timeSeriesResampleToGridWithStaleness

Introduced in: v25.6.0 Aggregate function that takes time series data as pairs of timestamps and values and re-samples this data to a regular time grid described by start timestamp, end timestamp and step. For each point on the grid the most recent (within the specified time window) sample is chosen. Alias: timeSeriesLastToGrid. 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.

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

Syntax

timeSeriesResampleToGridWithStaleness(start_timestamp, end_timestamp, grid_step, staleness_window)(timestamp, value)

Aliases: timeSeriesLastToGrid 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_window — Specifies the maximum staleness of the most recent sample 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

Arguments

timestamp — Timestamp of the sample. Can be individual values or arrays. UInt32 or DateTime or Array(UInt32) or Array(DateTime)
value — Value of the time series corresponding to the timestamp. Can be individual values or arrays. Float* or Array(Float*)

Returned value Returns time series values re-sampled to the specified grid. The returned array contains one value for each time grid point. The value is NULL if there is no sample for a particular grid point. Array(Nullable(Float64)) Examples Basic usage with individual timestamp-value pairs

Query

SET allow_experimental_time_series_aggregate_functions = 1;
WITH
    -- NOTE: the gap between 140 and 190 is to show how values are filled for ts = 150, 165, 180 according to staleness window parameter
    [110, 120, 130, 140, 190, 200, 210, 220, 230]::Array(DateTime) AS timestamps,
    [1, 1, 3, 4, 5, 5, 8, 12, 13]::Array(Float32) AS values, -- array of values corresponding to timestamps above
    90 AS start_ts,       -- start of timestamp grid
    90 + 120 AS end_ts,   -- end of timestamp grid
    15 AS step_seconds,   -- step of timestamp grid
    30 AS window_seconds  -- "staleness" window
SELECT timeSeriesResampleToGridWithStaleness(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
);

Response

┌─timeSeriesResampleToGridWithStaleness(start_ts, end_ts, step_seconds, window_seconds)(timestamp, value)─┐
│ [NULL,NULL,1,3,4,4,NULL,5,8]                                                                            │
└─────────────────────────────────────────────────────────────────────────────────────────────────────────┘

Using array arguments

Query

SET allow_experimental_time_series_aggregate_functions = 1;
WITH
    [110, 120, 130, 140, 190, 200, 210, 220, 230]::Array(DateTime) AS timestamps,
    [1, 1, 3, 4, 5, 5, 8, 12, 13]::Array(Float32) AS values,
    90 AS start_ts,
    90 + 120 AS end_ts,
    15 AS step_seconds,
    30 AS window_seconds
SELECT timeSeriesResampleToGridWithStaleness(start_ts, end_ts, step_seconds, window_seconds)(timestamps, values);

Response

┌─timeSeriesResampleToGridWithStaleness(start_ts, end_ts, step_seconds, window_seconds)(timestamps, values)─┐
│ [NULL,NULL,1,3,4,4,NULL,5,8]                                                                              │
└───────────────────────────────────────────────────────────────────────────────────────────────────────────┘

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timeSeriesResampleToGridWithStaleness

timeSeriesResampleToGridWithStaleness

​timeSeriesResampleToGridWithStaleness

timeSeriesResampleToGridWithStaleness