误导：将客户引导至非索引站点。
但如果我们的非索引谓词如下所示，情况有会怎样呢？
在某些情况下，联接非索引列会使查询速度变慢。
In some cases, joining on unindexed columns can result in a slow query.
如果我们将以下非索引谓词添加到我们的SQL将会怎样呢？
What if we added the following non-index predicates to our SQL!
如果不指定索引，则以非索引的方式绘制三角形。
If the indices are not specified, triangles are drawn in a non-indexed fashion.
调用中的格式字符串内的括号中放入非索引数字的内容。
There really isn't any formatting within a strong, beyond it's alignment. Alignment works for any argument being printed in a String. Format call.
第二，无论谓词的编码顺序如何，Stage1非索引谓词都按以下顺序应用？
Second, regardless of the order in which they are coded, Stage 1 non-index predicates are applied in the following order.
采用非索引方法的另一个关键优点是Netezza设备根本不需要进行调优。
Another critical benefit of the non-indexed approach is that the Netezza appliance doesn't need to be tuned at all.
示例13：收集构成索引的所有列以及两个非索引列中包含分布的目录统计信息。
Example 13: Collect catalog statistics with distribution on all columns that are part of the index, plus two columns that are not.
使用主变量或实际文本时，DB 2不会对非索引考虑这个因素；只有您能够考虑这个因素并相应编码。
With host variables or literals, DB2 does not consider this factor for non-index predicates; only you can take this fact into account and code accordingly.
您的邮箱是一个简单的平面（连续的、非索引的）文件（除非您的系统管理员正在使用 maildir格式）。
Your mailbox is simply a flat (contiguous, non-indexed) file (unless your systems administrator is using the maildir format).
如果两个执行个体只宣告非索引键属性，但名称、型别、顺序和值都相等，则这两个执行个体还是不相等。
Only properties you designate as key properties participate in tests of equality between anonymous type instances, or calculation of hash code values.
我想说的是，对于非索引谓词，DB 2不会考虑COLCARD或COLUMN DISTRIBUTION统计数据。
What I'm saying here is that for non-index predicates, DB2 does not consider the COLCARD or the COLUMN DISTRIBUTION statistics.
仅当查询中有非索引连接列或过滤列时，才使用UPDATESTATISTICSMEDIUMDISTRIBUTIONS。
Use UPDATE STATISTICS MEDIUM DISTRIBUTIONS ONLY if queries have non-indexed join columns or filter columns.
另外的解决方案，取决于具体的错误，可能是手工重建非聚簇索引，如果数据是静态的手工扔掉和重新载入表，诸如此类。
Additional solutions, depending on the errors, may be to manually rebuild non-clustered indexes, manually drop and reload a table if the data is static, and so on.
为了使索引发挥最优性能，索引应该位于以10,000R PM或者更快速度旋转的非系统硬盘上。
For maximum indexing performance, the index should reside on a nonsystem disk that rotates at 10,000 RPM or greater.
不管使用什么技术，索引大量非结构化数据是一件很艰难的任务。
Indexing large amounts of unstructured data is a difficult task regardless of the technologies involved.
该选项以筛选的方式用于非匹配索引扫描，且是仅索引访问的一部分。
The option can be used in non matching index scans in a screening fashion and as part of index-only access.
相关子查询将极大地降低数据检索的速度，对于拥有几百万个行但没有索引的大型表的非选择性查询更是如此。
Correlated subqueries will greatly degrade the speed of data retrieval, especially for non-selective queries on huge tables with millions of rows and with no index.
造成这种速度优势的原因是数组是固定大小的，而默认的PHP 数组是可变大小的，并且不允许非数值型索引。
This speedup is due to the fact that the array is a fixed size, not a variable-sized one like the default PHP one is, and that non-numeric indexes are not allowed.
然后，可以在非末端元素“phone”和元素“areacode”上分别定义一个xml索引。
Then, you can define one XML index on the non-leaf element "phone" and one on the element "areacode".
有些平台(非powerpc)允许程序员为索引寄存器指定一个倍数。
Some platforms (not PowerPC) allow programmers to specify a multiplier for the index register.
(聚集或非聚集)索引类型未指定。
更好的控制手工索引和索引编写（RAM使用、非混合的文件格式标志等等）。
Better control over manual indexing and index writing (RAM consumption, non-compound file format flag etc).
通常情况下，在基础索引提供好处(如唯一索引访问、避免排序或一些类似的好处)时，可通过优化器选择非匹配索引扫描。
Typically, a non-matching index scan is chosen by the optimizer when the underlying index provides benefits such as index-only access, avoids sort, or some similar benefit.
首先在逻辑上将表与其自身连接，然后将更具有选择性的非起始索引键作为索引绑定过滤器，应用于起始键值的每个惟一的组合。
The table is logically joined to itself, and the more selective non-leading index keys are applied as index bound filters to each unique combination of the leading key values.
在创建和使用方面，函数索引和非函数索引之间存在着大量差异。
There are not many differences between functional and non-functional indexes with respect to how you create and use them.
尽管可以在非末端元素上定义索引，但是仅在少数情况下这些索引才有用。
Although you can define indexes on non-leaf elements, they are useful only in rare cases.
它取代了2004开始试探的最初索引算法，它已经证明在处理大量和非结构化数据集时更有效。
It replaced the original indexing algorithms and heuristics in 2004, given its proven efficiency in processing very large, unstructured datasets.
有一些情况下，非末端元素上的索引是有意义的。
There are a few cases where indexes on non-leaf elements can make sense.
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