每个表达式返回一系列的值，这些值又可以作为其他表达式的输入。
Each expression returns a list of values that can be used as input to other expressions.
每个表达式仅根据其操作数来返回值，并且都不会产生副作用。
Each expression returns a value that depends only on the operands of the expression, and no expression has any side effects.
另外还需要注意，Root是泛型的(实际上每个表达式都是泛型的)。
Also notice that Root is generically typed. (Actually, every expression is.)
每个表达式类都有一个simplify方法，以允许表达式重写。
Each expression class has a simplify method, to allow expression rewriting.
注意，每个表达式必须用点号结束，告诉解释器可以执行该表达式了。
Note, you must always end each expression with a period. This tells the interpreter to execute it.
每个表达式类都有一个evaluate方法和一个enumerate方法。
Each expression class has an evaluate method, and an enumerate method.
在执行请求之前，部署实用工具会估算每个表达式，并且会考虑到已部署的请求。
Before a request is executed, the deployment utility tool evaluates each expression, taking into account the already deployed request.
该筛选表达式将产生一个整数序列，其中每个整数都小于1000且能被3或5整除。
The filter expression will result in a sequence of integers where each is less than 1,000 and divisible by 3 or 5.
每个规则定义含有一个可选描述、变量列表和一个表达式。
Each rule definition contains an optional description, a list of variables, and an expression.
还可以在键入过程中显示的列表中选择表达式的每个部分。
You can also select each part of the expression from the lists that display as you type.
具体而言，此表达式为每个名称长度超过15 个字符的产品匹配类别值。
Specifically, this expression matches the category value for every product that has a name over 15 characters in length.
虽然保留最初的查询词数组不动，但是为每个词构建了正则表达式。
While leaving the original query words array intact, we build a regular expression for each word.
每个请求参数都包含一个文本值或表达式。
Each request parameter can contain a literal value or an expression.
接下来的代码遍历列表，把搜索查询的正则表达式应用于每个电影的标题。
The code then iterates through the list and applies a regular expression of the search query to each movie title.
而每个参数也是一个表达式。
第一步是创建与每个查询词一致的正则表达式，只有在查询词包含通配符 * 时才需要修改。
The first step is to create a compatible regular expression out of each query word, although modification is only required if the word contains a wildcard character: *.
在路径表达式的每个轴步骤中，节点测试出现在轴和谓词(用于进行任意筛选)之间。
In each axis step of a path expression, the node test comes between the axis and any predicates that might be present for arbitrary filtering.
表达式使得你可以为每个订单增加相应的客户姓名。
The expression would allow you to also add in the customer name for each order.
当一个表达式被赋值时，每个操作符将会被应用于其周围所有项所代表的数值。
When an expression is evaluated, each operator is applied to the data values represented by the surrounding terms.
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。
The Cartesian join is reduced by the filters found in the join expressions from each dimension to the fake fact.
注意，已为每个副本组创建了一个公共表表达式(第2、18和38行)。
Notice that for each repetition group a common table expression has been created (lines 2, 18 and 38).
正则表达式捕获每个属性的值并将其放置到此前用于存放来自TMC2消息的字段的哈希中。
The regular expression captures the value of each attribute and places these in the same hash you used to hold the fields from the TMC2 message earlier.
在此将会找到与支持的每个地址类型相匹配的明确的正则表达式。
There you'll find explicit regular expressions that match each address type supported.
对于查询中的每个度量，将度量的SQL表达式添加到SELECT列表中作为列。
For each of the measures that are to be in the query, add the SQL expression generated for the measure as a column in the SELECT list.
它将迭代id x序列中的每个元素，求得表达式的值，并将结果添加到这个返回序列。
It will iterate over each element of the idx sequence, evaluate the expression, and add the result to the return sequence.
通过为每个特性编写XPath表达式可以做到这一点。
This is done by writing an XPath expression for each feature.
您可以配置FanOut中介原语，以仅触发其输出末端一次，或对使用指定XPath表达式获取的每个元素都触发一次。
You can configure the Fan Out mediation primitive to fire its output terminal just once or once for each element obtained using a specified XPath expression.
每个FLWR表达式都有一个或多个for子句、一个或多个let子句、一个可选的where子句以及一个return子句。
Each FLWR expression has one or more for clause, one or more let clause, an optional where clause, and a return clause.
为此，可以针对每个DataItem使用以下条件表达式(见图21)。
To do this, we can use following conditional expression for each Data Item (Figure 21).
与在单个dbspace中保存多个表或索引片段提高了查询性能，这样做胜过将每个分段表达式存储在不同的dbspace中。
Storing multiple table or index fragments in a single dbspace improves query performance over storing each fragmented expression in a different dbspace.
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