RANK_UNIQUE (window)
Syntax
RANK_UNIQUE( value [ , direction ] )
RANK_UNIQUE( value [ , direction ]
[ TOTAL | WITHIN ... | AMONG ... ]
[ BEFORE FILTER BY ... ]
)
More info:
Description
Returns the rank of the current row if ordered by the given argument. Rows corresponding to the same value have different rank values. This means that rank values are sequential and different for all rows, always increasing by 1 for the next row.
If direction is "desc" or omitted, then ranking is done from greatest to least, if "asc", then from least to greatest.
See also RANK, RANK_DENSE, RANK_PERCENTILE.
Argument types:
value—Boolean | Date | Datetime | Fractional number | Integer | String | UUIDdirection—String
Return type: Integer
Note
Only constant values are accepted for the arguments (direction).
Examples
Source data
| Date | City | Category | Orders | Profit |
|---|---|---|---|---|
'2019-03-01' |
'London' |
'Office Supplies' |
8 |
120.80 |
'2019-03-04' |
'London' |
'Office Supplies' |
2 |
100.00 |
'2019-03-05' |
'London' |
'Furniture' |
1 |
750.00 |
'2019-03-02' |
'Moscow' |
'Furniture' |
2 |
1250.50 |
'2019-03-03' |
'Moscow' |
'Office Supplies' |
4 |
85.00 |
'2019-03-01' |
'San Francisco' |
'Office Supplies' |
23 |
723.00 |
'2019-03-01' |
'San Francisco' |
'Furniture' |
1 |
1000.00 |
'2019-03-03' |
'San Francisco' |
'Furniture' |
4 |
4000.00 |
'2019-03-02' |
'Detroit' |
'Furniture' |
5 |
3700.00 |
'2019-03-04' |
'Detroit' |
'Office Supplies' |
25 |
1200.00 |
'2019-03-04' |
'Detroit' |
'Furniture' |
2 |
3500.00 |
Grouped by [City].
Sorted by [City].
Formulas:
- City:
[City]; - Order Sum:
SUM([Orders]); - RANK_UNIQUE desc:
RANK_UNIQUE(SUM([Orders]), "desc"); - RANK_UNIQUE asc:
RANK_UNIQUE(SUM([Orders]), "asc").
Result
| City | Order Sum | RANK_UNIQUE desc | RANK_UNIQUE asc |
|---|---|---|---|
'Detroit' |
32 |
1 |
4 |
'London' |
11 |
3 |
2 |
'Moscow' |
6 |
4 |
1 |
'San Francisco' |
28 |
2 |
3 |
Source data
| Date | City | Category | Orders | Profit |
|---|---|---|---|---|
'2019-03-01' |
'London' |
'Office Supplies' |
8 |
120.80 |
'2019-03-04' |
'London' |
'Office Supplies' |
2 |
100.00 |
'2019-03-05' |
'London' |
'Furniture' |
1 |
750.00 |
'2019-03-02' |
'Moscow' |
'Furniture' |
2 |
1250.50 |
'2019-03-03' |
'Moscow' |
'Office Supplies' |
4 |
85.00 |
'2019-03-01' |
'San Francisco' |
'Office Supplies' |
23 |
723.00 |
'2019-03-01' |
'San Francisco' |
'Furniture' |
1 |
1000.00 |
'2019-03-03' |
'San Francisco' |
'Furniture' |
4 |
4000.00 |
'2019-03-02' |
'Detroit' |
'Furniture' |
5 |
3700.00 |
'2019-03-04' |
'Detroit' |
'Office Supplies' |
25 |
1200.00 |
'2019-03-04' |
'Detroit' |
'Furniture' |
2 |
3500.00 |
Grouped by [City], [Category].
Sorted by [City], [Category].
Formulas:
- City:
[City]; - Category:
[Category]; - Order Sum:
SUM([Orders]); - RANK_UNIQUE TOTAL:
RANK_UNIQUE(SUM([Orders]) TOTAL); - RANK_UNIQUE WITHIN:
RANK_UNIQUE(SUM([Orders]) WITHIN [City]); - RANK_UNIQUE AMONG:
RANK_UNIQUE(SUM([Orders]) AMONG [City]).
Result
| City | Category | Order Sum | RANK_UNIQUE TOTAL | RANK_UNIQUE WITHIN | RANK_UNIQUE AMONG |
|---|---|---|---|---|---|
'Detroit' |
'Furniture' |
7 |
4 |
2 |
1 |
'Detroit' |
'Office Supplies' |
25 |
1 |
1 |
1 |
'London' |
'Furniture' |
1 |
8 |
2 |
4 |
'London' |
'Office Supplies' |
10 |
3 |
1 |
3 |
'Moscow' |
'Furniture' |
2 |
7 |
2 |
3 |
'Moscow' |
'Office Supplies' |
4 |
6 |
1 |
4 |
'San Francisco' |
'Furniture' |
5 |
5 |
2 |
2 |
'San Francisco' |
'Office Supplies' |
23 |
2 |
1 |
2 |
Data source support
ClickHouse 21.8, Microsoft SQL Server 2017 (14.0), MySQL 5.7, Oracle Database 12c (12.1), PostgreSQL 9.3.