lead

Documentación de la función de ventana lead

Devuelve un valor evaluado en la fila situada offset filas después de la fila actual dentro del marco ordenado. Esta función es similar a leadInFrame, pero siempre utiliza el marco ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING.

Sintaxis

lead(x[, offset[, default]])
  OVER ([[PARTITION BY grouping_column] [ORDER BY sorting_column]] | [window_name])
FROM table_name
WINDOW window_name as ([[PARTITION BY grouping_column] [ORDER BY sorting_column])

Para obtener más información sobre la sintaxis de las funciones de ventana, consulte: Funciones de ventana - Sintaxis.

Parámetros

• x — Nombre de la columna.
• offset — Desplazamiento que se aplica. (U)Int*. (Opcional; 1 de forma predeterminada).
• default — Valor que se devolverá si la fila calculada supera los límites del marco de ventana. (Opcional: el valor predeterminado del tipo de columna si se omite).

Valor devuelto

• valor evaluado en la fila situada offset filas después de la fila actual dentro del marco ordenado.

Ejemplo

Este ejemplo analiza datos históricos de los ganadores del Premio Nobel y usa la función lead para devolver una lista de ganadores sucesivos en la categoría de física.

Query

CREATE OR REPLACE VIEW nobel_prize_laureates
AS SELECT *
FROM file('nobel_laureates_data.csv');

Query

SELECT
    fullName,
    lead(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

Query

   ┌─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                        │
   └──────────────────┴──────┴──────────┴────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┘