PIVOT and UNPIVOT
| Feature compatibility | Amazon SCT / Amazon DMS automation level | Amazon SCT action code index | Key differences |
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Straightforward rewrite to use traditional SQL syntax. |
SQL Server Usage
PIVOT and UNPIVOT are relational operations used to transform a set by rotating rows into columns and columns into rows.
PIVOT
The PIVOT operator consists of several clauses and implied expressions.
The anchor column isn’t pivoted and results in a single row for each unique value, similar to GROUP BY.
The pivoted columns are derived from the PIVOT clause and are the row values transformed into columns. The values for these columns are derived from the source column defined in the PIVOT clause.
PIVOT Syntax
SELECT <Anchor column>, [Pivoted Column 1] AS <Alias>, [Pivoted column 2] AS <Alias> ...n FROM (<SELECT Statement of Set to be Pivoted>) AS <Set Alias> PIVOT ( <Aggregate Function>(<Aggregated Column>) FOR [<Column With the Values for the Pivoted Columns Names>] IN ( [Pivoted Column 1], [Pivoted column 2] ...) ) AS <Pivot Table Alias>;
PIVOT Examples
The following example creates and populates the Orders table.
CREATE TABLE Orders ( OrderID INT NOT NULL IDENTITY(1,1) PRIMARY KEY, OrderDate DATE NOT NULL, Customer VARCHAR(20) NOT NULL );
INSERT INTO Orders (OrderDate, Customer)
VALUES
('20180101', 'John'),
('20180201', 'Mitch'),
('20180102', 'John'),
('20180104', 'Kevin'),
('20180104', 'Larry'),
('20180104', 'Kevin'),
('20180104', 'Kevin');
The following example creates a simple PIVOT for the number of orders for each day. Days of month from 5 to 31 are omitted for example simplicity.
SELECT 'Number of Orders for Day' AS DayOfMonth,
[1], [2], [3], [4] /*...[31]*/
FROM (
SELECT OrderID,
DAY(OrderDate) AS OrderDay
FROM Orders
) AS SourceSet
PIVOT
(
COUNT(OrderID)
FOR OrderDay IN ([1], [2], [3], [4] /*...[31]*/)
) AS PivotSet;
For the preceding example, the result looks as shown following.
DayOfMonth 1 2 3 4 /*...[31]*/ Number of Orders for Day 2 1 0 4
The result set is now oriented in rows against columns. The first column is the description of the columns to follow.
PIVOT for number of orders for each day, for each customer.
SELECT Customer,
[1], [2], [3], [4] /*...[31]*/
FROM (
SELECT OrderID,
Customer,
DAY(OrderDate) AS OrderDay
FROM Orders
) AS SourceSet
PIVOT
(
COUNT(OrderID)
FOR OrderDay IN ([1], [2], [3], [4] /*...[31]*/)
) AS PivotSet;
Customer 1 2 3 4 John 1 1 0 0 Kevin 0 0 0 3 Larry 0 0 0 1 Mitch 1 0 0 0
UNPIVOT
UNPIVOT is similar to PIVOT in reverse, but spreads existing column values into rows.
The source set is similar to the result of the PIVOT with values pertaining to particular entities listed in columns. Because the result set has more rows than the source, aggregations aren’t required.
It is less commonly used than PIVOT because most data in relational databases have attributes in columns; not the other way around.
UNPIVOT Examples
The following example creates and populates the pivot-like EmployeeSales table. This is most likely a view or a set from an external source.
CREATE TABLE EmployeeSales ( SaleDate DATE NOT NULL PRIMARY KEY, John INT, Kevin INT, Mary INT );
INSERT INTO EmployeeSales
VALUES
('20180101', 150, 0, 300),
('20180102', 0, 0, 0),
('20180103', 250, 50, 0),
('20180104', 500, 400, 100);
The following example unpivots employee sales for each date into individual rows for each employee.
SELECT SaleDate, Employee, SaleAmount FROM ( SELECT SaleDate, John, Kevin, Mary FROM EmployeeSales ) AS SourceSet UNPIVOT ( SaleAmount FOR Employee IN (John, Kevin, Mary) )AS UnpivotSet;
For the preceding example, the result looks as shown following.
