One of the best features in SQL are window functions. Dimitri Fontaine put it bluntly:

There was SQL before window functions and SQL after window functions

If you’re lucky enough to be using any of these databases, then you can use window functions yourself:

- CUBRID
- DB2
- Firebird
- H2
- Informix
- MariaDB
- MySQL
- Oracle
- PostgreSQL
- SQLite
- SQL Server
- Sybase SQL Anywhere
- Teradata

One of the most obvious and useful set of window functions are ranking functions where rows from your result set are ranked according to a certain scheme. There are three ranking functions:

`ROW_NUMBER()`

`RANK()`

`DENSE_RANK()`

The difference is easy to remember. For the examples, let’s assume we have this table (using PostgreSQL syntax):

CREATE TABLE t(v) AS SELECT * FROM ( VALUES('a'),('a'),('a'),('b'), ('c'),('c'),('d'),('e') ) t(v)

**ROW_NUMBER()**

… assigns unique numbers to each row within the `PARTITION`

given the `ORDER BY`

clause. So you’d get:

SELECT v, ROW_NUMBER() OVER() FROM t

Note that some SQL dialects (e.g. SQL Server) require an explicit `ORDER BY`

clause in the `OVER()`

clause:

SELECT v, ROW_NUMBER() OVER(ORDER BY v) FROM t

The above query returns:

| V | ROW_NUMBER | |---|------------| | a | 1 | | a | 2 | | a | 3 | | b | 4 | | c | 5 | | c | 6 | | d | 7 | | e | 8 |

_{(see also this SQLFiddle)}

**RANK()**

… behaves like `ROW_NUMBER()`

, except that “equal” rows are ranked the same. If we substitute `RANK()`

into our previous query:

SELECT v, RANK() OVER(ORDER BY v) FROM t

… then the result we’re getting is this:

| V | RANK | |---|------| | a | 1 | | a | 1 | | a | 1 | | b | 4 | | c | 5 | | c | 5 | | d | 7 | | e | 8 |

_{(see also this SQLFiddle)}

As you can see, much like in a sports ranking, we have *gaps* between the different ranks. We can avoid those gaps by using

**DENSE_RANK()**

Trivially, `DENSE_RANK()`

is a rank with no gaps, i.e. it is *“dense”*. We can write:

SELECT v, DENSE_RANK() OVER(ORDER BY v) FROM t

… to obtain

| V | DENSE_RANK | |---|------------| | a | 1 | | a | 1 | | a | 1 | | b | 2 | | c | 3 | | c | 3 | | d | 4 | | e | 5 |

_{(see also this SQLFiddle)}

One interesting aspect of `DENSE_RANK()`

is the fact that it “behaves like” `ROW_NUMBER()`

when we add the `DISTINCT`

keyword.

SELECT DISTINCT v, DENSE_RANK() OVER(ORDER BY v) FROM t

… to obtain

| V | DENSE_RANK | |---|------------| | a | 1 | | b | 2 | | e | 5 | | d | 4 | | c | 3 |

_{(see also this SQLFiddle)}

In fact, `ROW_NUMBER()`

prevents you from using `DISTINCT`

, because `ROW_NUMBER()`

generates unique values across the partition *before* `DISTINCT`

is applied:

SELECT DISTINCT v, ROW_NUMBER() OVER(ORDER BY v) FROM t ORDER BY 1, 2

`DISTINCT`

has no effect:

| V | ROW_NUMBER | |---|------------| | a | 1 | | a | 2 | | a | 3 | | b | 4 | | c | 5 | | c | 6 | | d | 7 | | e | 8 |

_{(see also this SQLFiddle)}

## Putting it all together

A good way to understand the three ranking functions is to see them all in action side-by-side. Run this query

SELECT v, ROW_NUMBER() OVER(ORDER BY v), RANK() OVER(ORDER BY v), DENSE_RANK() OVER(ORDER BY v) FROM t ORDER BY 1, 2

… or this one (using the SQL standard `WINDOW`

clause, to reuse window specifications):

SELECT v, ROW_NUMBER() OVER(w), RANK() OVER(w), DENSE_RANK() OVER(w) FROM t WINDOW w AS (ORDER BY v)

… to obtain:

| V | ROW_NUMBER | RANK | DENSE_RANK | |---|------------|------|------------| | a | 1 | 1 | 1 | | a | 2 | 1 | 1 | | a | 3 | 1 | 1 | | b | 4 | 4 | 2 | | c | 5 | 5 | 3 | | c | 6 | 5 | 3 | | d | 7 | 7 | 4 | | e | 8 | 8 | 5 |

_{(see also this SQLFiddle)}

Note that unfortunately, the `WINDOW`

clause is not supported in all databases.

## SQL is awesome

These things can be written very easily using SQL window functions. Once you get a hang of the syntax, you won’t want to miss this killer feature in your every day SQL statements any more. Excited?

For further reading, consider:

- The jOOQ manual sections about window functions
- Dimitri Fontaine’s excellent article “Understanding Window Functions”
- A real-world use-case: Counting neighboring colours in a stadium choreography
- A real-world use-case: Calculating running totals (not only with window functions)
- SQL 101: A Window into the World of Analytic Functions