PIVOT and UNPIVOT for T-SQL
This topic provides reference content on migrating from Microsoft SQL Server 2019 to Amazon Aurora MySQL, specifically focusing on the PIVOT and UNPIVOT operators. You can use this guidance to understand the compatibility differences between these database systems and learn how to adapt your SQL queries.
Feature compatibility | AWS SCT / AWS DMS automation level | AWS SCT action code index | Key differences |
---|---|---|---|
|
|
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 is the column that isn’t be 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.
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
Create and populate 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');
Create 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 Per 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 Each Day 2 1 0 4
Note
The result set is now oriented in rows and 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
Create an populate the pivot-like EmployeeSales
table. In real life, 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);
Unpivot 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;
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
MySQL Usage
Amazon Aurora MySQL-Compatible Edition (Aurora MySQL) doesn’t support the PIVOT
and UNPIVOT
relational operators.
Functionality of both operators can be rewritten to use standard SQL syntax, as shown in the following examples.
PIVOT Examples
Create and populate the Orders
table.
CREATE TABLE Orders ( OrderID INT AUTO_INCREMENT NOT NULL 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');
Create 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 Per Day' AS DayOfMonth, COUNT(CASE WHEN DAY(OrderDate) = 1 THEN 'OrderDate' ELSE NULL END) AS '1', COUNT(CASE WHEN DAY(OrderDate) = 2 THEN 'OrderDate' ELSE NULL END) AS '2', COUNT(CASE WHEN DAY(OrderDate) = 3 THEN 'OrderDate' ELSE NULL END) AS '3', COUNT(CASE WHEN 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 Each Day 2 1 0 4
PIVOT
for number of orders for each day for each customer.
SELECT Customer, COUNT(CASE WHEN DAY(OrderDate) = 1 THEN 'OrderDate' ELSE NULL END) AS '1', COUNT(CASE WHEN DAY(OrderDate) = 2 THEN 'OrderDate' ELSE NULL END) AS '2', COUNT(CASE WHEN DAY(OrderDate) = 3 THEN 'OrderDate' ELSE NULL END) AS '3', COUNT(CASE WHEN DAY(OrderDate) = 4 THEN 'OrderDate' ELSE NULL END) AS '4' /*...[31]*/ FROM Orders AS O GROUP BY Customer;
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
Create an populate the pivot-like EmployeeSales
table. In real life, this is most likely a view or a set from an external source.
CREATE TABLE EmplyeeSales ( SaleDate DATE NOT NULL PRIMARY KEY, John INT, Kevin INT, Mary INT );
INSERT INTO EmplyeeSales VALUES ('20180101', 150, 0, 300), ('20180102', 0, 0, 0), ('20180103', 250, 50, 0), ('20180104', 500, 400, 100);
Unpivot 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 CROSS JOIN ( SELECT 'John' AS Employee UNION ALL SELECT 'Kevin' UNION ALL SELECT 'Mary' ) AS Employees ) AS UnpivotedSet;
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 MySQL/Pivot table