Selecting Rows with Value Changes Using ROW_NUMBER

In the context of a table where the value column reflects a changing state over time, selecting the moments when that value changed can be a valuable analytical task. This article presents a solution using the ROW_NUMBER function to identify such rows, considering both scenarios where values can increase or fluctuate.

Solution for Increasing Values

Assuming values can only increase, we employ the following approach:

;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;

The ROW_NUMBER function partitions the table by the value column and assigns consecutive numbers to rows in order of their time values within each partition. By selecting rows where the ROW_NUMBER is 1, we retrieve the first occurrence of each distinct value, which signifies a change in value.

Solution for Fluctuating Values

When values can fluctuate, we adapt our approach to address this complexity:

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;

In this case, we assign ROW_NUMBERS to the entire dataset in chronological order. We then perform a LEFT OUTER JOIN of the table with itself, matching rows with consecutive ROW_NUMBERS and non-equal values. The result ensures the selection of only those rows that have a distinct value in the following row.