RollingSum / Computation Layer

Calculate the rolling (cumulative) sum over a sliding window. Similar to pandas.rolling().sum() or R's roll_sum().

Mathematical form: $y_{i} = j = i - w + 1 \sum i (x_{j} \cdot w_{j})$ where $w$ is the window size and $w_{j}$ are optional weights.

Common applications:

Running totals (revenue, costs)
Cumulative counts (events, transactions)
Resource usage tracking
Rainfall accumulation
Traffic volume analysis
Energy consumption monitoring
Inventory movement

Note: Useful for monitoring accumulations over fixed time windows.

Table

Select

column

The numeric column to compute rolling sums for. Typical applications:

Sales volumes (daily totals)
Transaction counts (hourly sums)
Resource consumption (running totals)
Event frequencies (occurrence counts)
Cumulative measurements

WindowSize

u32

Number of observations in sliding window. Common periods:

24: Daily totals from hourly data
7: Weekly accumulation
30: Monthly totals
365: Annual running sum

Choose based on reporting and analysis needs.

Weights

[f64, ...]

Optional weights for window values. Must match window size if provided. Uses:

Weighted accumulation
Time-weighted totals
Priority-based summation

Modifies contribution of each value to total.

MinPeriods

oneof

AsWindow

Require complete windows for sum calculation. Ensures totals are based on full windows of data. Important for accurate accumulation tracking and complete period totals.

Period

Value

u32

Minimum number of valid observations (Value) required for sum calculation. Examples:

1: Sum any available values
window_size/2: Require majority of window
window_size: Require complete window

Controls trade-off between data availability and total accuracy.

Center

bool

false

Window label position. When true, aligns to window center; when false, to end. Effects:

true: Better for historical accumulation analysis
false: Better for real-time total monitoring

Name for the new column. If not provided, the system generates a unique name. If AsColumn matches an existing column, the existing column is replaced. The name should follow valid column naming conventions.