The filter factor indicates how selective the predicate is.
过滤因子表示谓词的选择性有多强。
The query annotation for this predicate shows that the predicate filter factor (FF) is 0.000014, or 0.0014%.
此谓词的查询注释显示谓词过滤因子(FF)是0.000014，或0.0014%。
For SQL statements with variables, the optimizer USES a default filter factor to determine the best access path at bind time.
对于带变量的sql语句，优化器会使用一个默认过滤因子在绑定时确定最佳访问路径。
The filter factor is a number between 0 and 1 that estimates the proportion of rows in a table for which the predicate is true.
过滤因子是0到1之间的一个数值，它用来评估表中谓词为真的行所占的比例。
The estimate for QUALIFIED_ROWS is obtained by multiplying the table cardinality (560,273 records) by the predicate filter factor (0.0014%).
用表基数（560,273条记录）与谓词过滤因子 (0.0014%) 相乘就获得了 QUALIFIED_ROWS的估计值。
If you want to further see if the filter factor estimates at TBSCAN (3) make sense, you should generate a count for each predicate individually. For example.
如果希望进一步看看TBSCAN(3)估计的筛选因子是否合理，应该分别对每个断言生成计数。
Since it is a range predicate and there are no frequency and histogram statistics available, the filter factor is calculated with the basic statistics information HIGH2KEY and LOW2KEY.
由于它是范围谓词，而且没有频度和直方图统计数据可用，过滤因子是用基础统计信息HIGH2KEY和LOW2KEY计算得出的。
According to the annotation information in the figure, the table reference CUST_CUSTOMER (CCUS) has two local predicates which are very selective, with filter factor 0.00727 and 0.004, respectively.
根据图中的注释信息，优先表CUST_CUSTOMER (CCUS)有两个本地谓词，其选择性很强，各自的过滤因子分别是0.00727和0.004。
FF (see number 6 in Figure 5) : Filter factor for the predicate.
FF(见图5中6)：谓词的过滤因子。
The Filter factor for each predicate indicates the proportion of data the optimizer estimates will satisfy the predicate.
每个断言的筛选因子表示优化器估计符合断言的数据的比例。
The Filter factor for each predicate indicates the proportion of data the optimizer estimates will satisfy the predicate.
每个断言的筛选因子表示优化器估计符合断言的数据的比例。
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