在下一专栏中，我们将关注汇总表。
一个关键设计决策是汇总表的粒度。
他首先查看底层数据库汇总表。
汇总表是指其定义基于查询结果的表。
A summary table is a table whose definition is based on a result of a query.
这样，您不必担心需要反复构建汇总表。
That way you never have to worry about building the summary table again and again.
第一张工作表是汇总表。
汇总表是创建高性能数据仓库的重要部分。
Summary tables are an important part of creating a high-performance data warehouse.
汇总表都与速度有关。
一个傲慢的人总表现出好像比别人技高一筹的德行。
An arrogant person will act as though he is better than others.
金字塔顶端的汇总表比较小，因此对它的查询非常快。
The summary table at the top of the pyramid is small, so queries on it are very fast.
您可以让构造汇总表和列出链接主题这样的事情自动完成。
You can automate things like building summary tables and listing linked topics.
维度建模包括三个关键部分：事实表、维度表、以及汇总表。
A dimensional model has three key parts: the fact tables, the dimension tables, and the summary tables.
从汇总表，他们可以选择打算进一步向下挖掘查看更多细节的维度。
From the summary table, they can then pick the dimensions that they want to drill down into and see more detail.
我们已经讨论过事实表和维度表，因此本专栏将关注如何设计汇总表。
We have already covered fact and dimension tables, so in this column, we will look at how to design summary tables.
汇总表存储以回答常见(或资源密集型)业务查询的方式汇总的数据。
A summary table stores data that has been aggregated in a way that answers a common (or resource-intensive) business query.
如果你要是能够不是总表现得这样愚蠢，你会发觉他还是乐意帮助你的。
If you'd stop acting like such a fool, you'd realize he's just tried to help you.
我们构建了一个汇总表，汇总收入和费用细节，显示每笔交易的最终结果。
We built a summary table that aggregated the income and expense detail to show the end result for each transaction.
因此，汇总表通常包含基于其定义所基于的表中的现有数据的预计算结果。
As such, the summary table typically contains pre-computed results based on the data existing in the table or tables that its definition is based on.
理想情况下，数据仓库的结构提供一个针对业务用户想问的所有问题的汇总表。
Ideally, the structure of the data warehouse offers a summary table for any question that business users want to ask.
另一种方法是使提取、转换和加载(etl)流程在加载事实表时更新汇总表。
Another way is to have the extract, transform, and load (ETL) process update the summary table as it loads the fact table.
在数据仓库中需要汇总表，来实现快速查询，并允许用户在事实表中钻入钻出。
Summary tables are required in a data warehouse for fast query processing and to allow users to drill up and down into the facts.
第三种方法是在ETL流程之后使用SQLSUM和汇总函数来重构汇总表。
A third method is to have the summary tables rebuilt after the ETL process using SQL sum and aggregate functions.
您可能还会对该软件生成的其它输出 —例如汇总表和尾数概率 —感兴趣。
You might also be interested in other outputs that the software generates, such as summary tables and tail probability.
事实上，我们已经看到，IWA取代了我在数据仓库中设计的汇总表中的许多需求。
In fact, I see IWA replacing the need for many of the summary tables I design in a data warehouse.
通过利用索引、缓存、登录开销的减少、汇总表以及取数据的减少来减少I/O。
Reduce I/O by taking the advantage of indexes, caching, reduced logging overhead, summary tables, and reduced fetches.
当他们发现需要更多细节的问题时，他们可以向下钻取到另一个汇总表或细节事实表。
When they found issues that required more detail, they could then drill down into another summary table or the detail fact table.
事实上，我们的目标是使90%的查询都针对汇总表运行，以便用户获取非常快的响应。
In fact, the goal is to have 90 percent of your queries running against the summary tables so the user gets very fast responses.
顶级汇总表可能拥有约100,000条记录，下一级汇总表有可能拥有数百万条记录。
Your top-level summary table may have about 100,000 records; the next-level summary table will probably have millions of records.
当用户向下钻取更多细节时，每个汇总表都包含更多行，直到用户到达事实表(见图1)。
As the user drills down into more detail, each summary table contains more rows, until the user reaches the fact table (see Figure 1).
count函数非常有用，可以在任何级别显示汇总表中的每个汇总行由多少条记录组成。
The COUNT function is very useful to show at any level how many records make up each aggregated row in the summary table.
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