Pivoting data in SQL Server

Very often there is a need to pivot (cross-tab) normalized data for some reporting purposes. While this is best done with reporting tools (Excel is one example with powerful pivoting capabilities), sometimes it needs to be done on the database side.

The discussion here is limited to static pivoting (that is when the values to pivot are known). Dynamic pivoting is accomplished by using dynamic SQL and is based on the same techniques, just dynamically building the pivoting query.

Here are a few methods and techniques to implement that in SQL Server.

Given the following data:

 OrderId    OrderDate  Amount
----------- ---------- ------
1           2007-01-01 10.50
2           2007-01-26 12.50
3           2007-01-30 12.00
4           2007-02-14 13.75
5           2007-02-20 10.00
6           2007-03-06 15.00
7           2007-03-10 17.50
8           2007-03-29 20.00

We would like to return this result set:

 OrderYear   Jan   Feb   Mar
----------- ----- ----- -----
2007        35.00 23.75 52.50

Creating the sample Orders table:

CREATE TABLE Orders (
 order_id INT IDENTITY(1, 1) NOT NULL PRIMARY KEY,
 order_date DATETIME NOT NULL DEFAULT CURRENT_TIMESTAMP,
 amount DECIMAL(8, 2) NOT NULL DEFAULT 0
        CHECK (amount >= 0));
 
INSERT INTO Orders
  (order_date, amount)
SELECT '20070101', 10.50
UNION ALL
SELECT '20070126', 12.50
UNION ALL
SELECT '20070130', 12.00
UNION ALL
SELECT '20070214', 13.75
UNION ALL
SELECT '20070220', 10.00
UNION ALL
SELECT '20070306', 15.00
UNION ALL
SELECT '20070310', 17.50
UNION ALL
SELECT '20070329', 20.00;

Using CASE

CASE can be very handy for pivoting. It allows writing flexible logic and to transform the data as needed. Also, it is a very efficient method as it requires a one pass scan of the data.

SELECT DATEPART(yyyy, order_date) AS OrderYear,
       SUM(CASE WHEN DATEPART(m, order_date) = 1
                THEN amount ELSE 0 END) AS 'Jan',
       SUM(CASE WHEN DATEPART(m, order_date) = 2
                THEN amount ELSE 0 END) AS 'Feb',
       SUM(CASE WHEN DATEPART(m, order_date) = 3
                THEN amount ELSE 0 END) AS 'Mar'
FROM Orders
GROUP BY DATEPART(yyyy, order_date);

Using Matrix table

This method requires creating a matrix table with 1 for the significant columns and 0 for columns to be ignored. Then joining the matrix table to the data table based on the pivoting column will produce the results:

CREATE TABLE MonthMatrix (
  month_nbr INT NOT NULL PRIMARY KEY
            CHECK (month_nbr BETWEEN 1 AND 12),
  jan INT NOT NULL DEFAULT 0
      CHECK (jan IN (0, 1)),
  feb INT NOT NULL DEFAULT 0
      CHECK (feb IN (0, 1)),
  mar INT NOT NULL DEFAULT 0
      CHECK (mar IN (0, 1)),
  apr INT NOT NULL DEFAULT 0
      CHECK (apr IN (0, 1)),
  may INT NOT NULL DEFAULT 0
      CHECK (may IN (0, 1)),
  jun INT NOT NULL DEFAULT 0
      CHECK (jun IN (0, 1)),
  jul INT NOT NULL DEFAULT 0
      CHECK (jul IN (0, 1)),
  aug INT NOT NULL DEFAULT 0
      CHECK (aug IN (0, 1)),
  sep INT NOT NULL DEFAULT 0
      CHECK (sep IN (0, 1)),
  oct INT NOT NULL DEFAULT 0
      CHECK (oct IN (0, 1)),
  nov INT NOT NULL DEFAULT 0
      CHECK (nov IN (0, 1)),
  dec INT NOT NULL DEFAULT 0
      CHECK (dec IN (0, 1)));
 
-- Populate the matrix table
INSERT INTO MonthMatrix (month_nbr, jan) VALUES (1, 1);
INSERT INTO MonthMatrix (month_nbr, feb) VALUES (2, 1);
INSERT INTO MonthMatrix (month_nbr, mar) VALUES (3, 1);
INSERT INTO MonthMatrix (month_nbr, apr) VALUES (4, 1);
INSERT INTO MonthMatrix (month_nbr, may) VALUES (5, 1);
INSERT INTO MonthMatrix (month_nbr, jun) VALUES (6, 1);
INSERT INTO MonthMatrix (month_nbr, jul) VALUES (7, 1);
INSERT INTO MonthMatrix (month_nbr, aug) VALUES (8, 1);
INSERT INTO MonthMatrix (month_nbr, sep) VALUES (9, 1);
INSERT INTO MonthMatrix (month_nbr, oct) VALUES (10, 1);
INSERT INTO MonthMatrix (month_nbr, nov) VALUES (11, 1);
INSERT INTO MonthMatrix (month_nbr, dec) VALUES (12, 1);
 
-- Use the matrix table to pivot
SELECT DATEPART(yyyy, order_date) AS OrderYear,
       SUM(amount * jan) AS 'Jan',
       SUM(amount * feb) AS 'Feb',
       SUM(amount * mar) AS 'Mar'
FROM Orders AS O
JOIN MonthMatrix AS M
  ON DATEPART(m, O.order_date) = M.month_nbr
GROUP BY DATEPART(yyyy, order_date);

The David Rozenshtein method

This method is based on the formula: 1 – ABS(SIGN(x – y)). This formula returns 1 when x = y, and 0 otherwise. In a way it mimics the matrix table approach.

SELECT DATEPART(yyyy, order_date) AS OrderYear,
       SUM(amount * (1 - ABS(SIGN(DATEPART(m, order_date) - 1)))) AS 'Jan',
       SUM(amount * (1 - ABS(SIGN(DATEPART(m, order_date) - 2)))) AS 'Feb',
       SUM(amount * (1 - ABS(SIGN(DATEPART(m, order_date) - 3)))) AS 'Mar'
FROM Orders
GROUP BY DATEPART(yyyy, order_date);

The PIVOT operator in SQL Server 2005

SQL Server 2005 provides built-in pivoting mechanism via the PIVOT operator.

SELECT OrderYear,
       [1] AS 'Jan',
       [2] AS 'Feb',
       [3] AS 'Mar'
FROM (SELECT DATEPART(yyyy, order_date),
             DATEPART(m, order_date),
             amount
      FROM Orders) AS O (OrderYear, month_nbr, amount) 
PIVOT
(SUM(amount) FOR month_nbr IN ([1], [2], [3])) AS P;

There are some other methods to implement pivoting (like using subqueries, multiple joins, or the APPLY operator in SQL Server 2005) but I am not showing examples of those as I do not find them practical, especially with large number of values to pivot.

Additional Resources:

Using PIVOT and UNPIVOT
http://msdn2.microsoft.com/en-us/library/ms177410.aspx