Introduzione a BigQuery
Matthew Forrest
Field CTO


SELECT customer_id, order_date, order_total, ROW_NUMBER() OVER(PARTITION BY customer_idORDER BY order_date) AS order_sequence FROM orders;
ROW_NUMBER(): La funzione window che restituisce il numero di rigaOVER(): Definisce il frame della finestraPARTITION BY customer_id: Raggruppa i dati per clienteORDER BY order_date: Ordina i dati dentro ogni partizioneorder_sequence: Risultato dell'operazione della funzione windowSELECT
product_id,
product_photos_qty,
-- Ordinal rank for each row
RANK() OVER(
ORDER BY product_photos_qty DESC
) as rank,
-- Percentile rank for each row
PERCENT_RANK() OVER(
ORDER BY product_photos_qty
) as percent
FROM ecommerce.ecomm_products
ORDER BY product_photos_qty DESC;

SELECT
product_id,
-- Returns value from previous row
LAG(product_photos_qty) OVER(
ORDER BY product_photos_qty
) as lag,
product_photos_qty,
-- Returns value from next row
LEAD(product_photos_qty) OVER(
ORDER BY product_photos_qty
) as lead
FROM ecommerce.ecomm_products
ORDER BY product_photos_qty DESC;

SELECT
order_id,
order_timestamp,
SUM(cost) OVER(
ORDER BY order_timestamp
ROWS BETWEEN 2 PRECEDING
AND CURRENT ROW) as rolling_avg
FROM sales_data
ORDER BY order_timestamp
Opzioni di delimitazione basate su righe:
UNBOUNDED PRECEDING: Tutte le righe precedentiUNBOUNDED FOLLOWING: Tutte le righe successive[INT] ROWS PRECEDING: Numero specifico di righe precedenti[INT] ROWS FOLLOWING: Numero specifico di righe successiveSELECT
product_id,
product_photos_qty,
RANK() OVER(
ORDER BY product_photos_qty DESC
) as rank
FROM ecommerce.ecomm_products
-- Filter using QUALIFY
QUALIFY rank < 4
ORDER BY product_photos_qty DESC;

HAVING perché non stai aggregandoIntroduzione a BigQuery