THE CLOUD EXPEDITION! · Chapter 1
The Bridge Over Troubled Data
Marina Webfoot surfaces with a splash, barely containing herself. Local data on your machine, travel records in the cloud — and you can JOIN them in ONE query?! She looks at you wide-eyed. Lets find out where our Pondville ducks have ACTUALLY been going! This is a Hybrid Query — joining local and cloud tables seamlessly.
Your task
Find where Pondville ducks have been traveling. Return their <b>name</b>, <b>destination_pond</b>, and <b>travel_date</b> — most recent trips first, 10 rows. Tables: `pondville_residents` (local), `dbquacks_cloud_expedition.duck_travels` (MotherDuck). The tables share a `duck_id` column.
Hint
JOIN the local and cloud tables using the shared duck_id column
Expected result
10 rows with columns: name, destination_pond, and travel_date showing where Pondville ducks traveled
Tables
lake_visits (500 rows)
| column | type |
|---|---|
visit_id | BIGINT |
duck_id | BIGINT |
destination_pond | VARCHAR |
visit_date | DATE |
purpose | VARCHAR |
pondville_events (50 rows)
| column | type |
|---|---|
event_id | BIGINT |
event_name | VARCHAR |
event_date | DATE |
organizer_id | BIGINT |
location | VARCHAR |
attendee_count | BIGINT |
pondville_residents (100 rows)
| column | type |
|---|---|
duck_id | BIGINT |
name | VARCHAR |
species | VARCHAR |
home_pond | VARCHAR |
age | BIGINT |
occupation | VARCHAR |
joined_date | DATE |
dbquacks_cloud_expedition.duck_travels
A table in a MotherDuck share; its columns are not listed here.
Database: https://dbquacks.com/data/databases/motherduck_tutorial.duckdb
This page as markdown: https://dbquacks.com/motherduck/3.md