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> Aggregate function that calculates PromQL-like resets over time series data on the specified grid.

# timeSeriesResetsToGrid

<h2 id="timeSeriesResetsToGrid">
  timeSeriesResetsToGrid
</h2>

Introduced in: v25.6.0

Aggregate function that takes time series data as pairs of timestamps and values and calculates [PromQL-like resets](https://prometheus.io/docs/prometheus/latest/querying/functions/#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.

<Note>
  This function is experimental, enable it by setting `allow_experimental_ts_to_grid_aggregate_function=true`.
</Note>

**Syntax**

```sql theme={null}
timeSeriesResetsToGrid(start_timestamp, end_timestamp, grid_step, staleness)(timestamp, value)
```

**Parameters**

* `start_timestamp` — Specifies start of the grid. - `end_timestamp` — Specifies end of the grid. - `grid_step` — Specifies step of the grid in seconds. - `staleness` — Specifies the maximum "staleness" in seconds of the considered samples.

**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]**

```sql title=Query theme={null}
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
);
```

```response title=Response theme={null}
┌─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**

```sql title=Query theme={null}
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);
```

```response title=Response theme={null}
┌─timeSeriesResetsToGrid(start_ts, end_ts, step_seconds, window_seconds)(timestamp, value)─┐
│ [NULL,NULL,0,1,1,0,NULL,0,1,2]                                                           │
└──────────────────────────────────────────────────────────────────────────────────────────┘
```