How Can I Efficiently Identify Rows Where a Column Value Changes in SQL?

Selecting Rows Where Column Value Has Changed: SQL Techniques

Determining the instances where a column value undergoes a transition is a critical operation in various data analysis scenarios. This article explores techniques for efficiently identifying such changes in a table.

Problem Statement

Consider the following table with "Value" and "Time" columns:

Value	Time
0	15/06/2012 8:03:43 PM
1	15/06/2012 8:03:43 PM	*
1	15/06/2012 8:03:48 PM
1	15/06/2012 8:03:53 PM
1	15/06/2012 8:03:58 PM	*
2	15/06/2012 8:04:03 PM	*
2	15/06/2012 8:04:08 PM
3	15/06/2012 8:04:13 PM	*
3	15/06/2012 8:04:18 PM
3	15/06/2012 8:04:23 PM
2	15/06/2012 8:04:28 PM	*
2	15/06/2012 8:04:33 PM

The task is to identify the rows marked with "*," indicating transitions in the "Value" column.

Solution

Using Window Functions (SQL Server 2012 and Higher)

With window functions introduced in SQL Server 2012, this operation can be performed efficiently:

;WITH x AS
(
  SELECT value, time, rn = ROW_NUMBER() OVER 
  (PARTITION BY Value ORDER BY Time)
  FROM dbo.table
)
SELECT * FROM x WHERE rn = 1;

This query calculates the row number within each partition of "Value" and selects the first row (rn = 1) for each partition.

Using Table Joins (SQL Server 2008 and Earlier)

For SQL Server versions prior to 2012, the following approach can be used:

DECLARE @x TABLE(value INT, [time] DATETIME)

INSERT @x VALUES
(0,'20120615 8:03:43 PM'),--
(1,'20120615 8:03:43 PM'),--*
(1,'20120615 8:03:48 PM'),--
(1,'20120615 8:03:53 PM'),--
(1,'20120615 8:03:58 PM'),--
(2,'20120615 8:04:03 PM'),--*
(2,'20120615 8:04:08 PM'),--
(3,'20120615 8:04:13 PM'),--*
(3,'20120615 8:04:18 PM'),--
(3,'20120615 8:04:23 PM'),--
(2,'20120615 8:04:28 PM'),--*
(2,'20120615 8:04:33 PM');

;WITH x AS
(
  SELECT *, rn = ROW_NUMBER() OVER (ORDER BY time)
  FROM @x
)
SELECT x.value, x.[time]
FROM x LEFT OUTER JOIN x AS y
ON x.rn = y.rn + 1
AND x.value <> y.value
WHERE y.value IS NOT NULL;

This query performs a self-join on the table, comparing adjacent rows to identify value changes. It requires a separate table variable to store intermediate results.

Note: While window functions offer better performance, they may not be available in all versions of SQL Server. Choose the approach that best suits your version and performance requirements.

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