https://blog.csdn.net/szx1999/article/details/50073857

7. 写日志会影响系统性能吗?

写日志必然是会消耗一定资源的,而RollingFileAppender也不是线程安全的。为了减小log4net影响系统性能的嫌疑,我们加入lockingModel参数,使用FileAppender.MinimalLock来减少并发时发生死锁的概率:

<param name="lockingModel" type="log4net.Appender.FileAppender+MinimalLock" />

尽管如此,文件的I/O始终是耗性能的,有没有办法缓存一批日志,然后一次性写入文件呢?BufferingForwardingAppender正是为此而生,我们下章再介绍如何使用它。

https://stackoverflow.com/questions/11319319/log4net-bufferingforwardingappender-performance-issue

I found out the issue.

The BufferingForwardingAppender is inheriting from BufferingAppenderSkeleton (as are other appenders making use of logging events buffering such as AdoNetAppender, RemotingAppender, SmtpAppender ..).

The BufferingAppenderSkeleton is actually buffering logging events before actually delivering them to the target appender once a certain condition is met (buffer full for example).

According to documentation of the LoggingEvent class (representing a logging event, and containing all values (message, threadid ...) of the event) :

Some logging events properties are considered "volatile", that is the values are correct at the time the event is delivered to appenders, but will not be consistent at any time afterwards. If an event is to be stored and the processed at a later time, these volatile values must be fixed bycalling FixVolatileData. There is a performance penalty incurred by calling FixVolatileData but is is essential to maintain data consistency

These "volatile" properties are represented by the FixFlags enumeration containing flags such as Message, ThreadName, UserName, Identity ... so all volatile properties. It also contains the flag "None" (fix no properties), "All" (fix all properties) and "Partial" (fix only a certain predefine dset of properties).

Whem the BufferingAppenderSkeleton is instanciated, by DEFAULT it sets the fixing to "All" meaning that all "volatile" properties should be fixed.

In that context, for each LoggingEvent appended into the BufferingAppenderSkeleton, ALL "volatile" properties will be fixed before the event is inserted in the buffer. This includes the properties Identity (username) and LocationInformation (stack trace) even if these properties are not included in the layout (but I guess it makes some kind of sense if the layout is changed to include these properties at a later time while a buffer has been already been filled with LoggingEvents).

However in my case this really HURTS performance. I am not including the Identity and LocationInformation in my layout and don't plan to (mainly for performance issues)

Now for the solution ...

There are two properties in BufferingAppenderSkeleton which can be used to control the FixFlags flag value of the BufferingAppenderSkeleton (once again by default it is set to "ALL" which is not very nice !). These two properties are Fix (FixFlags type) and OnlyFixPartialEventData (bool type).

For a fine tune of the flag value or to disable all fix, the Fix property should be used. For a specific partial predefined combination of flags (not including Identity or LocationInfo), the OnlyFixPartialEventData can be used instead by setting it to "true".

If I reuse the configuration sample above (in my question), the only change made to the configuration to unleash performance is indicated below:

<appender name="BufferingForwardingAppender" type="log4net.Appender.BufferingForwardingAppender">
<bufferSize value="512" />
<appender-ref ref="RollingLogFileAppender" />
<Fix value="0"/> <!-- Set Fix flag to NONE -->
</appender>

Using this modified configuration, the benchmark code execution presented in my question above, is dropping from approx 14000ms to 230ms (60X faster) ! And if I use <OnlyFixPartialEventData value="true"/> instead of disabling all fix it is taking approx 350ms.

Sadly, this flag is not very well documented (except in the SDK documentation, a little bit) .. so I had to dig deep into log4net sources to find the issue.

This is particularly problematic especially in the "reference" configuration samples, this flag appears nowhere (http://logging.apache.org/log4net/release/config-examples.html). So the samples provided for BufferingForwardingAppender, and AdoNetAppender (and other appenders inheriting from BufferingAppenderSkeleton) will give TERRIBLE performance to users, even if the layout they are using is pretty minimal.

https://www.cnblogs.com/wigis/p/5023229.html

http://www.nimaara.com/2016/01/01/high-performance-logging-log4net/

https://github.com/NimaAra/Easy.Logger

Problems with BufferingForwardingAppender

The BufferingForwardingAppender only flushes its events once the bufferSize is full unless you specify lossy to be true so this means if you have an application producing a single log event every 1 second you would have to wait 512 seconds for the batch to be flushed out. This may not be a problem for you and if it is not then I highly recommend using this forwarder as it has great GC and CPU performance but if you need real-time monitoring of every log entry and a higher throughput then continue reading.

Another point we should be aware of is that this forwarder is not asynchronous it merely batches the events so the application thread(s) producing the log events will be blocked while the buffer is being flushed out.

