How Can I Efficiently Transpose Rows to Columns in SQL Server?

Transposing Rows to Columns in SQL Server

Transposing rows to columns in SQL Server is a common task when working with data that is stored in a tabular format. Traditionally, this has been achieved using cursors, which can be time-consuming and inefficient. This article explores alternative methods for row transposition, offering solutions that are both elegant and performant.

Conditional Aggregation

One approach is to use conditional aggregation, which leverages the COALESCE() function to handle missing values.

SELECT TimeSeconds,
       COALESCE(MAX(CASE WHEN TagID = 'A1' THEN Value END), 'n/a') A1,
       COALESCE(MAX(CASE WHEN TagID = 'A2' THEN Value END), 'n/a') A2,
       COALESCE(MAX(CASE WHEN TagID = 'A3' THEN Value END), 'n/a') A3,
       COALESCE(MAX(CASE WHEN TagID = 'A4' THEN Value END), 'n/a') A4
  FROM table1
 GROUP BY TimeSeconds

This query generates output with placeholder values ('n/a') for missing data.

PIVOT

Another option is to use the PIVOT function, which allows for dynamic column creation.

SELECT TimeSeconds, A1, A2, A3, A4
  FROM
(
  SELECT TimeSeconds, TagID, Value
    FROM table1
) s
PIVOT
(
  MAX(Value) FOR TagID IN (A1, A2, A3, A4)
) p

This approach generates output with NULL values for missing data.

Dynamic SQL

If the number of columns is not fixed and must be determined dynamically, dynamic SQL can be employed.

DECLARE @cols NVARCHAR(MAX), @sql NVARCHAR(MAX)

SET @cols = STUFF((SELECT DISTINCT ',' + QUOTENAME(TagID)
            FROM Table1
            ORDER BY 1
            FOR XML PATH(''), TYPE
            ).value('.', 'NVARCHAR(MAX)'),1,1,'')

SET @sql = 'SELECT TimeSeconds, ' + @cols + '
              FROM
            (
              SELECT TimeSeconds, TagID, Value
                FROM table1
            ) s
            PIVOT
            (
              MAX(Value) FOR TagID IN (' + @cols + ')
            ) p'

EXECUTE(@sql)

This query constructs the dynamic PIVOT statement based on the unique TagID values in the table.

These methods provide efficient and customizable solutions for transposing rows to columns in SQL Server. By selecting the appropriate approach based on data characteristics and performance requirements, you can simplify data manipulation tasks and improve query execution efficiency.

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