timewrap interval: const duration, count: const int64, label_column: const string, [index_column: const string]?

Shifts the timestamps of rows ahead in time by the specified interval, creating count parallel timeseries.

You must specify a name for the label column, which will contain a string describing the shift, for example, "now", "1d ago", "2d ago", etc.

You may optionally specify index_column, in which case a column containing the index of the shift (0, 1, ..., count - 1, where 0 means "now") is created.

If used with non-temporal verbs (exists, follow, etc.), timewrap will return incomplete data.

Categories

• Metadata
• Metrics

Accelerable

timewrap is always accelerable if the input is accelerable. A dataset that only uses accelerable verbs can be accelerated, making queries on the dataset respond faster.

Examples

timewrap 1d, 4, "label"

Overlays data from today, 1 day ago, 2 days ago, and 3 days ago. Creates a column named label that indicates which time series the data belongs to.

timewrap 1d, 4, "label", "index"

Overlays data from today, 1 day ago, 2 days ago, and 3 days ago. In addition to the label column, also creates a column named index that indicates which time series the data belongs to (0 for "today", 1 for "1 day ago", 3 for "3 days ago", etc.).