## 10.6 Ranking Functions

The ranking functions compute the ordinal rank of a row within the window partition.

These functions can be used with or without partitioning and ordering. However, using them without ordering almost never makes sense.

The ranking functions can be used to create different type of incremental counters.
Consider `SUM(1) OVER (ORDER BY SALARY)`

as an example of what they can do, each of them differently.
Following is an example query, also comparing with the `SUM`

behavior.

`select`

`id,`

`salary,`

`dense_rank() over (order by salary),`

`rank() over (order by salary),`

`row_number() over (order by salary),`

`sum(1) over (order by salary)`

`from employee`

`order by salary;`

Results

`id salary dense_rank rank row_number sum`

`-- ------ ---------- ---- ---------- ---`

`3 8.00 1 1 1 1`

`4 9.00 2 2 2 2`

`1 10.00 3 3 3 4`

`5 10.00 3 3 4 4`

`2 12.00 4 5 5 5`

The difference between `DENSE_RANK`

and `RANK`

is that there is a gap related to duplicate rows (relative to the window ordering) only in `RANK`

.
`DENSE_RANK`

continues assigning sequential numbers after the duplicate salary.
On the other hand, `ROW_NUMBER`

always assigns sequential numbers, even when there are duplicate values.

### 10.6.1 `CUME_DIST()`

Available inDSQL, PSQL

Result type`DOUBLE PRECISION`

Syntax

`CUME_DIST () OVER <window_name_or_spec>`

The distribution function `CUME_DIST`

computes the relative rank of a row within a window partition.
`CUME_DIST`

is calculated as the number of rows preceding or peer of the current row divided by the number of rows in the partition.

In other words, `CUME_DIST() OVER <window_name_or_spec>`

is equivalent to `COUNT(*) OVER <window_name_or_spec> / COUNT(*) OVER()`

#### 10.6.1.1 `CUME_DIST`

Examples

`select`

`id,`

`salary,`

`cume_dist() over (order by salary)`

`from employee`

`order by salary;`

Result

`id salary cume_dist`

`-- ------ ---------`

`3 8.00 0.2`

`4 9.00 0.4`

`1 10.00 0.8`

`5 10.00 0.8`

`2 12.00 1`

### 10.6.2 `DENSE_RANK()`

Available inDSQL, PSQL

Result type`BIGINT`

Syntax

`DENSE_RANK () OVER <window_name_or_spec>`

Returns the rank of rows in a partition of a result set without ranking gaps.
Rows with the same *window_order* values get the same rank within the partition *window_partition*, if specified.
The dense rank of a row is equal to the number of different rank values in the partition preceding the current row, plus one.

#### 10.6.2.1 `DENSE_RANK`

Examples

`select`

`id,`

`salary,`

`dense_rank() over (order by salary)`

`from employee`

`order by salary;`

Result

`id salary dense_rank`

`-- ------ ----------`

`3 8.00 1`

`4 9.00 2`

`1 10.00 3`

`5 10.00 3`

`2 12.00 4`

### 10.6.3 `NTILE()`

Available inDSQL, PSQL

Result type`BIGINT`

Syntax

`NTILE ( `*number_of_tiles* ) OVER <window_name_or_spec>

`NTILE`

Argument | Description |
---|---|

number_of_tiles | Number of tiles (groups). Restricted to a positive integer literal, a named parameter (PSQL), or a positional parameter (DSQL). |

`NTILE`

distributes the rows of the current window partition into the specified number of tiles (groups).

#### 10.6.3.1 `NTILE`

Examples

`select`

`id,`

`salary,`

`rank() over (order by salary),`

`ntile(3) over (order by salary)`

`from employee`

`order by salary;`

Result

`ID SALARY RANK NTILE`

`== ====== ==== =====`

`3 8.00 1 1`

`4 9.00 2 1`

`1 10.00 3 2`

`5 10.00 3 2`

`2 12.00 5 3`

### 10.6.4 `PERCENT_RANK()`

Available inDSQL, PSQL

Result type`DOUBLE PRECISION`

Syntax

`PERCENT_RANK () OVER <window_name_or_spec>`

The distribution function `PERCENT_RANK`

computes the relative rank of a row within a window partition.
`PERCENT_RANK`

is calculated as the Section 10.6.5, `RANK()`

minus 1 of the current row divided by the number of rows in the partition minus 1.

In other words, `PERCENT_RANK() OVER <window_name_or_spec>`

is equivalent to `(RANK() OVER <window_name_or_spec> - 1) / CAST(COUNT(*) OVER() - 1 AS DOUBLE PRECISION)`

#### 10.6.4.1 `PERCENT_RANK`

Examples

`select`

`id,`

`salary,`

`rank() over (order by salary),`

`percent_rank() over (order by salary)`

`from employee`

`order by salary;`

Result

`id salary rank percent_rank`

`-- ------ ---- ------------`

`3 8.00 1 0`

`4 9.00 2 0.25`

`1 10.00 3 0.5`

`5 10.00 3 0.5`

`2 12.00 5 1`

### 10.6.5 `RANK()`

Available inDSQL, PSQL

Result type`BIGINT`

Syntax

`RANK () OVER <window_name_or_spec>`

Returns the rank of each row in a partition of the result set.
Rows with the same values of *window-order* get the same rank with in the partition _window-partition, if specified.
The rank of a row is equal to the number of rank values in the partition preceding the current row, plus one.

#### 10.6.5.1 `RANK`

Examples

`select`

`id,`

`salary,`

`rank() over (order by salary)`

`from employee`

`order by salary;`

Result

`id salary rank`

`-- ------ ----`

`3 8.00 1`

`4 9.00 2`

`1 10.00 3`

`5 10.00 3`

`2 12.00 5`

See alsoSection 10.6.2, `DENSE_RANK()`

, Section 10.6.6, `ROW_NUMBER()`

### 10.6.6 `ROW_NUMBER()`

Available inDSQL, PSQL

Result type`BIGINT`

Syntax

`ROW_NUMBER () OVER <window_name_or_spec>`

Returns the sequential row number in the partition of the result set, where `1`

is the first row in each of the partitions.

#### 10.6.6.1 `ROW_NUMBER`

Examples

`select`

`id,`

`salary,`

`row_number() over (order by salary)`

`from employee`

`order by salary;`

Result

`id salary rank`

`-- ------ ----`

`3 8.00 1`

`4 9.00 2`

`1 10.00 3`

`5 10.00 4`

`2 12.00 5`

See alsoSection 10.6.2, `DENSE_RANK()`

, Section 10.6.5, `RANK()`