How Can SQL Identify Changes in Column Values Over Time?

Identifying Changes in Column Values Using SQL

Problem:

Suppose you have a table with two columns: Value and Time. You want to identify rows where the Value column has changed. In other words, you need to find the moments when the stored value changed, denoted by starred rows.

Solution:

One approach to solve this problem involves leveraging window functions and row numbers within a SQL statement:

1. Introduce Row Numbers:

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

   This step introduces a new column called rn (row number) that assigns a unique sequence number to each row within each Value partition, in ascending order of Time.

2. Identify Changes:

   SELECT * FROM x WHERE rn = 1;

   This query filters the results to only include rows with rn equal to 1. These are the first rows in each Value partition, representing the start of value changes.

Additional Consideration for Up and Down Values:

If the Value column can both increase and decrease, a more complex approach is required:

1. Create Temporary Table:

   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');

   Create a temporary table with the sample data to illustrate the process.

2. Introduce Row Numbers (Again):

   WITH x AS (
       SELECT *, rn = ROW_NUMBER() OVER (ORDER BY time)
       FROM @x
   )

3. Identify Value Changes:

   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 left outer join between the table with the row numbers and a shifted version of itself (y) to check for changes in the Value column between adjacent rows. Rows with non-NULL values for y.value represent changes.

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