How to Understand SQL Joins with AI

Start with the intended meaning of one output row. A customer summary, an individual order and a customer-order pair are different results. Tell the AI which one you want, show the table columns and identify keys that are actually unique. Use invented examples or approved sample data rather than copying private customer records. An inner join retains matching pairs. A left join also keeps unmatched rows from its left input, filling the missing right-side values with nulls. A full outer join retains unmatched rows from both sides. A self join uses the same table in two roles, usually with different aliases. PostgreSQL documents these behaviors and provides examples you can run in a disposable database. Ask the AI to enumerate the result before showing a query. For customers Ada and Ben, where Ada has two orders and Ben has none, the inner join yields two customer-order pairs. The left join yields three rows. Ada's repeated name is expected because the result is at order level. Many-to-many matches deserve special attention. If three order lines and two promotion records share a product key, joining on that key creates six combinations. Adding DISTINCT afterward may hide the symptom without fixing the intended calculation. You might need to aggregate one side first, choose a more specific key or change the report's grain. Finally, test filters. A condition requiring a right-side value in WHERE can remove the null-extended rows produced by a left join. When the intention is to preserve every left-side row while limiting its matches, that condition may belong in ON. Verify both versions on examples with matches, missing matches and repeated keys.