lesson
Tables, Rows, Columns, Keys, and Grain
State row grain, distinguish identifiers from labels, and preview relationships. This public lesson explains the mental model, syntax pattern, result grain, mistakes, and next practice step for M01.
Practice this lesson
Answer first mental model
State row grain, distinguish identifiers from labels, and preview relationships.
Mental model: name the intended output grain for Tables, Rows, Columns, Keys, and Grain before writing SQL so later checks can distinguish a correct query from a coincidentally matching result.
Learning objectives and prerequisites
Learning objectives are stated as observable behaviors, and prerequisite links are public pages rather than hidden app state.
Plan about 20 minutes for the public read, worked example, prediction, and first app attempt; delayed review can add more practice later.
- Objective: State row grain, distinguish identifiers from labels, and preview relationships.
- Skill focus: schema-reading
- Prerequisite: review Workspace Orientation and First Run before this lesson.
Original worked query and result grain
The worked query is a compact SQL Trail example that can be read without loading the interactive engine.
Input grain: one source row from a small product table.
Output grain: one selected row with named columns.
SELECT product_id, product_name FROM products ORDER BY product_id;| Example output | Meaning |
|---|---|
| 1 | Trail Mix | one selected product row |
| 2 | Camp Mug | next product in deterministic order |
Syntax pattern
Use the syntax pattern as a shape, not as a memorized answer. Replace table, column, condition, grouping, and ordering names according to the stated grain.
SELECT column_name FROM table_name;| Input grain | Output grain | Validation focus |
|---|---|---|
| one source row from a small product table | one selected row with named columns | Result comparison, ordering, duplicates, nulls, and edge cases |
Common mistakes and why they fail
A common mistake is matching the visible rows while ignoring ordering, duplicate policy, null behavior, tie behavior, or the stated result grain.
Why it fails: Tables, Rows, Columns, Keys, and Grain checks meaning across deterministic variants, so a query that only copies the visible rows can break when row counts, labels, nulls, or ties change.
PostgreSQL dialect notes stay explicit when syntax, date handling, transaction behavior, or comparison semantics matter.
Lightweight public prediction
Before opening the app, predict the output grain, the first column, and one edge case that could change the answer.
This is a public reading prompt only; it does not load PGlite, learner history, drafts, or browser-only state.
- Prediction: name one row that should appear or one row that should be excluded.
- Check: explain whether nulls, duplicates, ties, or missing relationships affect the result.
- Transfer: say what would change on a second dataset with different labels and counts.
Practice and related resources
Move to the app when you want the editor, local SQL worker, variant checks, hints, and Solution Studio comparison.