ClickHouse/docs/en/sql-reference/window-functions/leadInFrame.md
Denny Crane 0ebee19f2e
Update docs/en/sql-reference/window-functions/leadInFrame.md
Co-authored-by: János Benjamin Antal <antaljanosbenjamin@users.noreply.github.com>
2024-11-26 09:21:58 -04:00

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---
slug: /en/sql-reference/window-functions/leadInFrame
sidebar_label: leadInFrame
sidebar_position: 10
---
# leadInFrame
Returns a value evaluated at the row that is offset rows after the current row within the ordered frame.
:::warning
`leadInFrame` behavior differs from the standard SQL `lead` window function.
Clickhouse window function `leadInFrame` respects the window frame.
To get behavior identical to the `lead`, use `ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING`.
:::
**Syntax**
```sql
leadInFrame(x[, offset[, default]])
OVER ([[PARTITION BY grouping_column] [ORDER BY sorting_column]
[ROWS or RANGE expression_to_bound_rows_withing_the_group]] | [window_name])
FROM table_name
WINDOW window_name as ([[PARTITION BY grouping_column] [ORDER BY sorting_column])
```
For more detail on window function syntax see: [Window Functions - Syntax](./index.md/#syntax).
**Parameters**
- `x` — Column name.
- `offset` — Offset to apply. [(U)Int*](../data-types/int-uint.md). (Optional - `1` by default).
- `default` — Value to return if calculated row exceeds the boundaries of the window frame. (Optional - default value of column type when omitted).
**Returned value**
- value evaluated at the row that is offset rows after the current row within the ordered frame.
**Example**
This example looks at [historical data](https://www.kaggle.com/datasets/sazidthe1/nobel-prize-data) for Nobel Prize winners and uses the `leadInFrame` function to return a list of successive winners in the physics category.
Query:
```sql
CREATE OR REPLACE VIEW nobel_prize_laureates
AS SELECT *
FROM file('nobel_laureates_data.csv');
```
```sql
SELECT
fullName,
leadInFrame(year, 1, year) OVER (PARTITION BY category ORDER BY year ASC
ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING
) AS year,
category,
motivation
FROM nobel_prize_laureates
WHERE category = 'physics'
ORDER BY year DESC
LIMIT 9
```
Result:
```response
┌─fullName─────────┬─year─┬─category─┬─motivation─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┐
1. │ Anne L Huillier │ 2023 │ physics │ for experimental methods that generate attosecond pulses of light for the study of electron dynamics in matter │
2. │ Pierre Agostini │ 2023 │ physics │ for experimental methods that generate attosecond pulses of light for the study of electron dynamics in matter │
3. │ Ferenc Krausz │ 2023 │ physics │ for experimental methods that generate attosecond pulses of light for the study of electron dynamics in matter │
4. │ Alain Aspect │ 2022 │ physics │ for experiments with entangled photons establishing the violation of Bell inequalities and pioneering quantum information science │
5. │ Anton Zeilinger │ 2022 │ physics │ for experiments with entangled photons establishing the violation of Bell inequalities and pioneering quantum information science │
6. │ John Clauser │ 2022 │ physics │ for experiments with entangled photons establishing the violation of Bell inequalities and pioneering quantum information science │
7. │ Giorgio Parisi │ 2021 │ physics │ for the discovery of the interplay of disorder and fluctuations in physical systems from atomic to planetary scales │
8. │ Klaus Hasselmann │ 2021 │ physics │ for the physical modelling of Earths climate quantifying variability and reliably predicting global warming │
9. │ Syukuro Manabe │ 2021 │ physics │ for the physical modelling of Earths climate quantifying variability and reliably predicting global warming │
└──────────────────┴──────┴──────────┴────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┘
```