RSUM (window)
Syntax
RSUM( value [ , direction ] )
RSUM( value [ , direction ]
[ TOTAL | WITHIN ... | AMONG ... ]
[ ORDER BY ... ]
[ BEFORE FILTER BY ... ]
)
More info:
Description
Warning
The sorting order is based on the fields listed in the sorting section of the chart and in the ORDER BY clause. First, ORDER BY fields are used, and then they are complemented by the fields from the chart.
Returns the sum of all values in a growing (or shrinking) window defined by the sort order and the value of direction:
direction |
Window |
|---|---|
"asc" |
Starts from the first row and ends at the current row. |
"desc" |
Starts from the current row and ends at the last row. |
By default "asc" is used.
Window functions with a similar behavior: RCOUNT, RMIN, RMAX, RAVG.
Argument types:
value—Fractional number | Integerdirection—String
Return type: Same type as (value)
Note
Only constant values are accepted for the arguments (direction).
Examples
Example with grouping
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].
Result
| [City] | [Category] | SUM([Orders]) | RSUM(SUM([Orders]) TOTAL) | RSUM(SUM([Orders]) WITHIN [City]) | RSUM(SUM([Orders]) AMONG [City]) |
|---|---|---|---|---|---|
'Detroit' |
'Furniture' |
7 |
7 |
7 |
7 |
'Detroit' |
'Office Supplies' |
25 |
32 |
32 |
48 |
'London' |
'Furniture' |
1 |
33 |
1 |
8 |
'London' |
'Office Supplies' |
10 |
43 |
11 |
62 |
'Moscow' |
'Furniture' |
2 |
45 |
2 |
10 |
'Moscow' |
'Office Supplies' |
4 |
49 |
6 |
52 |
'San Francisco' |
'Furniture' |
5 |
54 |
5 |
15 |
'San Francisco' |
'Office Supplies' |
23 |
77 |
28 |
23 |
Example with ORDER BY
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].
Result
| [City] | SUM([Orders]) | RSUM(SUM([Orders]), "desc") | RSUM(SUM([Orders]), "asc" ORDER BY [City] DESC) | RSUM(SUM([Orders]) ORDER BY [Order Sum]) |
|---|---|---|---|---|
'Detroit' |
32 |
77 |
77 |
77 |
'London' |
11 |
45 |
45 |
17 |
'Moscow' |
6 |
34 |
34 |
6 |
'San Francisco' |
28 |
28 |
28 |
45 |
Data source support
ClickHouse 19.13, Microsoft SQL Server 2017 (14.0), MySQL 5.6, PostgreSQL 9.3.