THE CLOUD EXPEDITION! · Chapter 5

The Great Convergence

Aria and Captain Cloudsworth lock eyes across the war room. What if... Aria begins. ...we JOIN them? Cloudsworth finishes, dramatically. External CSV archives meeting live cloud tables in a single query — no ETL, no staging, no waiting. This is Files + Cloud Joins — combining remote file reads with cloud table queries in one statement.

Your task

Enrich the historical discovery archive with live cloud data. Use `read_csv()` to load the archive, then combine it with cloud pond data to pull in current climate info. Return <b>pond_name</b>, <b>discoverer_name</b>, <b>discovery_year</b>, <b>climate_zone</b>, and <b>avg_temperature</b> — ordered by discovery year, 10 rows. Sources: `https://data.dbquacks.com/archives/pond_discoveries.csv` (remote CSV, has `pond_name`), `dbquacks_cloud_expedition.global_ponds` (MotherDuck, has `pond_name`, `climate_zone`, `avg_temperature`).<br><br><div class="text-xs text-gray-400 mt-2">Regional tip: MotherDuck runs in US East, US West, and EU Central. For best performance, query data stored in your region. These files are hosted in US East.</div>

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