环境

jdk：1.7.0_79

cpu：i5-4570@3.20GHz 4核

eclipse：3.7

操作系统：win7

准备

• log4j:1.7.21

<dependency>
 <groupId>org.slf4j</groupId>
 <artifactId>slf4j-log4j12</artifactId>
 <version>1.7.21</version>
</dependency>

log4j.xml

<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE log4j:configuration SYSTEM "log4j.dtd">
<log4j:configuration xmlns:log4j='http://jakarta.apache.org/log4j/'>
 <appender name="myConsole" class="org.apache.log4j.ConsoleAppender">
 <layout class="org.apache.log4j.PatternLayout">
 <param name="ConversionPattern" value="[%d{dd HH:mm:ss,SSS\} %-5p] [%t] %c{2\} - %m%n" />
 </layout>
 <!--过滤器设置输出的级别 -->
 <filter class="org.apache.log4j.varia.LevelRangeFilter">
 <param name="levelMin" value="debug" />
 <param name="levelMax" value="warn" />
 <param name="AcceptOnMatch" value="true" />
 </filter>
 </appender>
 <appender name="myFile" class="org.apache.log4j.DailyRollingFileAppender">
 <param name="File" value="log4jTest.log" />
 <param name="Append" value="true" />
 <param name="DatePattern" value="'.'yyyy-MM-dd'.log'" />
 <layout class="org.apache.log4j.PatternLayout">
 <param name="ConversionPattern" value="[%t] - %m%n" />
 </layout>
 </appender>
 <appender name="async_file" class="org.apache.log4j.AsyncAppender">
 <param name="BufferSize" value="32" />
 <appender-ref ref="myFile" />
 </appender>
 <logger name="org.logTest" additivity="false">
 <level value="info" />
 <appender-ref ref="async_file" /> <!-- 同步:FILE 异步:async_file -->
 </logger>
</log4j:configuration>

• logback:1.1.7

<dependency>
 <groupId>ch.qos.logback</groupId>
 <artifactId>logback-classic</artifactId>
 <version>1.1.7</version>
</dependency>

logback.xml

<configuration>
 <appender name="STDOUT" class="ch.qos.logback.core.ConsoleAppender">
 <!-- encoder 默认配置为PatternLayoutEncoder -->
 <encoder>
 <pattern>%d{HH:mm:ss.SSS} [%thread] %-5level %logger{36} - %msg%n
 </pattern>
 </encoder>
 </appender>
 <appender name="FILE" class="ch.qos.logback.core.FileAppender">
 <file>testFile.log</file>
 <append>true</append>
 <encoder>
 <pattern>[%t] - %m%n
 </pattern>
 </encoder>
 </appender>
 <!-- 异步输出 -->
 <appender name="ASYNC" class="ch.qos.logback.classic.AsyncAppender">
 <discardingThreshold>0</discardingThreshold>
 <appender-ref ref="FILE" />
 </appender>
 <logger name="org.logTest" level="INFO"
 additivity="false">
 <appender-ref ref="ASYNC" /> <!-- 同步:FILE 异步:ASYNC-->
 </logger>
 <root level="ERROR">
 <appender-ref ref="STDOUT" />
 </root>
</configuration>

• log4j2:2.6.2

<dependency>
 <groupId>org.apache.logging.log4j</groupId>
 <artifactId>log4j-core</artifactId>
 <version>2.6.2</version>
</dependency>
<dependency>
 <groupId>org.apache.logging.log4j</groupId>
 <artifactId>log4j-slf4j-impl</artifactId>
 <version>2.6.2</version>
</dependency>
<dependency>
 <groupId>com.lmax</groupId>
 <artifactId>disruptor</artifactId>
 <version>3.3.4</version>
</dependency>

log4j2.xml

<?xml version="1.0" encoding="UTF-8"?>
<!--设置log4j2的自身log级别为warn -->
<configuration status="warn">
 <appenders>
 <console name="Console" target="SYSTEM_OUT">
 <PatternLayout pattern="[%d{HH:mm:ss:SSS}] [%p] - %l - %m%n" />
 </console>
 <RollingFile name="RollingFileInfo" fileName="info.log"
 filePattern="${sys:user.home}/logs/hpaasvc/$${date:yyyy-MM}/info-%d{yyyy-MM-dd}-%i.log">
 <Filters>
 <ThresholdFilter level="INFO" />
 <ThresholdFilter level="WARN" onMatch="DENY"
 onMismatch="NEUTRAL" />
 </Filters>
 <PatternLayout pattern="[%t] - %m%n" />
 <Policies>
 <TimeBasedTriggeringPolicy />
 <SizeBasedTriggeringPolicy size="100 MB" />
 </Policies>
 </RollingFile>
 <RandomAccessFile name="RandomAccessFile" fileName="asyncWithLocation.log"
 immediateFlush="false" append="true">
 <PatternLayout>
 <Pattern>[%t] - %m%n</Pattern>
 </PatternLayout>
 </RandomAccessFile>
 </appenders>
 <loggers>
 <!-- <AsyncLogger name="asynLogger" level="trace"
 includeLocation="true">
 <AppenderRef ref="RandomAccessFile" />
 </AsyncLogger> -->
 <Root level="info" includeLocation="true">
 <AppenderRef ref="RollingFileInfo" />
 </Root>
 </loggers>
</configuration>

测试

准备50条线程同时记录1000000条数据，然后统计时间，详细代码如下：

import java.util.concurrent.CountDownLatch;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
public class App {
 private static Logger log = LoggerFactory.getLogger(App.class);
 public static void main(String[] args) throws InterruptedException {
 int messageSize = 1000000;
 int threadSize = 50;
 final int everySize = messageSize / threadSize;
 final CountDownLatch cdl = new CountDownLatch(threadSize);
 long startTime = System.currentTimeMillis();
 for (int ts = 0; ts < threadSize; ts++) {
 new Thread(new Runnable() {
 @Override
 public void run() {
 for (int es = 0; es < everySize; es++) {
 log.info("======info");
 }
 cdl.countDown();
 }
 }).start();
 }
 cdl.await();
 long endTime = System.currentTimeMillis();
 System.out.println("log4j1:messageSize = " + messageSize
 + ",threadSize = " + threadSize + ",costTime = "
 + (endTime - startTime) + "ms");
 }
}

log4j1和logback的同步和异步分别修改为对应的appender就行了

log4j2的异步方式提供了2中模式：

1.全局开启

设置Log4jContextSelector系统属性为：

org.apache.logging.log4j.core.async.AsyncLoggerContextSelector

System.setProperty("Log4jContextSelector", "org.apache.logging.log4j.core.async.AsyncLoggerContextSelector");

2.混合同步异步模式

不需要设置Log4jContextSelector，但是需要使用AsyncLogger标签

更多详细参考官方文档：http://logging.apache.org/log4j/2.x/manual/async.html#AllAsync

结果

分别测试完以后统计成表格如下：

log4j2的异步模式表现了绝对的性能优势，优势主要得益于Disruptor框架的使用

LMAX Disruptor technology. Asynchronous Loggers internally use the Disruptor, a lock-free inter-thread communication library, instead of queues, resulting in higher throughput and lower latency.

一个无锁的线程间通信库代替了原来的队列

更多Disruptor ：