数据集是否可扩展?像 myspace 这样的网站会使用它们进行数据检索吗? [英] Are datasets scalable? Would a site like myspace use them for data retrieval?

问题描述

数据集的可扩展性如何?团队成员希望使用数据集进行数据检索和操作，使用内置的数据完整性等来使用对象执行数据更新等.

How scalable are datasets? Team member wants to use datasets for data retrieval and manipulation, use the built in data integrity etc. to use the object to perform data updates etc.

我们的系统预计将扩展到数百万用户.

Our system is expected to scale to millions of users.

我读到的所有内容都是针对企业环境中的数据集的，我在这里是错的还是什么?

Everything that I have read is against dataset's in an enterprise environment, am I wrong here or what?

推荐答案

免责声明-这些是我的个人经验

数据集使用起来非常痛苦，除非您对它们有特定需求，否则我真的不推荐使用它们.我曾参与过 .NET 1.0 时代的大型项目(包含数千个数据集)，我发现它们难以维护、使用和测试.除非您使用强类型数据集，否则您必须使用基于数组的语法来访问所有内容，而您将永远花在维护上.

Datasets are so painful to use I would REALLY not recommend using them unless you had some specific need for them. I have worked on large .NET 1.0 era projects (with thousands datasets) and I find them hard to maintain, use and test. You have to access everything with array based syntax unless you use strongly typed datasets, which you will spend forever maintaining.

我真的推荐使用像 NHibernate 这样的 ORM.您可以通过这些截屏视频了解有关 NHibernate 的更多信息.

I would really recommend using an ORM like NHibernate. You can learn more about NHibernate with these screen casts.

如果您对 Salable 架构感兴趣，您应该查看 High Scalability 网站，在那里您将能够找到您在问题中提到的 MySpace 架构.

If you are interested in Saleable architecture you should look at the High Scalability web site, where you will be able to find the MySpace Architecture that you mention in your question.

有关数据集的更公正的意见，请查看此 MSDN 链接(以下总结)

For a more unbiased opinion on Datasets please check this MSDN link (summary below)

何时使用哪个

DataSet 和自定义类都没有以任何方式限制您可以做的事情，并且两者都可以用来完成相同的目标.也就是说，数据集是出色的原型制作工具应用和代表优秀用于构建系统的解决方案一种紧急情况——有限的预算，接近最后期限，或短期应用程序生命周期.对于相对简单的应用程序，自定义实体添加一个可能不必要的水平复杂.在这种情况下，我建议您认真考虑使用数据集.

Both DataSets and custom classes don't limit what you can do in any way, and both can be used to accomplish the same aims. That said, DataSets are fantastic tools for prototyping applications and represent excellent solutions for building systems in a kind of emergency—a limited budget, an approaching deadline, or a short application lifetime. For relatively simple applications, custom entities add a perhaps unnecessary level of complexity. In this case, I suggest that you seriously consider using DataSets.

在一个大型、耐用的经济体中，复杂的企业系统几个月才能完成，费用的架构和实施一堆集合类是相对最小，并且会招致只有一次.优势方面表现力、表现力、可读性和易于维护很大程度上偿还了投资.你是不受表格渲染的约束数据.业务规则和习惯商业实体不能总是适应看起来像一个集合表.一般来说，你应该避免使数据适应数据容器——完全相反，我会说.最后，使用自定义类使为了更容易的单元测试，因为类和逻辑更严格与数据集相关.在图 3中，你会找到一张总览表数据集、类型化数据集和自定义实体按几个因素进行比较.

In the economy of a large, durable, complex enterprise system that takes several months to complete, the cost of architecting and implementing a bunch of collections classes is relatively minimal and is incurred only once. The advantages in terms of performance, expressivity, readability, and ease of maintenance largely repay the investment. You are not bound to a tabular rendering of data. Business rules and custom business entities can't always be adapted to look like a collection of tables. In general, you should avoid adapting data to the data container—quite the reverse, I'd say. Finally, using custom classes makes for easier unit testing because classes and logic are more strictly related than with DataSets. In Figure 3, you find a synoptic table with DataSets, typed DataSets, and custom entities compared by several factors.

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