# CASE
The CASE expression is used to implement if-then logic.
# Use CASE to COUNT the number of rows in a column match a condition.
Use Case
CASE
can be used in conjunction with SUM
to return a count of only those items matching a pre-defined condition. (This is similar to COUNTIF
in Excel.)
The trick is to return binary results indicating matches, so the "1"s returned for matching entries can be summed for a count of the total number of matches.
Given this table ItemSales
, let's say you want to learn the total number of items that have been categorized as "Expensive":
Id | ItemId | Price | PriceRating |
---|---|---|---|
1 | 100 | 34.5 | EXPENSIVE |
2 | 145 | 2.3 | CHEAP |
3 | 100 | 34.5 | EXPENSIVE |
4 | 100 | 34.5 | EXPENSIVE |
5 | 145 | 10 | AFFORDABLE |
Query
SELECT
COUNT(Id) AS ItemsCount,
SUM ( CASE
WHEN PriceRating = 'Expensive' THEN 1
ELSE 0
END
) AS ExpensiveItemsCount
FROM ItemSales
Results:
ItemsCount | ExpensiveItemsCount |
---|---|
5 | 3 |
Alternative:
SELECT
COUNT(Id) as ItemsCount,
SUM (
CASE PriceRating
WHEN 'Expensive' THEN 1
ELSE 0
END
) AS ExpensiveItemsCount
FROM ItemSales
# Searched CASE in SELECT (Matches a boolean expression)
The searched CASE returns results when a boolean expression is TRUE.
(This differs from the simple case, which can only check for equivalency with an input.)
SELECT Id, ItemId, Price,
CASE WHEN Price < 10 THEN 'CHEAP'
WHEN Price < 20 THEN 'AFFORDABLE'
ELSE 'EXPENSIVE'
END AS PriceRating
FROM ItemSales
Id | ItemId | Price | PriceRating |
---|---|---|---|
1 | 100 | 34.5 | EXPENSIVE |
2 | 145 | 2.3 | CHEAP |
3 | 100 | 34.5 | EXPENSIVE |
4 | 100 | 34.5 | EXPENSIVE |
5 | 145 | 10 | AFFORDABLE |
# CASE in a clause ORDER BY
We can use 1,2,3.. to determine the type of order:
SELECT * FROM DEPT
ORDER BY
CASE DEPARTMENT
WHEN 'MARKETING' THEN 1
WHEN 'SALES' THEN 2
WHEN 'RESEARCH' THEN 3
WHEN 'INNOVATION' THEN 4
ELSE 5
END,
CITY
ID | REGION | CITY | DEPARTMENT | EMPLOYEES_NUMBER |
---|---|---|---|---|
12 | New England | Boston | MARKETING | 9 |
15 | West | San Francisco | MARKETING | 12 |
9 | Midwest | Chicago | SALES | 8 |
14 | Mid-Atlantic | New York | SALES | 12 |
5 | West | Los Angeles | RESEARCH | 11 |
10 | Mid-Atlantic | Philadelphia | RESEARCH | 13 |
4 | Midwest | Chicago | INNOVATION | 11 |
2 | Midwest | Detroit | HUMAN RESOURCES | 9 |
# Shorthand CASE in SELECT
CASE
's shorthand variant evaluates an expression (usually a column) against a series of values. This variant is a bit shorter, and saves repeating the evaluated expression over and over again. The ELSE
clause can still be used, though:
SELECT Id, ItemId, Price,
CASE Price WHEN 5 THEN 'CHEAP'
WHEN 15 THEN 'AFFORDABLE'
ELSE 'EXPENSIVE'
END as PriceRating
FROM ItemSales
A word of caution. It's important to realize that when using the short variant the entire statement is evaluated at each WHEN
. Therefore the following statement:
SELECT
CASE ABS(CHECKSUM(NEWID())) % 4
WHEN 0 THEN 'Dr'
WHEN 1 THEN 'Master'
WHEN 2 THEN 'Mr'
WHEN 3 THEN 'Mrs'
END
may produce a NULL
result. That is because at each WHEN
NEWID()
is being called again with a new result. Equivalent to:
SELECT
CASE
WHEN ABS(CHECKSUM(NEWID())) % 4 = 0 THEN 'Dr'
WHEN ABS(CHECKSUM(NEWID())) % 4 = 1 THEN 'Master'
WHEN ABS(CHECKSUM(NEWID())) % 4 = 2 THEN 'Mr'
WHEN ABS(CHECKSUM(NEWID())) % 4 = 3 THEN 'Mrs'
END
Therefore it can miss all the WHEN
cases and result as NULL
.
