Time series aggregations

Quiver supports several time series aggregations that can operate on either one or several series at a time.

Single series aggregate

Single series aggregates operate on a single, continuous, time series producing one aggregated value for each specified time window.

Supported aggregation options

The following options are supported:

• Sum: Sum of all points in each window.
• Mean: Average of all points in each window.
• Standard deviation: Standard deviation of all points in each window.
• Max: Largest value in each window.
• Min: Smallest value in each window.
• Difference: Difference between the last point and first point in each window.
• Relative difference: Percent change between the last point and first point in each window.
• Product: Product of all points in each window.
• Count: Number of points in each window.
• First: Value of the first point in each window.
• Last: Value of the last point in each window.

Quiver cards using this aggregate

• Cumulative aggregate: This card applies a data point aggregation for each point in the input series, where the time window ranges from the start of the series to the current point (inclusive).
• Periodic aggregate: This card divides the time series into contiguous time windows of fixed duration and applies a data point aggregation to each. Windows with no data points are not included in the output.
• Rolling aggregate: This card applies a data point aggregation for each point in the input series where the time window ends at the current timestamp (inclusive) and spans a specified duration. As new data points are added to the window, old points fall out of it if they are outside the specified duration.
• Time series numeric aggregation: This card applies a data point aggregation to a single time window spanning the entire series.
• Time series scatter plot: This card uses a periodic aggregate.
• Bollinger bands: This card uses a rolling aggregate.

Multi-series aggregate

Multi-series aggregates align multiple continuous time series and combine one value from each series producing an aggregated value for each timestamp.

Supported aggregation options

The following options are supported:

• Sum: Sum of points across all series at each timestamp.
• Mean: Average of points across all series at each timestamp.
• Standard deviation: Standard deviation of points across all series at each timestamp.
• Max: Largest value in any series at each timestamp.
• Min: Smallest value in any series at each timestamp.
• Product: Product of points across all series at each timestamp.

Quiver cards using this aggregate

• Linear aggregation
• Time series formula: This card allows you to perform most of the operations in the above list, but with mathematical operators.

Interval aggregate

Interval aggregates operate on an interval time series which can be produced via the Filter time series card. They produce one aggregated value for each interval in the series. Aggregates are inclusive of points at the start timestamp of each interval and exclusive of points at the end timestamp.

Supported aggregation options

The following options are supported:

• Sum: Sum of all points in each interval.
• Mean: Average of all points in each interval.
• Standard deviation: Standard deviation of all points in each interval.
• Max: Largest value in each interval.
• Min: Smallest value in each interval.
• Difference: Difference between the last point and first point in each interval.
• Relative difference: Percent change between the last point and first point in each interval.
• Product: Product of all points in each interval.
• Count: Number of points in each interval.
• First: Value of the first point in each interval.
• Last: Value of the last point in each interval.
• Duration: Length of each interval in the precision that the time series is configured with (usually milliseconds).
• Rate change: Difference between the last point and first point in each interval divided by the interval's length in the precision that the time series is configured with (usually milliseconds).

Quiver cards using this aggregate

• Segment transformation