Field note · July 2, 2024

Fan-out join, in short

A join to a table with more than one row per key multiplies every measure on the other side. Nothing errors, and the number is plausible.

1 min read ·Analytics engineering ·sql

Someone asked why Fan-out join is written the way it is. Fair question.

A join to a table with more than one row per key multiplies every measure on the other side. Nothing errors, and the number is plausible.

What makes it a pattern rather than a tip is that the wrong version is the one you write naturally. It reads correctly, it runs, and it returns something. The failure is in the result, not in the execution — which means the only defence is recognising the shape before you are in it.

Two datasets on this site have the shape built in: retail-orders and world-indicators. Both are small enough to run the broken version, see the number, then run the corrected one and see it change.

It lives under shaping because the fix is in how the rows are arranged, not in the arithmetic. Almost every "the number is wrong" report that turns out to be real lands here.

The long-form treatment is in the course (joins-that-behave, rows-grain-shape); the pattern page is the version to read at 4pm with a query open.

Whether you use our version matters much less than having a version you did not re-derive under time pressure. That is what a pattern library is for.

AE

Analytics engineering

Turning warehouses full of raw tables into models an analyst can trust without asking anyone.

Dimensional modelling, grain, slowly changing dimensions, metric definitions, and the SQL that survives production. Most "we need a data scientist" problems are "we need one correct table" problems.

Related

All field notes    2024 archive