# Using CASE in UPDATE
sample on price increases:
UPDATE ItemPrice
SET Price = Price *
CASE ItemId
WHEN 1 THEN 1.05
WHEN 2 THEN 1.10
WHEN 3 THEN 1.15
ELSE 1.00
END
# CASE use for NULL values ordered last
in this way '0' representing the known values are ranked first, '1' representing the NULL values are sorted by the last:
SELECT ID
,REGION
,CITY
,DEPARTMENT
,EMPLOYEES_NUMBER
FROM DEPT
ORDER BY
CASE WHEN REGION IS NULL THEN 1
ELSE 0
END,
REGION
ID | REGION | CITY | DEPARTMENT | EMPLOYEES_NUMBER |
---|---|---|---|---|
10 | Mid-Atlantic | Philadelphia | RESEARCH | 13 |
14 | Mid-Atlantic | New York | SALES | 12 |
9 | Midwest | Chicago | SALES | 8 |
12 | New England | Boston | MARKETING | 9 |
5 | West | Los Angeles | RESEARCH | 11 |
15 | NULL | San Francisco | MARKETING | 12 |
4 | NULL | Chicago | INNOVATION | 11 |
2 | NULL | Detroit | HUMAN RESOURCES | 9 |
# CASE in ORDER BY clause to sort records by lowest value of 2 columns
Imagine that you need sort records by lowest value of either one of two columns.
Some databases could use a non-aggregated MIN()
or LEAST()
function for this (... ORDER BY MIN(Date1, Date2)
), but in standard SQL, you have to use a CASE
expression.
The CASE
expression in the query below looks at the Date1
and Date2
columns, checks which column has the lower value, and sorts the records depending on this value.
# Sample data
Id | Date1 | Date2 |
---|---|---|
1 | 2017-01-01 | 2017-01-31 |
2 | 2017-01-31 | 2017-01-03 |
3 | 2017-01-31 | 2017-01-02 |
4 | 2017-01-06 | 2017-01-31 |
5 | 2017-01-31 | 2017-01-05 |
6 | 2017-01-04 | 2017-01-31 |
# Query
SELECT Id, Date1, Date2
FROM YourTable
ORDER BY CASE
WHEN COALESCE(Date1, '1753-01-01') < COALESCE(Date2, '1753-01-01') THEN Date1
ELSE Date2
END
# Results
Id | Date1 | Date2 |
---|---|---|
1 | 2017-01-01 | 2017-01-31 |
3 | 2017-01-31 | 2017-01-02 |
2 | 2017-01-31 | 2017-01-03 |
6 | 2017-01-04 | 2017-01-31 |
5 | 2017-01-31 | 2017-01-05 |
4 | 2017-01-06 | 2017-01-31 |
# Explanation
As you see row with Id = 1
is first, that because Date1
have lowest record from entire table 2017-01-01
, row where Id = 3
is second that because Date2
equals to 2017-01-02
that is second lowest value from table and so on.
So we have sorted records from 2017-01-01
to 2017-01-06
ascending and no care on which one column Date1
or Date2
are those values.
# Syntax
WHEN compare1 THEN result1
[WHEN compare2 THEN result2]...
[ELSE resultX]
END
WHEN condition1 THEN result1
[WHEN condition2 THEN result2]...
[ELSE resultX]
END
# Remarks
The simple CASE expression returns the first result whose compareX
value is equal to the input_expression
.
The searched CASE expression returns the first result whose conditionX
is true.