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> Use this file to discover all available pages before exploring further.

> Sorts time series by timestamp in ascending order.

# timeSeriesGroupArray

<h2 id="timeSeriesGroupArray">
  timeSeriesGroupArray
</h2>

Introduced in: v25.8.0

Sorts time series data by timestamp in ascending order.

The samples can be passed in one of three forms:

* as two arguments `timestamp` and `value`, where each row holds a single sample;
* as two arrays of timestamps and values, where each row holds a whole time series;
* as a single array of `(timestamp, value)` tuples, where each row holds a whole time series. This form has the same type as the result, which allows using the function in the `SimpleAggregateFunction` data type.

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`.
</Note>

**Syntax**

```sql theme={null}
timeSeriesGroupArray(timestamp, value)
timeSeriesGroupArray(samples)
```

**Arguments**

* `timestamp` — Timestamp of the sample. Can be an individual value or an array. [`UInt32`](/reference/data-types/int-uint) or [`DateTime`](/reference/data-types/datetime) or [`DateTime64`](/reference/data-types/datetime64) or [`Array(UInt32)`](/reference/data-types/array) or [`Array(DateTime)`](/reference/data-types/array) or [`Array(DateTime64)`](/reference/data-types/array)
* `value` — Value of the time series corresponding to the timestamp. Can be an individual value or an array. [`Float*`](/reference/data-types/float) or [`Array(Float*)`](/reference/data-types/array)
* `samples` — Samples of the time series passed as an array of tuples `(timestamp, value)`, where the tuple elements have the timestamp and value types listed above. [`Array(Tuple(T1, T2))`](/reference/data-types/array)

**Returned value**

Returns an array of tuples `(timestamp, value)` sorted by timestamp in ascending order. [`Array(Tuple(T1, T2))`](/reference/data-types/array)

**Examples**

**Basic usage with individual values**

```sql title=Query theme={null}
SET allow_experimental_time_series_aggregate_functions = 1;
WITH
    [110, 120, 130, 140, 140, 100]::Array(UInt32) AS timestamps,
    [1, 6, 8, 17, 19, 5]::Array(Float32) AS values
SELECT timeSeriesGroupArray(timestamp, value)
FROM
(
    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}
┌─timeSeriesGroupArray(timestamp, value)─────┐
│ [(100,5),(110,1),(120,6),(130,8),(140,19)] │
└────────────────────────────────────────────┘
```

**Passing multiple samples of timestamps and values as arrays of equal size**

```sql title=Query theme={null}
SET allow_experimental_time_series_aggregate_functions = 1;
WITH
    [110, 120, 130, 140, 140, 100]::Array(UInt32) AS timestamps,
    [1, 6, 8, 17, 19, 5]::Array(Float32) AS values
SELECT timeSeriesGroupArray(timestamps, values);
```

```response title=Response theme={null}
┌─timeSeriesGroupArray(timestamps, values)───┐
│ [(100,5),(110,1),(120,6),(130,8),(140,19)] │
└────────────────────────────────────────────┘
```