blocks|key|4411959|text|这完全取决于您添加了多少日志语句。如果您在每一行代码之后添加日志记录，那么性能肯定会降低。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|4411960|在重要情况下使用日志记录，为当前目的(测试或实际部署)设置正确的日志记录级别，并使用如下结构|4411961|if+(Logger.isDebugEnabled())+{
+++Logger.debug("Value+is+"+%2B+costlyOperation()")
}|code-block|syntax|javascript|4411962|以避免调用运行成本较高的代码。|4411963|您可能还想检查this+article|offset|length|4411964|entityMap|0|LINK|mutability|MUTABLE|url|http://www.ibm.com/developerworks/java/library/j-logging/^0|0|0|0|0|7|C|0|0^^$0|@$1|2|3|4|5|6|7|W|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|X|8|@]|9|@]|A|$]]|$1|D|3|E|5|F|7|Y|8|@]|9|@]|A|$G|H]]|$1|I|3|J|5|6|7|Z|8|@]|9|@]|A|$]]|$1|K|3|L|5|6|7|10|8|@]|9|@$M|11|N|12|1|13]]|A|$]]|$1|O|3|-4|5|6|7|14|8|@]|9|@]|A|$]]]|P|$Q|$5|R|S|T|A|$U|V]]]]

It all depends on how much log statements you add. If you add logging after every line of code then performance will must certainly degrade. 

Use logging for the important cases, set the correct logging level for your current purposes (testing or actual deployment) and use constructions like

<pre><code>if (Logger.isDebugEnabled()) {
 Logger.debug("Value is " + costlyOperation()")
}
</code></pre>

to avoid calling code that is costly to run.

You might also want to check <a href="http://www.ibm.com/developerworks/java/library/j-logging/" rel="nofollow">this article</a>

blocks|key|2621053|text|为了避免像“视情况而定”或“有点”之类的笼统说法，你应该在有和没有日志开销的情况下测量应用程序的性能。Apache+JMeter可以帮助您为测试生成负载。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|2621054|您可以通过日志记录收集的信息通常对应用程序的完整性非常重要，因此您不能盲目操作。如果你使用Google+Analytics，也会有轻微的开销，但好处占上风。|2621055|为了使您的日志文件保持在合理的大小内，您可以始终使用轮换日志文件。|2621056|entityMap|0|LINK|mutability|MUTABLE|url|http://jakarta.apache.org/jmeter/^0|1F|D|0|0|0|0^^$0|@$1|2|3|4|5|6|7|P|8|@]|9|@$A|Q|B|R|1|S]]|C|$]]|$1|D|3|E|5|6|7|T|8|@]|9|@]|C|$]]|$1|F|3|G|5|6|7|U|8|@]|9|@]|C|$]]|$1|H|3|-4|5|6|7|V|8|@]|9|@]|C|$]]]|I|$J|$5|K|L|M|C|$N|O]]]]

In order to avoid generalities like "it depends" or "a little" etc. you should measure the performance of your application with and without the logging overhead. <a href="http://jakarta.apache.org/jmeter/" rel="nofollow">Apache JMeter</a> can help you generate the load for the test.

The information you can collect through logging is usually so essential for the integrity of the application, that you can not operate blindly. There is also a slight overhead if you use Google Analytics, but the benefits prevail. 

In order to keep your log files within reasonable sizes, you can always use rotating log files.

blocks|key|4411995|text|我认为JavaRevisited博客上有一篇关于性能问题的很好的文章：Top+10+Tips+on+Logging+in+Java|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|4411996|entityMap|0|LINK|mutability|MUTABLE|url|http://javarevisited.blogspot.com/2011/05/top-10-tips-on-logging-in-java.html^0|Z|U|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@$A|M|B|N|1|O]]|C|$]]|$1|D|3|-4|5|6|7|P|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]]]

I think that JavaRevisited blog has a pretty good post on a problem with performance: <a href="http://javarevisited.blogspot.com/2011/05/top-10-tips-on-logging-in-java.html" rel="nofollow">Top 10 Tips on Logging in Java</a>

blocks|key|2621119|text|在最近的一个项目中，我将审计事件记录到数据库表中，并且我担心性能问题，因此我添加了以“异步”模式登录的功能。在这种模式下，日志记录器在低优先级后台线程中运行，从主线程进行日志记录的操作只是将日志事件放到一个队列中，该队列由后台日志记录线程懒惰地检索和写入。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|2621120|然而，只有在处理过程中有自然的“中断”时，这种方法才会起作用；如果您的系统经常繁忙，则队列永远不会被清空。解决这个问题的一种方法是使后台线程更加活跃，这取决于队列中日志消息的数量(这是我尚未实现的增强)。|2621121|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|F|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|G|8|@]|9|@]|A|$]]|$1|D|3|-4|5|6|7|H|8|@]|9|@]|A|$]]]|E|$]]

In a recent project, I log audit events to a database table and I was concerned about performance, so I added the ability to log in 'asynchronous' mode. In this mode the logger runs in a low-priority background thread and the act of logging from the main thread just puts the log events onto a queue which are lazily retrieved and written by the background logging thread.

