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  • 还在用 Log4j ?快用 Log4j2,性能太猛了!

    环境

    jdk:1.7.0_79

    cpu:i5-4570@3.20GHz 4核

    eclipse:3.7

    操作系统:win7

    准备

    1.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>
    

    2.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>
    

    3.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 :

    http://developer.51cto.com/art/201306/399370.htm

    http://ifeve.com/disruptor/

    来源:https://my.oschina.net/OutOfMemory/blog/789267

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  • 原文地址:https://www.cnblogs.com/javastack/p/15247170.html
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