SaleDate Employee SaleAmount 2018-01-01 John 150 2018-01-01 Kevin 0 2018-01-01 Mary 300 2018-01-02 John 0 2018-01-02 Kevin 0 2018-01-02 Mary 0 2018-01-03 John 250 2018-01-03 Kevin 50 2018-01-03 Mary 0 2018-01-04 John 500 2018-01-04 Kevin 400 2018-01-04 Mary 100
For more information, see FROM - Using PIVOT and UNPIVOT
PostgreSQL Usage
Amazon Aurora PostgreSQL-Compatible Edition (Aurora PostgreSQL) doesn’t support the PIVOT and UNPIVOT relational operators.
You can rewrite the functionality of these operators to use standard SQL syntax, as shown in the following examples.
PIVOT Examples
The following example creates and populates the Orders table.
CREATE TABLE Orders ( OrderID SERIAL PRIMARY KEY, OrderDate DATE NOT NULL, Customer VARCHAR(20) NOT NULL );
INSERT INTO Orders (OrderDate, Customer)
VALUES
('20180101', 'John'),
('20180201', 'Mitch'),
('20180102', 'John'),
('20180104', 'Kevin'),
('20180104', 'Larry'),
('20180104', 'Kevin'),
('20180104', 'Kevin');
The following example creates a simple PIVOT for the number of orders for each day. Days of month from 5 to 31 are omitted for example simplicity.
SELECT 'Number of Orders for Day' AS DayOfMonth,
COUNT(CASE WHEN date_part('day', OrderDate) = 1 THEN 'OrderDate' ELSE NULL END) AS "1",
COUNT(CASE WHEN date_part('day', OrderDate) = 2 THEN 'OrderDate' ELSE NULL END) AS "2",
COUNT(CASE WHEN date_part('day', OrderDate) = 3 THEN 'OrderDate' ELSE NULL END) AS "3",
COUNT(CASE WHEN date_part('day', OrderDate) = 4 THEN 'OrderDate' ELSE NULL END) AS "4" /*...[31]*/
FROM Orders AS O;
For the preceding example, the result looks as shown following.
DayOfMonth 1 2 3 4 /*...[31]*/ Number of Orders for Day 2 1 0 4
PIVOT for number of orders for each day, for each customer.
SELECT Customer,
COUNT(CASE WHEN date_part('day', OrderDate) = 1 THEN 'OrderDate' ELSE NULL END) AS "1",
COUNT(CASE WHEN date_part('day', OrderDate) = 2 THEN 'OrderDate' ELSE NULL END) AS "2",
COUNT(CASE WHEN date_part('day', OrderDate) = 3 THEN 'OrderDate' ELSE NULL END) AS "3",
COUNT(CASE WHEN date_part('day', OrderDate) = 4 THEN 'OrderDate' ELSE NULL END) AS "4" /*...[31]*/
FROM Orders AS O
GROUP BY Customer;
For the preceding example, the result looks as shown following.
Customer 1 2 3 4 John 1 1 0 0 Kevin 0 0 0 3 Larry 0 0 0 1 Mitch 1 0 0 0
UNPIVOT Examples
The following example creates and populates the pivot-like EmployeeSales table. In real life this will most likely be a view, or a set from an external source.
CREATE TABLE EmployeeSales ( SaleDate DATE NOT NULL PRIMARY KEY, John INT, Kevin INT, Mary INT );
INSERT INTO EmployeeSales
VALUES
('20180101', 150, 0, 300),
('20180102', 0, 0, 0),
('20180103', 250, 50, 0),
('20180104', 500, 400, 100);
The following example unpivots employee sales for each date into individual rows for each employee.
SELECT SaleDate, Employee, SaleAmount
FROM (
SELECT SaleDate,
Employee,
CASE
WHEN Employee = 'John' THEN 'John'
WHEN Employee = 'Kevin' THEN 'Kevin'
WHEN Employee = 'Mary' THEN 'Mary'
END AS SaleAmount
FROM EmployeeSales as emp
CROSS JOIN
(
SELECT 'John' AS Employee
UNION ALL
SELECT 'Kevin'
UNION ALL
SELECT 'Mary'
) AS Employees
) AS UnpivotedSet;
For the preceding example, the result looks as shown following.
SaleDate Employee SaleAmount 2018-01-01 John 150 2018-01-01 Kevin 0 2018-01-01 Mary 300 2018-01-02 John 0 2018-01-02 Kevin 0 2018-01-02 Mary 0 2018-01-03 John 250 2018-01-03 Kevin 50 2018-01-03 Mary 0 2018-01-04 John 500 2018-01-04 Kevin 400 2018-01-04 Mary 100