This approach will only work, however, if there are natural 'breaks' in the processing; if your system is constantly busy then the queue will never be emptied. One way to solve this is to make the background thread more active depending on the number of the log messages in the queue (an enhancement I've yet to implement).

blocks|key|2337279|text|您应该：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|2337280|2337281|定义了适当的性能指标(例如响应性、吞吐量等)。然后，您应该在所有日志记录关闭然后再打开的情况下测量此指标。不同之处在于日志的成本。|ordered-list-item|2337282|然后，您应该尝试不同的日志库和它们提供的模式，并记录观察到的差异。|2337283|2337284|根据我的个人经验，对于我参与的所有三个项目，我发现异步日志记录有助于极大地提高应用程序吞吐量。但同样的情况可能不适用于你，所以请确保你在仔细衡量后做出决定。|2337285|以下内容与您的问题没有直接关系。|2337286|我注意到您特别提到了业务日志。在这种情况下，您可能还希望保持日志记录的相关性和整洁，以防您发现日志文件变得越来越大且难以理解。这个区域有日志：a+generally+accepted+design+pattern+as+function。这将意味着业务记录(例如，客户请求退款)将去往不同的目的地，接口日志将去往另一目的地(例如，用户点击了向上投票按钮!=用户对答案进行了向上投票)，并且跨系统呼叫将去往另一目的地(例如，通过支付网关请求清除)。有些人还保留了一个包含所有事件的主日志文件，只是为了查看过程的时间表，而有些人则设计日志挖掘器/剪贴器，以便在需要时构建时间表。|offset|length|2337287|希望这能帮上忙|2337288|entityMap|0|LINK|mutability|MUTABLE|url|http://gojko.net/2006/12/09/logging-anti-patterns/^0|0|0|0|0|0|0|0|1Z|Z|0|0|0^^$0|@$1|2|3|4|5|6|7|10|8|@]|9|@]|A|$]]|$1|B|3|-4|5|6|7|11|8|@]|9|@]|A|$]]|$1|C|3|D|5|E|7|12|8|@]|9|@]|A|$]]|$1|F|3|G|5|E|7|13|8|@]|9|@]|A|$]]|$1|H|3|-4|5|6|7|14|8|@]|9|@]|A|$]]|$1|I|3|J|5|6|7|15|8|@]|9|@]|A|$]]|$1|K|3|L|5|6|7|16|8|@]|9|@]|A|$]]|$1|M|3|N|5|6|7|17|8|@]|9|@$O|18|P|19|1|1A]]|A|$]]|$1|Q|3|R|5|6|7|1B|8|@]|9|@]|A|$]]|$1|S|3|-4|5|6|7|1C|8|@]|9|@]|A|$]]]|T|$U|$5|V|W|X|A|$Y|Z]]]]

You should: 

<ol>
<li>Define an appropriate metric of performance (e.g., responsiveness, throughput, etc.). Then you should measure this metric with all logging turned off and then on. The difference would be the cost of logging. </li>
<li>Then you should experiment with different logging libraries and the modes they provide and document the observed differences. </li>
</ol>

In my personal experience, for all the three projects I worked on, I found that asynchronous logging helped improve the application throughput a lot. But the same may not hold for you, so make sure you make your decision after careful measurements.

The following does not directly relate to your question. 

I noticed that you specifically mentioned business logging. In this case, you may also want to keep logging relevant and clean, in case you find your log files are growing huge and difficult to understand. There is <a href="http://gojko.net/2006/12/09/logging-anti-patterns/" rel="nofollow">a generally accepted design pattern</a> in this area: log as per function. This would mean that business logging (e.g., customer requested a refund) goes to a different destination, interface logging would go to another destination (e.g., user clicked the upvote button != user upvoted an answer), and a cross system call would go to another destination (e.g., Requesting clearance through payment gateway). Some people keep a master log file with all events as well just to see a timeline of the process while some design log miners/scrappers to construct timelines when required.

Hope this helps,

I am considering logging business events in a J2EE web application by using Java logging and FileHandler.

I am wondering whether that could cause a performance bottleneck, since many log records will be written to one file. 

What are your experiences and opinions?

Is logging a busy web application to one file with Java logging and FileHandler likely to become performance bottleneck?

Is Logging using FileHandler a bottleneck?

翻译质量差，导致语言生硬或混乱。

没有提供实际的解决方法或示例。

解答不清晰，无法理解或解决问题。

页面排版不美观，阅读体验差。

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我正在考虑使用Java和FileHandler在J2EE web应用程序中记录业务事件。我想知道这是否会导致性能瓶颈，因为许多日志记录将写入到一个文件中。你的经验和观点是什么？使用Java和FileHandler将繁忙的web应用程序记录到一个文件中会成为性能瓶颈吗？

问使用FileHandler进行日志记录是一个瓶颈吗？
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