();
factory.setHost("localhost");
try (Connection connection = factory.newConnection();
Channel channel = connection.createChannel()) {
channel.queueDeclare(QUEUE_NAME, true, false, false, null);
while (true) {
String logMessage = generateLogMessage();
channel.basicPublish("", QUEUE_NAME, MessageProperties.PERSISTENT_TEXT_PLAIN, logMessage.getBytes("UTF - 8"));
}
}
}
private static String generateLogMessage() {
// 模拟生成日志消息,这里简单返回一个字符串
return "This is a log message";
}
}
通过以上方法,可以有效避免因 RabbitMQ 消息积压导致 Java 应用出现内存溢出的问题,确保系统的稳定运行。