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Titlebook: SQL Server Advanced Data Types; JSON, XML, and Beyon Peter A. Carter Book 2018 Peter A. Carter 2018 XML.JSON.CLR.Hierarchical data.Spatial

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31#
發(fā)表于 2025-3-26 21:57:15 | 只看該作者
XML Indexes,ther large object types, it can store up to a maximum of 2GB per tuple. Although standard operators such as . and . can be used against XML columns, you also have the option of using . expressions (discussed in this chapter). They can be rather inefficient, however, unless you create XML indexes.
32#
發(fā)表于 2025-3-27 03:54:09 | 只看該作者
33#
發(fā)表于 2025-3-27 07:46:13 | 只看該作者
34#
發(fā)表于 2025-3-27 09:54:13 | 只看該作者
35#
發(fā)表于 2025-3-27 13:45:25 | 只看該作者
Understanding Spatial Data,-tier applications, the ability to construct or interrogate spatial data may be critical. In this chapter, I will give an overview of spatial data and its implementation in SQL Server, before looking at the spatial standards that are used in the SQL Server implementation.
36#
發(fā)表于 2025-3-27 18:09:11 | 只看該作者
Working with Spatial Data, examine how to work with these data types. First, I will discuss the methods that can be used to construct surfaces, before reviewing how to query spatial data. Finally, you will see how to design and create spatial indexes.
37#
發(fā)表于 2025-3-27 22:28:08 | 只看該作者
38#
發(fā)表于 2025-3-28 05:47:51 | 只看該作者
39#
發(fā)表于 2025-3-28 07:36:38 | 只看該作者
40#
發(fā)表于 2025-3-28 14:29:20 | 只看該作者
Understanding JSON,milar to XML, in the respect that it is a self-describing, hierarchical data-interchange format. Unlike XML, however, JSON tags are minimal, making JSON documents shorter and both easier to read and quicker to parse.
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