This option, however, still retrieves the dimension members on the edges through joins to a common fact table.
但此选项，仍然会在边上通过连接到普通事实表来检索维度成员。
Each join reduces the size of the fact table by one-tenth due to selectivity of the table filter on each dimension table.
由于每个维度表过滤的选择度，每次连接都会减少事实表大小的十分之一。
A star join query typically involves a fact table and several dimension tables, with join predicates between the fact table and each dimension table.
一个星型连接查询通常包含一个事实表和几个维度表，事实表和每个维度表之间都有连接谓词。
Assume that there is a LINEITEM fact table on one remote source and a PART dimension table on another.
假设在一个远程数据源上有一个lineitem事实表，在另一个远程数据源上有一个part维表。
We have already covered fact and dimension tables, so in this column, we will look at how to design summary tables.
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。
The join between the fact table and any dimension table is an equi-join, which makes a hash join possible.
事实表和任何维度表之间的连接都是等值连接，这使得散列连接成为可能。
We have already covered fact tables, so in this column we will look at how to design dimension tables.
我们已经讨论过事实表，因此本专栏将关注如何设计维度表。
If the query was written by adding a dimension followed by a fact and then another dimension, then the database optimization would include the materialization as necessary.
如果查询的创建是通过先添加维度再添加事实表然后又添加维度的方式构成，那么数据库优化则必须包含实体化。
The dimension tables describe each analysis entry in the fact table: the actual date, the keyword values and categories as well as corresponding document title and content.
维表描述事实表中的每个分析条目：实际日期、关键词值和类别以及相应的文档标题和内容。
It typically has one large central table (called the fact table) and a set of smaller tables (called the dimension tables) arranged in a radial pattern around the fact table.
它通常有一个大型的中心表(称作事实表)和一组小型表(称作维度表)，维度表以放射模式围绕事实表。
Verify queries are split into dimension and fact queries.
验证查询按维度和事实查询划分。
Data in this fact table would typically be joined with data in multiple dimension tables to obtain specific details about various products, regions, and so on.
这个事实表中的数据通常与多个维表中的数据联结，从而获取关于各个产品、地区等的特定信息。
Now that you understand the process for both the dimension and fact tables, let's look at a real world example to explore how to identify the dimension and measures from the business requirements.
既然您理解了维度和事实表的处理，就让我们看一看真实世界的例子，以探索如何从业务需求中识别维度和测度。
The Cartesian join is reduced by the filters found in the join expressions from each dimension to the fake fact.
由于伪事实的每个维度中的连接表达式的过滤，笛卡尔连接结果缩小了。
When a fact is created, the key from each dimension must be assigned to it.
在创建事实时，必须将每个维度的键分配给它。
For example, in the relationship expression between the time dimension and the fake fact, a filter can be applied to reduce the records from the time dimension to just a few days.
例如，在时间维度和伪事实的关系表达式中，可以使用过滤来将时间维度缩小到几天之内。
It is made up of a facts object, which represents the fact table, and a set of dimension objects, representing the dimension tables.
它由一个事实对象(代表事实表)和一组维对象(代表维表)组成。
In the above, T1 is the fact table with FK-PK relationship with dimension tables T2 and T3.
其中，T1是与维表t2和t3有fk - PK关系的事实表。
IBM Cognos BI can be configured to not go through fact query subjects in dimension only queries.
可以配置IBMCognosBI，在只有维度的查询中，不对事实查询主题起作用。
STEP A: We assume you have created a database with the default table spaces. Create the fact and dimension tables as follows.
第 1 步：我们假设已经用默认表空间创建了一个数据库，同时创建下面的事实表和维度表。
This is a star schema consisting of a fact table and four dimension tables.
这是一个星型模式，由一个事实表和4个维表组成。
Partial Key Joins occur when there is an implicit many to many relationship between a dimension and a fact.
当一个维度和一个事实之间有一个隐式的多对多关系时会出现PartialKeyJoins。
This setting tells IBM Cognos BI to use the alphabetically first common fact table between the dimensions in a dimension only query.
这项设置告诉IBMCognosBI在只有维度的查询中，在维度之间使用字母顺序第一张通用事实表。
It will be more efficient to create a measures data source in Transformer that takes its keys from the actual fact table rather than from its related dimension tables.
使用事实表的键，而不是使用相关维度表的键，是一个更有效的创建Transformer度量指标数据源的方法。
STEP Ea: Alter the fact table and create the proper FK relationships with the dimension tables.
第 5.1步： Alter（修改）事实表，创建正确的维度表外键（FK）联系。
Only queries from a particular application that accesses a particular set of tables (for example, a fact table and its dimension tables)
只来自访问特定一组表（例如，一个事实表和它的维表）的一个特定应用程序的查询。
Connect to database GBPM4ETL and run script GBPM4ET.sql to create the dimension tables and fact table, as illustrated in Figure 10.
连接数据库GBPM 4etl，运行脚本GBPM 4et . sql以创建维度表和事实表，如图10所示。
For example, as shown below, the Location table is a dimension table for the Orders fact table.
例如，如下所示，location表是Orders事实表的一个维度表。
If Design filters are applied to both a fact query subject and any relating dimension query subjects, ensure that the filters are the same for both the fact and the related dimension.
如果DesignFilters应用到事实查询主题和任何相关的维度查询主题，要确保对事实和相关维度的过滤要一致。
It contains a fact table of 630 million records, a customer dimension of 2.5 million customers, and three small dimension tables for organization, programs, and commodities.
该架构包含一个拥有630,000,000条记录的事实表，一个拥有2,500,000名客户的客户维度，以及三个小的维度表，分别用于组织、程序和商品。
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