前文已经讲了log4j2的AsyncAppender的实现【log4j2异步日志解读（一）AsyncAppender】，今天我们看看AsyncLogger的实现。

看了这个图，应该很清楚AsyncLogger调用Disruptor，然后直接返回。至于高性能队列 这里已经展开讲了是如何实现的。

AsyncLogger的调用流程

 

我们来看看AsyncLogger的调用流程，log.info()首先会调用抽象类AbstractLogger，然后调用了Logger的logMessage。

//Logger.java
    @Override
    public void logMessage(final String fqcn, final Level level, final Marker marker, final Message message,
            final Throwable t) {
        final Message msg = message == null ? new SimpleMessage(Strings.EMPTY) : message;
        final ReliabilityStrategy strategy = privateConfig.loggerConfig.getReliabilityStrategy();
        strategy.log(this, getName(), fqcn, marker, level, msg, t);
    }

strategy.log是调用了ReliabilityStrategy接口，日志事件传递到适当的appender的对象的接口，然后调用了LoggerConfig.log()方法，来创建有关记录消息的上下文信息。

//LoggerConfig.java
    @PerformanceSensitive("allocation")
    public void log(final String loggerName, final String fqcn, final Marker marker, final Level level,
            final Message data, final Throwable t) {
        List<Property> props = null;
        if (!propertiesRequireLookup) {
            props = properties;
        } else {
            if (properties != null) {
                props = new ArrayList<>(properties.size());
                final LogEvent event = Log4jLogEvent.newBuilder()
                        .setMessage(data)
                        .setMarker(marker)
                        .setLevel(level)
                        .setLoggerName(loggerName)
                        .setLoggerFqcn(fqcn)
                        .setThrown(t)
                        .build();
                for (int i = 0; i < properties.size(); i++) {
                    final Property prop = properties.get(i);
                    final String value = prop.isValueNeedsLookup() // since LOG4J2-1575
                            ? config.getStrSubstitutor().replace(event, prop.getValue()) //
                            : prop.getValue();
                    props.add(Property.createProperty(prop.getName(), value));
                }
            }
        }
        final LogEvent logEvent = logEventFactory.createEvent(loggerName, marker, fqcn, level, data, props, t);
        try {
            log(logEvent, LoggerConfigPredicate.ALL);
        } finally {
            // LOG4J2-1583 prevent scrambled logs when logging calls are nested (logging in toString())
            ReusableLogEventFactory.release(logEvent);
        }
    }

接着我们来看AsyncLoggerConfig.logToAsyncDelegate()方法，首先会调用Disruptor，放入环形队列。如果环形队列阻塞，则执行等待策略。

//AsyncLoggerConfig.java
    private void logToAsyncDelegate(LogEvent event) {
        if (!isFiltered(event)) {
            // Passes on the event to a separate thread that will call
            // asyncCallAppenders(LogEvent).
            populateLazilyInitializedFields(event);
            if (!delegate.tryEnqueue(event, this)) {
                //如果获取Disruptor队列需要等待则执行等待策略，这里类似AsyncAppender等待策略
                handleQueueFull(event);
            }
        }
    }

    private void handleQueueFull(final LogEvent event) {
        if (AbstractLogger.getRecursionDepth() > 1) { // LOG4J2-1518, LOG4J2-2031
            // If queue is full AND we are in a recursive call, call appender directly to prevent deadlock
            AsyncQueueFullMessageUtil.logWarningToStatusLogger();
            logToAsyncLoggerConfigsOnCurrentThread(event);
        } else {
            // otherwise, we leave it to the user preference
            final EventRoute eventRoute = delegate.getEventRoute(event.getLevel());
            // 1、DefaultAsyncQueueFullPolicy---等待队列，转为同步操作策略
            // 2、DiscardingAsyncQueueFullPolicy---按照日志等级抛弃日志策略
            eventRoute.logMessage(this, event);
        }
    }

然后再来看看Disruptor写入 的过程。LogEvent是记录消息的上下文信息的接口，然后调用tryPublishEvent去获取环形队列的位置，然后发布数据到环形队列上。这一块具体可以看笔者前文Disruptor源码分析，这里就不展开讨论。

//AsyncLoggerConfigDisruptor.java
    @Override
    public boolean tryEnqueue(final LogEvent event, final AsyncLoggerConfig asyncLoggerConfig) {
        final LogEvent logEvent = prepareEvent(event);
        return disruptor.getRingBuffer().tryPublishEvent(translator, logEvent, asyncLoggerConfig);
    }

日志的消费过程，定义RingBufferLogEventHandler类实现Disruptor的SequenceReportingEventHandler的onEvent方法，从ringbuffer读取事件进行处理。最后会调用该logger绑定的默认appender输出。

最后提供下笔者测试demo

<?xml version="1.0" encoding="UTF-8"?>
<Configuration status="WARN" monitorInterval="30">
    <Appenders>
        <RollingRandomAccessFile name="applicationAppender" fileName="./log/application.log"
                                 filePattern="./log/$${date:yyyy-MM}/common-%d{yyyy-MM-dd}.log.gz"
                                 append="false">
            <PatternLayout pattern="[%d{yyyy-MM-dd HH:mm:ss.SSS}] [%p] - %l - %m%n"/>
            <Policies>
                <TimeBasedTriggeringPolicy/>
            </Policies>
        </RollingRandomAccessFile>

        <Console name="CONSOLE" target="SYSTEM_OUT">
            <PatternLayout pattern="[%d{yyyy-MM-dd HH:mm:ss.SSS}] [%p] %t - %l - %m%n"/>
        </Console>

        <!-- AsyncAppender配置 -->
        <!--<Async name="asyncTest" blocking="true">-->
            <!--<AppenderRef ref="applicationAppender"/>-->
        <!--</Async>-->

    </Appenders>

    <Loggers>
        <!-- AsyncLogger配置 -->
        <AsyncLogger name="log4j2" >
            <AppenderRef ref="applicationAppender"/>
        </AsyncLogger>

        <Root level="info">
            <!--<AppenderRef ref="CONSOLE"/>-->
            <AppenderRef ref="applicationAppender"/>
        </Root>

        <!--<Logger name="log4j2" level="debug" additivity="false" >-->
            <!--<AppenderRef ref="CONSOLE"/>-->
            <!--<AppenderRef ref="applicationAppender"/>-->
        <!--</Logger>-->

    </Loggers>
</Configuration>

 

总结

1、Log4j 2的异步记录日志在一定程度上提供更好的吞吐量，但是一旦队列已满，appender线程需要等待，这个时候就需要设置等待策略，AsyncAppender是依赖于消费者最序列最后的消费者，会持续等待。至于异步性能图可以看下官方提供的吞吐量比较图，差异很明显。

2、因为AsyncAppender是采用Disruptor，通过环形队列无阻塞队列作为缓冲，多生产者多线程的竞争是通过CAS实现，无锁化实现，可以降低极端大的日志量时候的延迟尖峰，Disruptor 可是号称一个线程里每秒处理600万订单的高性能队列。

 

版权声明：本文为lewis09原创文章，遵循 CC 4.0 BY-SA 版权协议，转载请附上原文出处链接和本声明。
本文链接：https://www.cnblogs.com/lewis09/p/10004117.html