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log4j2异步日志配置

一、asyncLogger和asyncRootLogger的异同

在使用log4j2异步日志配置时,可以使用asyncLogger和asyncRootLogger两个配置项来实现异步日志记录。两者的主要区别在于asyncRootLogger会记录所有的日志事件,而asyncLogger仅记录指定了级别的日志事件。asyncRootLogger的默认级别为ERROR,而asyncLogger的默认级别为DEBUG。

示例代码:

<Configuration status="debug" name="AsyncAppenders">
  <Appenders>
    <Async name="Async">
      <AppenderRef ref="SomeAppender"/>
    </Async>
  </Appenders>
  <Loggers>
    <AsyncLogger name="com.foo.Bar" level="debug" includeLocation="true">
      <AppenderRef ref="Async"/>
    </AsyncLogger>
    <AsyncRoot level="error">
      <AppenderRef ref="Async"/>
    </AsyncRoot>
  </Loggers>
</Configuration>

二、异步日志队列的配置

在log4j2异步日志配置中,可以通过配置异步日志队列来实现更好的性能。包括BlockingQueue、LinkedBlockingQueue和ArrayBlockingQueue在内的多种队列实现都被支持。BlockingQueue可以无限制地添加新的元素,LinkedBlockingQueue限制队列大小为Integer.MAX_VALUE,而ArrayBlockingQueue则需要指定队列的大小。

示例代码:

<Configuration status="debug" name="AsyncAppenders">
  <Appenders>
    <Async name="Async">
      <AppenderRef ref="SomeAppender"/>
      <BlockingQueueFactory>
        <ArrayBlockingQueue>
          <capacity>1000</capacity>
        </ArrayBlockingQueue>
      </BlockingQueueFactory>
    </Async>
  </Appenders>
  <Loggers>
    <AsyncLogger name="com.foo.Bar" level="debug" includeLocation="true">
      <AppenderRef ref="Async"/>
      <BlockingQueueFactory>
        <LinkedBlockingQueue/>
      </BlockingQueueFactory>
    </AsyncLogger>
  </Loggers>
</Configuration>

三、异步日志并发线程数的配置

在log4j2异步日志配置中,可以通过配置异步日志的并发线程数来控制日志的处理速度。可以指定最小、最大、以及线程池名称等参数。如果不指定最大线程数值,默认为2147483647。

示例代码:

<Configuration status="debug" name="AsyncAppenders">
  <Appenders>
    <Async name="Async">
      <AppenderRef ref="SomeAppender"/>
      <BlockingQueueFactory>
        <ArrayBlockingQueue>
          <capacity>1000</capacity>
        </ArrayBlockingQueue>
      </BlockingQueueFactory>
      <AsyncQueueFullPolicy>
        <DiscardPolicy/>
      </AsyncQueueFullPolicy>
      <AsyncLoggerConfig>
        <ContextStackFactory>
          <ThreadContextStackFactory/>
        </ContextStackFactory>
        <ThreadName>AsyncLoggerConfig</ThreadName>
        <Level>info</Level>
        <Properties>
          <Property name="vendor">Apache</Property>
          <Property name="product">MyApp</Property>
        </Properties>
      </AsyncLoggerConfig>
      <disruptor>
        <WaitStrategy>BlockingWait</WaitStrategy>
        <RingBufferSize>262144</RingBufferSize>
        <ClaimStrategy>SingleThreaded</ClaimStrategy>
        <BufferSize>32768</BufferSize>
      </disruptor>
      <ThreadProperties>
        <Property name="ThreadPriority">5</Property>
      </ThreadProperties>
      <executor>
        <ThreadFactory>
          <name>MyThread</name>
          <priority>1</priority>
        </ThreadFactory>
        <core>1</core>
        <max>4</max>
        <keepAliveMillis>1000</keepAliveMillis>
        <shutdownTimeout>5000</shutdownTimeout>
        <BlockingQueueFactory>
          <LinkedBlockingQueue/>
        </BlockingQueueFactory>
      </executor>
    </Async>
  </Appenders>
  <Loggers>
    <AsyncRoot level="error">
      <AppenderRef ref="Async"/>
    </AsyncRoot>
  </Loggers>
</Configuration>

四、异步日志的discard_policy属性

在使用log4j2异步日志配置时,可以通过discard_policy属性来控制队列满时的行为。默认情况下,队列满时会阻塞,然后等待空闲状态。用户可以通过discard_policy属性,选择在队列满时直接抛弃最早的一条日志,或者抛弃最新的一条日志。

示例代码:

<Async name="async">
  ...
  <AsyncQueueFullPolicy>
    <DiscardPolicy/>
  </AsyncQueueFullPolicy>
  ...
</Async>

五、异步日志的性能测试

下面是异步日志的性能测试代码。可以通过测试代码来验证使用异步日志配置后的性能优化效果。

package com.jeff.example;

import org.apache.logging.log4j.LogManager;
import org.apache.logging.log4j.Logger;
import org.apache.logging.log4j.ThreadContext;

public class AsyncLoggerPerformanceTest {
    public static void main(String[] args) {
        Runnable task = new Runnable() {
            @Override
            public void run() {
                Logger logger = LogManager.getLogger("async");
                int count = 0;
                while (count++ < 100000) {
                    logger.info("count: " + count);
                }
            }
        };
        
        Thread t1 = new Thread(task);
        Thread t2 = new Thread(task);
        
        t1.start();
        t2.start();
    }
}