RANK and LEAD/LAG
Rankings allow you to rank your data in any particular order, while the LAG and LEAD functions allow you to look forward or backward in the window of our query. These tools help you to create compelling reports and more complex analytical functions in the case of LAG/LEAD. Here, you will put these into practice with our data.
Diese Übung ist Teil des Kurses
Introduction to BigQuery
Interaktive Übung
Vervollständige den Beispielcode, um diese Übung erfolgreich abzuschließen.
-- Complete the query to order customers by the total amount spent
-- First, write a CTE to group customers and find their total amount spent
WITH orders AS (
SELECT
-- Add the correct columns and aggregate functions
___,
SUM(___) as all_items
FROM ecommerce.ecomm_orders o, UNNEST(o.order_items) items
JOIN ecommerce.ecomm_order_details od USING (order_id)
GROUP BY od.customer_id
)
SELECT
customer_id,
all_items,
-- Fill in the RANK window function and OVER clause
RANK() ___(ORDER BY ___ DESC)
FROM orders
ORDER BY all_items DESC;