The solution

Having considered the points above, I thought I could do better so say hello to my little friend AsyncBufferingForwardingAppender.

This buffering forwarder uses a worker thread which batches up and flushes the log events in the background, it also detects if it has been idle meaning if there has not been enough log events to cause the buffer to be flushed it will invoke a manual flush which addresses the problem I mentioned above and since it is developed as a forwarder you can add additional appenders to it for example it can forward the log events to the ConsoleDB or any other appender that you might have all at the same time.

BufferingForwardingAppender in log4net的更多相关文章

  1. log4net的各种Appender配置示例

    Apache log4net™ Config Examples Overview This document presents example configurations for the built ...

  2. Log4net 日志使用介绍

    概述 Log4net 有三个主要组件:loggers,appenders 和 layouts.这三个组件一起工作使得开发者能够根据信息类型和等级(Level)记录信息,以及在运行时控制信息的格式化和信 ...

  3. log4net学习笔记

    一直想找一个好用的日子类,今天偶然的机会看到了log4net这个类库,过来学习一下. log4net是.NET框架下的一个日子类库,官网是http://logging.apache.org/log4n ...

  4. log4net日志组件

    转载:http://www.cnblogs.com/knowledgesea/archive/2012/04/26/2471414.html 一.什么是log4net组件 Log4net是基于.net ...

  5. Apache log4net™ Config Examples

    Overview This document presents example configurations for the built-in appenders. These configurati ...

  6. Log4net 日志

    Log4net 日志使用介绍 概述 Log4net 有三个主要组件:loggers,appenders 和 layouts.这三个组件一起工作使得开发者能够根据信息类型和等级(Level)记录信息,以 ...

  7. log4net性能小探

    初步测试了Log4性能.Appender架构如下. 一般客户端,使用FileAppender,把Log记录在本地磁盘. <lockingModel type="log4net.Appe ...

  8. Log4net_配置

    Log4net 有三个主要组件:loggers,appenders 和 layouts.这三个组件一起工作使得开发者能够根据信息类型和等级(Level)记录信息,以及在运行时控制信息的格式化和信息的写 ...

  9. log4net使用手册

    1. log4net简介 log4net是.Net下一个非常优秀的开源日志记录组件.log4net记录日志的功能非常强大.它可以将日志分不同的等级,以不同的格式,输出到不同的媒介.Java平台下,它还 ...

随机推荐

  1. 如何通过sequel pro导入.sql脚本

    1.参考地址     https://zhidao.baidu.com/question/985373253463808219.html

  2. Dmidecode

    一.Dmidecode简介 DMI (Desktop Management Interface, DMI)就是帮助收集电脑系统信息的管理系统,DMI信息的收集必须在严格遵照SMBIOS规范的前提下进行 ...

  3. jQuery EasyUI的各历史版本和应用

    from:http://blog.sina.com.cn/s/blog_b8be6dc40102xpe6.html 各历史版本下载地址: http://www.jeasyui.com/download ...

  4. 基于ormlite创建数据库存储数据案例

    一直不知道安卓创建数据库存储数据,以前遇到过,但是没有深入研究,今天仔细的看了一下,学习到了一点知识 直接看代码了 public class DatabaseHelper extends OrmLit ...

  5. 《从零开始学Swift》学习笔记(Day2)——使用Web网站编写Swift代码

    Swift 2.0学习笔记——使用Web网站编写Swift代码 原创文章,欢迎转载.转载请注明:关东升的博客 Swift程序不能在Windows其他平台编译和运行,有人提供了一个网站swiftstub ...

  6. 调用第三方物流公司API即时查询物流信息

    主要是利用快递鸟提供的物流服务,通过对接快递鸟的API,调用即时查询接口,获取物流信息. 这里采用java语言,调用快递鸟的接口为例.步骤如下: 1.首先,得去快递鸟的官方网站注册一个账号并进行实名认 ...

  7. GPU instancing

    参考 https://www.cnblogs.com/hont/p/7143626.html github地址 https://github.com/yingsz/instancing/ 补充2点: ...

  8. MySQL中有关icp mrr和bka的特性

    文辉考我的问题,有关这三个的特性,如果在面试过程中,个人见解可以答以下 icp MyQL数据库会在取出索引的同时,判断是否进行WHERE条件过滤,也就是把WHERE的部分过滤操作放在存储引擎层,在某些 ...

  9. python模块学习(四)

    re模块 就其本质而言,正则表达式(或 RE)是一种小型的.高度专业化的编程语言,(在Python中)它内嵌在Python中,并通过 re 模块实现.正则表达式模式被编译成一系列的字节码,然后由用 C ...

  10. Linux中的输出重定向

    标准输入输出: 键盘        /dev/stdin        0       标准输入 显示器    /dev/stdout      1       标准输出 显示器    /dev/st ...