---
description: 'Aggregate function that calculates PromQL-like idelta over time series data on the specified grid.'
sidebar_position: 222
slug: /sql-reference/aggregate-functions/reference/timeSeriesInstantDeltaToGrid
title: 'timeSeriesInstantDeltaToGrid'
---

Aggregate function that takes time series data as pairs of timestamps and values and calculates [PromQL-like idelta](https://prometheus.io/docs/prometheus/latest/querying/functions/#idelta) 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 `idelta` are considered within the specified time window.

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` - specified the maximum "staleness" in seconds of the considered samples

Arguments:
- `timestamp` - timestamp of the sample
- `value` - value of the time series corresponding to the `timestamp`

Return value:
`idelta` 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 not enough samples within the window to calculate the instant delta value for a particular grid point.

Example:
The following query calculates `idelta` values on the grid [90, 105, 120, 135, 150, 165, 180, 195, 210]:

```sql
WITH
    -- NOTE: the gap between 140 and 190 is to show how values are filled for ts = 150, 165, 180 according to window paramater
    [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
    45 AS window_seconds  -- "staleness" window
SELECT timeSeriesInstantDeltaToGrid(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:

```response
   ┌─timeSeriesInsta⋯stamps, values)─┐
1. │ [NULL,NULL,0,2,1,1,NULL,NULL,3] │
   └─────────────────────────────────┘
```

Also it is possible to pass multiple samples of timestamps and values as Arrays of equal size. The same query with array arguments:

```sql
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,
    45 AS window_seconds
SELECT timeSeriesInstantDeltaToGrid(start_ts, end_ts, step_seconds, window_seconds)(timestamps, values);
```

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