分区是否适用于 SQL Server 2005 标准版 SP2
我在测试环境中使用 SQL Server 2005 Standard Edition SP2。我的本地 SQL Server 是开发人员版本。
我能够在本地计算机上对表进行分区。我知道 SQL Server 标准版不支持索引视图或分区。我只是想知道 SP2 与标准版相比是否有什么不同。
谢谢 维哈尔。
I am using SQL Server 2005 Standard edition with SP2 in test environment. My local SQL Server is a Developer edition.
I was able to partition the table on my local computer. I know that the SQL Server Standard edition does not support either indexed views or partitioning. I just wanted to know if the SP2 has made any difference to the Standard edition.
Thanks
vihar.
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SQL Server 2005 标准版不支持分区，Oracle 标准版也不支持分区。
该供应商希望您购买昂贵的企业版产品，该产品默认也没有分区，您需要购买支持分区的额外功能。
如果您的应用程序是用 Jave 编写的，那么有一个名为 Rewius 的产品，据我所知，它可能有助于解决您的解决方案知道它作为 JdbcDriver 之上的代理工作，封装查询和插入到数据库并模拟标准版数据库上的分区功能，如果您只需要分区功能而不需要其他企业功能，那么这是更便宜的解决方案。
Partitioning doesn't supported in SQL Server 2005 Standard Edition neither it is not supported in Oracle Standard Edition.
This vendors want you to buy the expensive Enterprise Edition products, which also don't have partitions as default, you need to buy an extra feature which support partitions.
If your application is written in Jave there is a product called Rewius which might help to solve your solution, as far as I know it works as a proxy above the JdbcDriver and encapsulate the queries and the insert to the database and emulate the partitions feature on Standard Edition database, It is cheaper solution if you only need the partition feature and not other enterprise features.
24M 并不大，但说分区不会提高性能只是笼统的说法；有些情况下没有，有些情况下有一点，有些情况下性能显着提高。如果您使用的是标准，您可以通过拆分表并在其前面放置一个存储过程来创建自己的分区（或者我猜您可以在应用程序代码中执行此操作，但不推荐这样做）。当然，诸如您如何搜索以及数据是什么之类的事情将决定您如何拆分表。许多人会说不然，但当硬件限制和处理能力成为界限时，情况是一样的，无论您的索引策略有多么出色，搜索 2M 行与 24M 或 60M 行绝对会有所不同。
24M isn't huge but saying that partitioning wouldn't improve performance is a blanket statement; some cases no, some cases a little and some cases substantial performance increases. If you are using Standard, you can create your own partitioning by splitting the table and throwing a stored proc in front of it (or i guess you could do it in your app code but wouldn't recommend it). Of course things like how you are searching and what the data is would dictate how you split the table. Many will say otherwise but have been in the same boat when hardware limitations and processing power are boundaries and it most definitely makes a difference searching 2M rows vs 24M or 60M rows regardless of how great your indexing strategy is.
我们实现了索引视图来解决性能问题。现在效果很好。感谢所有的帮助
We have implemented the indexed views to solve the issue with the performance. It is working great now. Thanks for all the help