I do not pretend knowing everything about XML and SQL, I just puzzled a lot of the little bits of information together and think I found an easy way how to deal with null values correctly. This I want to share with you all in this article and I hope you will all benefit from me putting my findings in writing.
Most of the times prefixed as xsi. Among other things, this name space defines a nil attribute. For your XML document to have a null value in it, you need to declare this namespace in the document and then on the appropriate element s , add the nil attribute. Most of times the prefix xsi is used for this name space but this is not a requirement.
Any other prefix can be used just as well. For better readability I tend to use xsi most the time, and I suggest you all do so too. For example, this code:. If you just use the. The following qualifiers specify that an empty field in the data file retains its null value during the bulk-import operation, rather than inheriting a default value if any for the table columns.
You can specify that for an empty field in the data file, the corresponding table column uses its default value if any. The script below creates a test database and a table named myNulls. Notice that the fourth table column, Kids , has a default value. Note that there is no value in the third record, fourth column.
Alternatively, you can execute the following PowerShell script to create and populate the data file:. You can use XML format files to bulk import data into tables or non-partitioned views and to bulk export data. This is because the function relies on the XML format file to read data from a data file. Like a non-XML format file, an XML format file defines the format and structure of the data fields in a data file and maps those data fields to columns in a single target table.
These elements correspond to fields in the data file. The basic syntax is as follows:. A field can only be mapped to one column in the table. Not all fields need to be mapped to columns. A field value can be represented as: a character using single-byte representation , a wide character using Unicode two-byte representation , native database format, or a file name.
If a field value is represented as a file name, the file name points to the file that contains the value of a BLOB column in the target table. These elements correspond to table columns. The syntax of a format file is independent of the direction of the operation; that is, the syntax is the same for bulk export and bulk import. Putting the xsi:type Value into a Data Set. The attributes are described in separate sections later in this topic. The order in which the fields are declared in the format file is the order in which those fields appear in the data file.
A field is described in terms of the following attributes:. The xsi:type value is an XML construct used like an attribute that identifies the data type of an instance of an element.
For information on using the "Putting the xsi:type Value into a Data Set," later in this section. Instead, bcp loads the data based on the column types of the target table. If a mismatch exists between column types as specified in the format file and in the target table, an extra type conversion occurs. If no column is mapped to a field, the field is not copied into the generated row s. This behavior allows a data file to generate rows with different columns in different tables.
Users may want to perform a contextual search for topics of interest such as searching for the section on "clustered index" within the chapter on "indexing", and query technical quantities.
An appropriate storage model for your XML documents is an xml data type column. Indexing the XML column benefits query performance. For illustration, assume that government regulations require you to retain exact textual copies of your XML documents.
For example, these could include signed documents, legal documents, or stock transaction orders. You may want to store your documents in a [n]varchar max column. For querying, convert the data to xml data type at run time and execute Xquery on it. The run-time conversion may be costly, especially when the document is large.
If you query frequently, you can redundantly store the documents in an xml data type column and index it while you return exact document copies from the [n]varchar max column. The XML column may be a computed column, based on the [n]varchar max column. By defining a mapping between your XML schemas and the tables in a database, you create an "XML view" of your persistent data.
Similarly, updates are also propagated to those tables. Order is not important in your data, or your query table data is not recursive, or the maximal recursion depth is known in advance. For illustration, assume that you have existing relational data, such as customers, orders, and line items, that you want to handle as XML. This model is useful if you have to exchange data that contains XML markup with other applications while your SQL applications work uninterrupted.
Frequently, a combination of relational and xml data type columns is appropriate for data modeling. This may yield better performance in that you have more control over the indexes created on the relational columns and locking characteristics. The values to store in relational columns depend on your workload. On the other hand, if your XML data is extensively and nonredundantly decomposed into relational columns, the re-assembly cost may be significant.
For highly structured XML data, for example, the content of a table has been converted into XML; you can map all values to relational columns, and possibly use XML view technology.
The granularity of the XML data stored in an XML column is very important for locking and, to a lesser degree, it is also important for updates. Therefore, row-level locking causes all XML instances in the row to be locked. When the granularity is large, locking large XML instances for updates causes throughput to decline in a multiuser scenario.
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