IE 10中的垂直滚动条11(Vertical scroll bars in IE 10 11)

 你链接到的文章的问题在于，当作者询问“瓶颈”在哪里时，作者显然不知道他在说什么; 有人拥有比数据库服务器更多的Web服务器的事实并不意味着“数据库不能成为问题所在”。 “数据库是瓶颈”通常意味着什么，这一点与任何曾经对Web应用程序进行运行时分析的人都了解到。 
 
 考虑一个需要半秒钟才能返回完整响应的应用程序。 假设你坐下来对其进行分析，并发现处理时间的半秒分解如下： 
 
 
 
 解析传入的请求：50ms 
 
 
 查询数据库：350ms 
 
 
 呈现HTML响应：50毫秒 
 
 
 发送回应：50ms 
 
 
 如果您看到类似的细分情况，那么数据库查询占应用程序实际运行时间的70％，则您可以正确地断定数据库是瓶颈。 而这正是大多数人在分析他们的应用程序时发现的（并且，通常，数据库如此完全支配处理时间，以至于剩余处理的语言选择没有任何人会注意到任何区别）。 
 
 涉及的数据库服务器的数量事实上并不重要; 这里的着名引述是，像你所链接的帖子的作者这样的人是那些听说一个女人需要9个月才能生个孩子的人，并且假设九个女人一起工作可以在一个月内完成。 用数据库术语来说：如果给定的查询需要100毫秒才能在给定的数据库上执行，那么添加更多的数据库服务器并不会使它们中的任何一个能够更快地执行该查询。 添加更多数据库服务器的原因是能够处理更多的并发请求，并防止数据库过载，而不是使隔离请求更快。 
 
 然后从那里进行扩展应用程序的常规舞蹈：缓存以减少检索数据或呈现响应的总时间，负载平衡增加可以服务的并发请求数，分片和更高级的数据库设计防止在负荷下沉没等的方案等。 
 
 但是，您会注意到，这与使用的编程语言没有任何关系，因为再次，由其他因素所花费或节省的时间大大超过了“快速”获取或丢失的时间量，或者一个“慢”的语言（当然，实际上没有这样的东西;这很大程度上取决于问题领域和程序员的技能，因此你不能进行有意义的一般比较）。 
 
 无论如何，这是漫长而漫长的过程，所以我只是将其总结为一条准则：如果你看到有人争辩说“你应该用X语言来建立语言，因为它运行得更快”，这是一个死的东西，他们不会真的不了解真实世界的性能或缩放比例。 因为，毕竟，如果它只是归结为“用最快的语言写作”，他们会建议我们都使用汇编:) 

The problem with the article you link to is that the author clearly doesn't really know what he's talking about when he asks where the "bottleneck" is; the fact that someone has more web servers than database servers doesn't mean "the database can't be where the problem is". What's generally meant by "the database is the bottleneck" is the same thing that's been learned by everyone who ever does run-time profiling of a web application.
 
Consider an application which takes half a second to return a full response. Suppose you sit down and profile it, and find that that half second of processing time breaks down as follows:
 
 
 
Parsing incoming request: 50ms
 
 
Querying database: 350ms
 
 
Rendering HTML for response: 50ms
 
 
Sending response back out: 50ms
 
 
If you saw a breakdown like that, where database queries constitute 70% of the actual running time of the application, you'd rightly conclude that the database is the bottleneck. And that's exactly what most people find when they do profile their applications (and, generally, the database so completely dominates the processing time that the choice of language for the rest of the processing doesn't make any difference anyone will notice).
 
The number of database servers involved turns out not to matter too much; the famous quote here is that people like the author of the post you've linked are the types who hear that it takes one woman nine months to have a baby, and assume that nine women working together could do it in one month. In database terms: if a given query takes 100ms to execute on a given DB, then adding more DB servers isn't going to make any one of them be able to execute that query any faster. The reason for adding more database servers is to be able to handle more concurrent requests and keep your DB from getting overloaded, not to make isolated requests go any faster.
 
And from there you go into the usual dance of scaling an application: caching to cut down on the total time spent retrieving data or rendering responses, load-balancing to increase the number of concurrent requests you can serve, sharding and more advanced database-design schemes to keep from bogging down under load, etc., etc.
 
But, you'll note, none of this has anything whatsoever to do with the programming language in use because, once again, the amount of time spent or saved by other factors grossly outweighs the amount of time gained or lost by a "fast" or a "slow" language (and, of course, there's really no such thing; so much depends on the problem domain and the skill of the programmer that you just can't have a meaningful general comparison).
 
Anyway, this is getting kind of long and rambling, so I'll just wrap it up with a general guideline: if you see someone arguing that "you should build in Language X because it runs faster", it's a dead giveaway that they don't really know anything about real-world performance or scaling. Because, after all, if it just came down to "write in the fastest language", they'd be recommending that we all use assembly :)