我们有一个需要尽可能实时的 Analysis Services 多维数据集。这是一个相对较小的立方体，目前需要几秒钟来处理。
有没有这方面的指导方针？我很好奇其他人在做什么。
此外，过于频繁地处理多维数据集会有什么影响？主要关注的是 SSAS 服务器和源数据库上的负载吗？在我们的例子中，这将是相当名义上的。SSAS 客户将如何受到影响？当前的 SSAS 使用者是 Excel、PerformancePoint 和 Sharepoint/Excel Services。
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3 回答
1
Have you considered a real-time (ROLAP) partition to store the current day's data? This way, you get the performance of MOLAP for all your data prior to the current day, which you can process nightly, but have ROLAP's low latency for the data collected since the last cube process.
If your cube is small enough, you could even stretch that to be the current week's data, or more.
As far as the disadvantages of processing frequently, check out the below article, which says: "If the processing job succeeds, an exclusive lock is put on the object when changes are being committed, which means the object is temporarily unavailable for query or processing. During the commit phase of the transaction, queries can still be sent to the object, but they will be queued until the commit is completed." http://technet.microsoft.com/en-us/library/ms174860.aspx
So your users will see an impact in query performance.
于 2009-11-20T16:37:00.557 回答
1
I would say the first issue you'd have to consider is how much is this cube going to grow over time? If it is constantly updated and processed that couple seconds could quickly turn into 20 minutes.
For example, we currently have a cube that has 20 million rows (probably more now hehe) with financial data related to hospital billing and charges that takes about 20 mins to process and we do it once a day in the morning. Depending on the time of the year we sometimes do process during the day again but there have been no complaints as long as we notify people we are doing this.
于 2009-11-03T20:38:40.767 回答
0
可能你必须“把它放在那里”并跟踪它的表现。
一旦您了解人们如何使用立方体，您就可以确定是否真的需要不断地重新处理，如果是，您可能必须优化这种情况的发生方式。
具体使用此处描述的“基于使用的优化”：
于 2009-11-06T14:23:02.617 回答