SQL XML programming
The few times that I've seen the XML data type in SQL server it's tables, columns, and relationships in place to hold data for complex objects. Db2 for IBM i provides support to store and retrieve XML data using Structured Query Language (SQL). Objects defined using SQL such as tables, functions, and. Mar 13, This topic discusses the advantages and the limitations of the xml data type in SQL Server, and helps you to choose how to store XML data.
After you have reviewed these parameters you are ready to test. Click the Test Driver Configuration link, and if everything is correct, you will see the "Connection Successful" message.
You'll get to the Data Source configuration page Figure 4. Remember the JNDI path; we'll use it later to set up a connection from our code. Next select Continue, and then choose the correct connection pool to associate with the Data Source. Select the Connection Pool that you just created, and click Continue. The next page allows you to select servers and clusters on which to deploy the Data Source. Check the necessary ones from the list, and then click Create.
The Data Source has been created and we ready to start writing the code. Preparing the Environment for a Stand-Alone Java Application Let's prepare our environment for writing a simple client application. Also, as we're using JNDI, we need to have weblogic.
They are quite different, and you should use the appropriate approach for your task. Consequently, these columns can participate in queries just like any other column type. You can read more about this approach and see examples in the WebLogic Server documentation on the Oracle driver, or on the Oracle Technology Network.
In this article we are going to focus exclusively on the XSU approach.
- XML Data (SQL Server)
- SQL XML programming
- XML as a Bridge between SQL and Web Applications
Here is the complete source code oraxml. Lines 13 and 20 establish and close the connection. The most interesting lines are which make a so-called "XML query". Line 14 initializes the query.
Lines set the structure of the future XML document. Line 15 sets the maximum number of rows returned, limited to maxRows. Lines 16 and 17 set the root element of the document and the item delimiters. Line 18 generates an XML document and stores it in the xmlString variable. As you can see, the code is very simple and easy to read. Note that this is not production code. You should close a connection in a finally clause. We should not forget about JNDI, which we're using in this code.
As this is a stand-alone Java application, we need to set a naming provider for it to use. We'll use our WebLogic Server; to configure this we need to create a jndi. Here is our jndi.
As you can see, this is quite a handy utility that can be used for performing SQL queries and returning an XML formatted output. However, XSU is not limited only to this functionality. XSU can also store them in relational tables by creating object views over the flat tables and querying over these views. In addition, it supports XML attributes during generation. One of the questions you may be asking yourself is why we are using XML here and why we are calling it "a bridge.
Imagine you've got an information portal, which is designed to deliver news from the SQL database to end users, whoever they are: Furthermore, you, as an information owner, can resell it to other end users, and your news should be shown with different titles, like "News from the Acme, Corp. But the news that you are delivering does not change. So why should you perform extra coding for every kind of end user who may receive your news, when you technically need only change the "look and feel"?
Now you can see that you need some transparent bridge that can receive SQL on one side and produce different formats on the other. This bridge is XML. Your servlet makes a request to the database, receives XML output, and applies an XSL template to it, producing a page for an end user. So, you need to change only a design in XSL and nothing more. No extra coding, no wasted time.
XML Data Type and Columns (SQL Server)
What about sharing your news with others? That's great, but why should you allow others to access your SQL database? Why should you explain the structure of it?
The next step is mastering the WebLogic Server options for converting XML into different formats, and building a web application. At the moment, there are different technologies for handling XML streams. Generally, you may have to use a combination of these approaches. For example, you may want to store your XML data in an xml data type column and promote properties from it into relational columns. Or, you may want to use mapping technology to store nonrecursive parts in non-XML columns and only the recursive parts in xml data type columns.
Storage options Your XML data may be more appropriate for large object storage for example, a product manualor more amenable to storage in relational columns for example, a line item converted to XML.
Each storage option preserves document fidelity to a different extent. Query capabilities You may find one storage option more appropriate than another, based on the nature of your queries and on the extent to which you query your XML data. Fine-grained query of your XML data, for example, predicate evaluation on XML nodes, is supported to varying degrees in the two storage options.
Indexing options vary with the storage options; you have to make the appropriate choice to optimize your workload. Data modification capabilities Some workloads involve fine-grained modification of XML data.
For example, this can include adding a new section within a document, while other workloads, such as Web content, do not. Data modification language support may be important for your application.
Different choices also have different performance characteristics. This is an appropriate choice if the following applies: You want a straightforward way to store your XML data at the server and, at the same time, preserve document order and document structure.
Why use XML type to store XML data in SQL Server? - Stack Overflow
You may or may not have a schema for your XML data. You want to query and modify your XML data.
You want to index the XML data for faster query processing. Native XML storage is useful when you have XML documents that have a range of structures, or you have XML documents that conform to different or complex schemas that are too hard to map to relational structures. A section can contain subsections. Product manuals contain a large amount of mixed content, diagrams, and technical material; the data is semi-structured. 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 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. Similarly, updates are also propagated to those tables. This technology is useful in the following situations: Order is not important in your data, or your query table data is not recursive, or the maximal recursion depth is known in advance.
SQL/XML - Wikipedia
This model is useful if you have to exchange data that contains XML markup with other applications while your SQL applications work uninterrupted. Hybrid Model 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.
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. On the other hand, severe decomposition loses object encapsulation and increases reassembly cost. A balance between data modeling requirements and locking and update characteristics is important for good design.
For example, updates to an XML instance are performed by using new support for partial binary large object BLOB and partial index updates in which the existing stored XML instance is compared to its updated version.