We haven't found any convincing evidence that selectivity or prestige matters.
我们还没有找到任何有说服力的证据来证明选择性或声望很重要。
Schools are tending towards greater selectivity.
学校对新生的选拔有趋严之势。
Step 2.5: Verify the selectivity estimates
步骤 2.5：验证选择性估计
The first bucket of gold can make her life full of selectivity.
这第一桶金，让生活的可选择性丰富极了。
Histograms are used to calculate the selectivity of the predicates.
直方图用于计算谓词的选择率。
This suggests a much better predicate selectivity than it appears to be!
这表明谓词选择性比其表现出来的还要好！
The Listing 7 output is starting to look useful, but suffers from a lack of selectivity.
清单7的输出看起来有用一些了，但是缺少选择性。
Our ears have only evolved to respond to sound with very high sensitivity and high selectivity.
人类的耳朵对声音的反应，极为敏感，也极有选择性。
The optimizer can use data distributions to calculate selectivity for the filters in a query.
优化器可以使用数据分布来计算查询中过滤器的选择率。
In other words, the optimizer overestimated the selectivity of the local predicates on the table.
换句话说，优化器过高估计了本地谓词对表格的选择性。
Given accurate statistics, the query optimizer generally comes up with correct selectivity estimates.
如果有了准确的统计信息，那么查询优化器一般能够得出正确的选择性估计。
YUSHAN YAN: "in terms of sensitivity and selectivity, the current technology out there is still inferior."
严教授：“在灵敏度和选择性方面，目前的技术仍存在劣势。”
Now that you've analyzed the selectivity of the local predicates, let's now look at the table selectivity.
已经分析了本地谓词的选择性，我们再看看表的选择性。
The use of column groups provides more accurate estimates of the joint selectivity of multiple predicates.
列组的使用将给多个谓词的联合选择提供更准确的估计。
So it is obvious that the accuracy of selectivity estimation depends upon how often you run UPDATE STATISTICS.
因此，选择性估算的准确性显然基于您运行UPDATESTATISTICS的频率。
But the selectivity calculated in this way is not as accurate as selectivity calculated using data distribution.
但是，使用该方式计算的选择性不如使用数据分布计算的选择性准确。
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。
The selectivity is a value between 0 and 1 that indicates the percentage of rows within the table that the filter can pass.
选择率是介于 0 到1 之间的一个值，表示表中能通过过滤器的行所占的百分比。
On its own, that's pretty powerful; but XPath offers quite a bit more in terms of selectivity, all using what's called a predicate.
这本身已经非常强大了，不过XPath 还提供了更多的选择性，即使用所谓的谓词。
The optimizer USES data distribution information generated by UPDATE STATISTICS to calculate selectivity for the filters in the query.
优化器使用UPDATESTATISTICS所生成的数据分布信息来计算查询中筛选器的选择性。
At the same time, we also have found differences in signal selectivity that may allow us to target some bacteria while ignoring others.
同时，我们还发现了信号选择性的差异，这能够使我们针对一些特定的细菌而不影响到其他。
The performance improvement depends on the selectivity of the filter on the dimension table from which the join keys are pushed down.
性能的提高取决于连接键被下推时所在维度表的过滤选择度。
The optimizer can then compare the input variable values to catalog statistics and compute a better selectivity estimate for predicates.
然后，优化器可以将输入变量的值与编目统计进行比较，并为谓词计算出一个更好的选择估计。
However, in the absence of data distributions, the database server calculates selectivity for filters of different types based on table indexes.
但是，如果没有数据分布，则数据库服务器根据表索引计算不同类型的过滤器的选择率。
Selectivity: When the query optimizer (QO) studies your SQL, the degree of selectivity determines if an index should be used to perform the operation.
选择性：当查询优化器(query optimizer，即QO)读取SQL时，选择性的程度决定了索引是否应该用来执行该操作。
However, in the absence of data distribution information, the optimizer will calculate selectivity for filters of different types based on table indexes.
然而在缺乏数据分布信息的情况下，优化器将基于表索引计算不同类型筛选器的选择性。
Refer to Chapter 10 of the Performance Guide for the detailed table that the optimizer USES to calculate selectivity in the absence of data distribution.
关于在缺乏数据分布的情况下，优化器用以计算选择性的详细表，请参阅performanceGuide的第10章。
This can occur if the IN list contains parameter markers or host variables which prevent the optimizer from using catalog statistics to determine the selectivity.
如果IN列表中包含参数标记符或主机变量，使优化器不能使用编目统计信息来确定选择性，就会出现这种情况。
Missing statistics can cause the optimizer to overestimate or to underestimate the selectivity of a predicate, and eventually to select an inefficient access path.
丢失的统计数据会让优化器高估或低估谓词的选择性，最终会选择低效的访问路径。
应用推荐