timeSeriesResetsToGrid

Aggregate function that takes time series data as pairs of timestamps and values and calculates PromQL-like resets from this data on a regular time grid described by start timestamp, end timestamp and step. For each point on the grid the samples for calculating resets are considered within the specified time window.

If several samples have the same timestamp, only one of them is used: the sample with the greatest value. A NaN value loses to any other value, so a NaN value is used only if all samples at this timestamp are NaN.

:::note This function is experimental, enable it by setting allow_experimental_time_series_aggregate_functions=true. :::

Syntax

timeSeriesResetsToGrid(start_timestamp, end_timestamp, grid_step, staleness)(timestamp, value)

Parameters

• start_timestamp — Specifies start of the grid. With a DateTime64 timestamp argument it can also be a fractional number, or a string containing a number or a date-time text. UInt32 or DateTime or DateTime64 or Float* or Decimal* or String
• end_timestamp — Specifies end of the grid. With a DateTime64 timestamp argument it can also be a fractional number, or a string containing a number or a date-time text. UInt32 or DateTime or DateTime64 or Float* or Decimal* or String
• grid_step — Specifies step of the grid in seconds. With a DateTime64 timestamp argument it can also be a fractional number, or a string containing a number or a duration like '15s' or '1m'. UInt32 or Float* or Decimal* or String
• staleness — Specifies the maximum "staleness" in seconds of the considered samples. With a DateTime64 timestamp argument it can also be a fractional number, or a string containing a number or a duration like '15s' or '1m'. UInt32 or Float* or Decimal* or String

Arguments

• timestamp — Timestamp of the sample. Can be individual values or arrays. - value — Value of the time series corresponding to the timestamp. Can be individual values or arrays.

Returned value

resets values on the specified grid as an Array(Nullable(Float64)). The returned array contains one value for each time grid point. The value is NULL if there are no samples within the window to calculate the resets value for a particular grid point.

Examples

Calculate resets values on the grid [90, 105, 120, 135, 150, 165, 180, 195, 210, 225]

SET allow_experimental_time_series_aggregate_functions = 1;
WITH
    -- NOTE: the gap between 130 and 190 is to show how values are filled for ts = 180 according to window parameter
    [110, 120, 130, 190, 200, 210, 220, 230]::Array(DateTime) AS timestamps,
    [1, 3, 2, 6, 6, 4, 2, 0]::Array(Float32) AS values, -- array of values corresponding to timestamps above
    90 AS start_ts,       -- start of timestamp grid
    90 + 135 AS end_ts,   -- end of timestamp grid
    15 AS step_seconds,   -- step of timestamp grid
    45 AS window_seconds  -- "staleness" window
SELECT timeSeriesResetsToGrid(start_ts, end_ts, step_seconds, window_seconds)(timestamp, value)
FROM
(
    -- This subquery converts arrays of timestamps and values into rows of `timestamp`, `value`
    SELECT
        arrayJoin(arrayZip(timestamps, values)) AS ts_and_val,
        ts_and_val.1 AS timestamp,
        ts_and_val.2 AS value
);

┌─timeSeriesResetsToGrid(start_ts, end_ts, step_seconds, window_seconds)(timestamp, value)─┐
│ [NULL,NULL,0,1,1,1,NULL,0,1,2]                                                           │
└──────────────────────────────────────────────────────────────────────────────────────────┘

Same query with array arguments

SET allow_experimental_time_series_aggregate_functions = 1;
WITH
    [110, 120, 130, 190, 200, 210, 220, 230]::Array(DateTime) AS timestamps,
    [1, 3, 2, 6, 6, 4, 2, 0]::Array(Float32) AS values,
    90 AS start_ts,
    90 + 135 AS end_ts,
    15 AS step_seconds,
    45 AS window_seconds
SELECT timeSeriesResetsToGrid(start_ts, end_ts, step_seconds, window_seconds)(timestamps, values);

┌─timeSeriesResetsToGrid(start_ts, end_ts, step_seconds, window_seconds)(timestamp, value)─┐
│ [NULL,NULL,0,1,1,0,NULL,0,1,2]                                                           │
└──────────────────────────────────────────────────────────────────────────────────────────┘

Introduced in version 25.6.0.