timewindow

A time window is an interval of time used to define the portion of data that will be selected or analyzed in a given operation. It is typically specified by a duration and an anchor moment, or by explicit start and end times. Windows can be fixed and non-overlapping, known as tumbling windows, or sliding, where the window moves forward in steps and may overlap with previous windows. They can also be anchored to calendar boundaries (such as days or hours) or to specific events.

In data processing and streaming analytics, time windows segment continuous data streams into manageable chunks so that metrics can be computed for each window, such as counts, sums, averages, or more complex statistics. In databases and query systems, time windows filter rows to a defined temporal range. In signal processing, applying a time-domain window to a finite set of samples helps control spectral leakage in subsequent Fourier analysis; common window shapes include rectangular, Hann, and Hamming windows, each with different leakage and resolution characteristics.

Key considerations for time windows include size, alignment, and overlap. Window size affects latency and the amount of data included; alignment determines how the window sits relative to fixed time marks; overlap can smooth results but increases redundancy. Edge effects at the start and end of streams may require padding or special handling for incomplete windows.

See also: rolling window, windowing in signal processing, time-based aggregation.