如何返回一个多维数组键树吗？
多维数组使用多个索引来访问数据。
A multidimensional array USES more than one index to access data.
在此范围之外，多维数组是有效的。
有关更多信息，请参见多维数组。
这个技巧的原理同上（前面提到的定义多维数组）。
This trick applies the same principles as the last one (defining a multi-dimensional array).
多维数组指针和递归是C语言教学中的难点。
Multi-dimensional array pointer and recursion are the difficult sections of teaching C language.
通过使用不同的分隔符，你可以创建多维数组。
Through the use of different separators, you can create multidimensional arrays.
如何将一个大的文本文件的数据转换成一个多维数组？
How to sort a large text file's data into a multi-dimensional array?
如果每个子数组都具有相同的长度，则多维数组更适用。
If each subarray has the same length, a multidimensional array may be more useful.
下面的示例阐释了定义一维数组和多维数组之间的区别。
The following example illustrates the difference between defined a one-dimensional array and a multidimensional array.
联机分析使用多维数组作为存储结构以加快查询响应时间。
On-line analytical processing uses multidimensional array as storage structure to speed up response time.
变量可以像一个整数或字符串那样简单，也可以像多维数组或对象那样复杂。
The variable could be as simple as an integer or a string or as complex as a multidimensional array or an object.
为了等同的对待每个维，适应稀疏数据，必须对多维数组进行划分。
To treat every dimension equally and adapt to sparse data, it is necessary to partition multidimensional array.
并且唯一和多维数组的棕榈基本的支持整数、浮动小数点和串变量。
Palm Basic supports integer, floating point, and string variables, as well as single and multi-dimensional arrays.
这是一个简单的多维数组，主机名是第一个元素，端口号是第二个元素。
This is a simple array of arrays with the hostname as the first element, port number as the second.
如果需要的话，可以用括号把数组括起来，这对创建多维数组是很有用的。
If necessary, you can put parentheses around the array. This is useful for arrays of arrays.
表格计算引擎作为OLAP服务器的子系统，负责完成此类多维数组计算。
Spreadsheet engine, as a part of the OLAP server, can accomplish this kind of computations.
用同一方法也可以指定多维数组的数据类型，但要在括号内使用逗号(，)。
The same procedure specifies a multidimensional array data type, but commas (,) are between the brackets.
与关系数据库相比，基于多维数组的多维数据库更适合表示和存储多维数据。
As compared to RDB (Relational DataBase), multidimensional data base (MDDB) which base on multidimensional arrays is more suitable to express and store multidimensional data.
增加一个数组的维数时，该数组所需的总存储空间会急剧增大，因此应慎用多维数组。
When you add dimensions to an array, the total storage needed by the array increases considerably, so use multidimensional arrays with care.
如果你想使用接着一个一个多维数组操作，然后每个必须返回一个二维数组(少一个)。
If you want to use operators in succession an a multi-dimensional array, then each must return a (one less) -dimensional array.
如果为这个函数传递一个用户ID，它将在一个多维数组中按日期倒序的顺序返回那个用户发出的贴子。
If you pass this particular function a user id, it returns all the posts made by that user in reverse-chronological order, all bundled in a nice, multidimensional array.
极高性能的数值运算(助理法律顾问科学和图形)是有可能与新增对模块，实现了真正的多维数组。
Extremely high performance numeric computing (ala scientific and graphics) is possible with an add-on module that implements true multidimensional arrays.
这是一个科学计算库，支持多维数组和线性代数数，在某些计算概率、标记、聚类和分类任务中用到。
This is a scientific computing library with support for multidimensional arrays and linear algebra, required for certain probability, tagging, clustering, and classification tasks.
通过引入面指针、行指针和列指针，并与相应级别的指针相关联，阐述了应用指针访问多维数组的方法。
By introducing side pointer, row pointer and column pointer - three Pointers in different level, this paper discusses the means to access multi - dimensional array by pointer.
有几个因素会对性能产生负面影响，如数据模型的设计不正确（例如，在您的数据模型中产生对多维数组的需求）。
There are several factors that adversely affect performance, such as improper design of the data model (for example, creating a need for multidimensional arrays in your data model).
多维数据分析的关键是生成多维数据立方体，立方体实质上就是一个多维数组，是维和变量的组合表示。
The linchpin of multi-dimension analysis is to build multi-dimension data cube, essential of which is a multi-dimension array, and is the combination express of dimension and variable.
清单6 中程序的整体目标是扫描SRGS文档，并用表示提示结构的SimpleXML对象填充一个多维数组。
The overall goal of the program in Listing 6 is to scan the SRGS document and fill a multidimensional array with SimpleXML objects that represent the prompt structure.
当您选取数组的层面时 --我们将会看到，多维数组中的分层方法非常灵活且强大 -- 您得到的不是一个拷贝而是一个“视图”。
When you take slices of arrays -- and we will see that slicing is quite flexible and powerful for multiple dimensions -- what you get is not a copy but a "view."
当您选取数组的层面时 --我们将会看到，多维数组中的分层方法非常灵活且强大 -- 您得到的不是一个拷贝而是一个“视图”。
When you take slices of arrays -- and we will see that slicing is quite flexible and powerful for multiple dimensions -- what you get is not a copy but a "view."
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