SQL Server: Compare Fields in 2 Tables with PIVOT Query

In this article, we will explore how to compare fields from two tables using a PIVOT query. We’ll examine the provided Stack Overflow question, provide an explanation of the current solution and its limitations, and then present a better approach to achieve the desired result.

Background

To understand the problem at hand, let’s first review the table structure mentioned in the question:

CREATE TABLE [dbo].[tblWidget](
    [ID] [int] NOT NULL,
    [Description] [varchar](50) NOT NULL,
    [UpdatedBy] [varchar](50) NOT NULL,
 CONSTRAINT [PK_tblWidget] PRIMARY KEY CLUSTERED 
(
    [ID] ASC
)WITH (PAD_INDEX = OFF, STATISTICS_NORECOMPUTE = OFF, IGNORE_DUP_KEY = OFF, ALLOW_ROW_LOCKS = ON, ALLOW_PAGE_LOCKS = ON, OPTIMIZE_FOR_SEQUENTIAL_KEY = OFF) ON [PRIMARY]
) ON [PRIMARY]
GO

We also know that the table in each database (dbSource and dbTarget) has one row for simplicity.

Current Solution - PIVOT Query

The current solution presented by the user involves using a PIVOT query to compare only two fields: UpdatedBy. Here’s how it looks:

SELECT 'UpdatedBy' Field, [0] AS [Source], [1] AS [Target]
FROM
(
    SELECT [ID]
          ,[Description]
          ,[UpdatedBy]
          ,1 IsSource
    FROM [dbSource].[dbo].[tblWidget]
    UNION ALL 
    SELECT [ID]
          ,[Description]
          ,[UpdatedBy]
          ,0 IsSource
    FROM [dbTarget].[dbo].[tblWidget]
) a
PIVOT (
    MAX(UpdatedBy)
    FOR IsSource IN ([0], [1])
) AS pvt

Limitations of the Current Solution

The current solution has two main limitations:

• It only compares UpdatedBy, which is not the desired outcome. We want to compare all fields from both tables.
• The result does not follow a logical structure, as it combines rows with different IDs.

Alternative Approach - Joining and Unpivoting

A more effective approach involves joining the two tables using an ID column (assuming that’s the common field) and then unpivoting the columns to rows:

SELECT s.id, x.*
FROM dbsource.tblWidget s
INNER JOIN dbtarget.tblWidget t ON t.id = s.id
CROSS APPLY (
    VALUES 
        ('Description', s.description, t.description),
        ('UpdatedBy',   s.updatedby,   t.updatedby)
) x (field, source, target)

This approach has several advantages:

• It correctly compares all fields from both tables.
• The result follows a logical structure, with each row representing a specific ID and its corresponding values.

Explanation of the Alternative Approach

Let’s break down the alternative approach step by step:

1. Joining Tables: We start by joining dbsource.tblWidget and dbtarget.tblWidget on their common ID column using an INNER JOIN.
2. Cross Apply: After joining the tables, we use a CROSS APPLY operation to unpivot the columns (Description, UpdatedBy) into separate rows.
3. VALUES Clause: Inside the CROSS APPLY clause, we define a VALUES expression that creates two new values for each column. The first value is the column name, and the second value is the actual column value from the source or target table.

Conclusion

Comparing fields from two tables using a PIVOT query can be challenging when you need to consider all available columns. The provided alternative approach of joining and unpivoting columns offers a more effective solution for achieving your desired result. By understanding the inner workings of this approach, you can create powerful queries that accurately compare data across multiple sources.

Example Use Cases

Here are some example use cases where this technique can be applied:

• Data Comparison: When comparing data from different databases or tables to identify discrepancies or differences.
• Business Intelligence: In business intelligence scenarios where you need to analyze and compare data from various sources to gain insights into business performance.
• Data Integration: During data integration projects, this technique can be used to synchronize data between multiple systems or databases.

Best Practices

To ensure the best results when using this approach:

• Make sure to use a common column that exists in both tables as the join key.
• Define the columns correctly inside the CROSS APPLY clause to achieve the desired outcome.
• Consider optimizing performance by indexing the join column and columns used in the query.

Last modified on 2023-11-09