Скачать или смотреть Efficiently Parse XML Data in SQL Server for Reports

Learn how to efficiently parse XML data stored in SQL Server into a more usable format for reporting in SQL Server Report Writer.
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This video is based on the question https://stackoverflow.com/q/76301108/ asked by the user 'Stuart Riches' ( https://stackoverflow.com/u/21936110/ ) and on the answer https://stackoverflow.com/a/76301222/ provided by the user 'siggemannen' ( https://stackoverflow.com/u/13061224/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

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Introduction

When working with SQL Server, developers often need to manage complex data structures, such as XML. This article addresses a common scenario: extracting and organizing XML data from a database table column into a flat, readable format that can be easily utilized in reports. The specific case involves parsing XML data from the CustomerCrossReferences table containing multiple CustomColumn elements, which need to be transformed into distinct dataset rows for effective reporting.

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In this setup, the customColumns column holds XML formatted data that captures various customer product properties. The goal is to extract this data and format it into a clear output table that enhances reporting clarity.

The Problem

The XML data in the customColumns is structured with multiple CustomColumn entries that include fields like Name, DataType, and Value. A straightforward but cumbersome SQL query method was proposed, which makes multiple calls to pull data into a suitable format. However, this method is inefficient for datasets with numerous custom columns, making it impractical for larger applications.

Example of Current Dataset Format

The dataset prior to transformation has the following structure:

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With approximately 20 CustomColumn entries, this methodology becomes inefficient and tedious to maintain.

The Solution

To simplify the retrieval and formatting of XML data, the XQuery nodes() method provides a powerful and efficient solution. This approach allows for extracting elements from the XML structure and presenting them in a relational, row-based format effortlessly.

Step-by-Step Breakdown

Use CROSS APPLY with nodes(): Leverage the CROSS APPLY operator in conjunction with the nodes() method to create a derived table that can output each CustomColumn element as its own row.

Retrieve Individual Properties: Combine the value() method to fetch the Name, DataType, and Value for each CustomColumn element.

Implementation

Here's how the SQL query looks:

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Explanation of the Code

CROSS APPLY: This operator allows us to join each row in the CustomerCrossReferences table with the rows generated by the nodes() method. This way, each CustomColumn in the XML can be treated as a separate row.

n.value('(...): This part extracts the relevant XML data fields into our final result set. Each (Name/text())[1], (DataType/text())[1], and (Value/text())[1] points to the associated XML tag we want to extract.

Conclusion

By employing the CROSS APPLY and nodes() methods along with the value() function, we can efficiently parse XML data stored in SQL Server tables. This solution is not only concise but also scalable for larger datasets with numerous CustomColumn entries. As a result, developers can produce structured datasets suitable for report generation with ease.

Incorporating this improved method into your SQL workflows will streamline reporting efforts and enhance the clarity of the data presented.