RAVG (window)

Syntax

RAVG( value [ , direction ] )
RAVG( 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 average 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: RSUM, RCOUNT, RMIN, RMAX.

See also AVG, MAVG.

Argument types:

  • valueFractional number | Integer
  • directionString

Return type: Integer

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]) RAVG(SUM([Orders]) TOTAL) RAVG(SUM([Orders]) WITHIN [City]) RAVG(SUM([Orders]) AMONG [City])
'Detroit' 'Furniture' 7 7.00 7.00 7.00
'Detroit' 'Office Supplies' 25 16.00 16.00 24.00
'London' 'Furniture' 1 11.00 1.00 4.00
'London' 'Office Supplies' 10 10.75 5.50 15.50
'Moscow' 'Furniture' 2 9.00 2.00 3.33
'Moscow' 'Office Supplies' 4 8.17 3.00 17.33
'San Francisco' 'Furniture' 5 7.71 5.00 3.75
'San Francisco' 'Office Supplies' 23 9.62 14.00 23.00
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]) RAVG(SUM([Orders]), "desc") RAVG(SUM([Orders]), "asc" ORDER BY [City] DESC) RAVG(SUM([Orders]) ORDER BY [Order Sum])
'Detroit' 32 19.25 19.25 19.25
'London' 11 15.00 15.00 8.50
'Moscow' 6 17.00 17.00 6.00
'San Francisco' 28 28.00 28.00 15.00

Data source support

ClickHouse 19.13, Microsoft SQL Server 2017 (14.0), MySQL 5.6, PostgreSQL 9.3.

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