Practice / joins
The Daily Grind wants total spend per customer, labelled by name rather than id.
You have two DataFrames:
orders
customers
Your task: join orders to customers on customer_id, then return each name and their total_spend (the sum of amount).
Assign your answer DataFrame to result. Row order doesn't matter.
ordersinput DataFrame| column | type |
|---|---|
| order_id | long |
| customer_id | long |
| amount | double |
| order_id | customer_id | amount |
|---|---|---|
| 1 | 100 | 5 |
| 2 | 100 | 7 |
| 3 | 101 | 4 |
customersinput DataFrame| column | type |
|---|---|
| customer_id | long |
| name | string |
| customer_id | name |
|---|---|
| 100 | Priya |
| 101 | Sam |
nametotal_spend· 2 rowsJoin first, then aggregate: orders.join(customers, on="customer_id", how="inner").groupBy("name").agg(F.sum("amount").alias("total_spend")).
This problem builds on Joins (~8 min). Pop it open in a new tab if you want a quick recap.