N053-M1 Tier 4 · Advanced · medium ecommerce · Brightlane

Return the ID, name, and warranty length in years for every product whose warranty term exceeds `1` year

Part of JSONB Field Extraction in SQL

The problem

Brightlane's product quality team audits consumer electronics with extended warranty coverage.

Write a query to return the ID, name, and warranty length in years for every product whose warranty term exceeds 1 year.

Assumptions:

  • The products table has one row per product with an id, a name, and an attributes JSONB column.
  • Products with extended warranty have a 'warranty_years' key in their attributes whose value is a JSONB number.
  • The warranty-years output column carries the value extracted from attributes and represented as an integer. Only products whose warranty term is strictly greater than 1 should appear.

Output:

  • One row per qualifying product, with columns id, name, and warranty_years.
Schema · ecommerce 5 tables
categories
id integer
name text
parent_id? integer
products
id integer
name text
category_id integer
price numeric
stock_qty integer
attributes? jsonb
order_items
id integer
order_id integer
product_id integer
quantity integer
unit_price numeric
customers
id integer
name text
email text
city? text
country text
created_at timestamptz
is_active boolean
orders
id integer
customer_id integer
ordered_at timestamptz
status text
total_amount numeric

Run previews · Check grades

Write a query, then run it to see results here.

Worked solution Try it yourself first
Solution query
SELECT
  id,
  name,
  (attributes ->> 'warranty_years')::INTEGER AS warranty_years
FROM
  products
WHERE
  (attributes ->> 'warranty_years')::INTEGER > 1

The shape

Composes JSONB extraction with type casting. ->> returns the warranty value as text, then ::integer converts that text to a number so the > 1 comparison is numeric. The same extract-and-cast appears twice: once in the SELECT (so the output column is an integer) and once in the WHERE (so the filter compares numbers, not strings).

Clause by clause

  • SELECT id, name, (attributes ->> 'warranty_years')::integer AS warranty_years returns the product's ID and name, then extracts the warranty value as text and casts it to an integer for the output column. The parentheses are required because :: would otherwise try to bind to 'warranty_years' instead of the whole extraction expression.
  • FROM products reads the product catalog.
  • WHERE (attributes ->> 'warranty_years')::integer > 1 runs the same extract-and-cast per row and keeps the row only when the integer warranty term is strictly greater than 1. Products with no 'warranty_years' key extract to NULL, the cast of NULL is NULL, and NULL > 1 is unknown, so those rows are dropped automatically.

The trap

Without the cast, the comparison would be lexical, not numeric. ->> returns text, so '10' > '1' is a string comparison that does happen to be true here, but '2' > '10' would be false because '2' sorts after '1'. With longer numbers the order breaks: '9' > '10' is true as text, false as numbers. The ::integer cast is what makes > 1 mean "greater than one as a number" instead of "lexicographically after the character one." Any time a JSONB-extracted value goes into a numeric comparison, the cast is mandatory.

You practiced (attributes ->> 'key')::integer — extract as text, then cast to a numeric type for both the output column and the threshold comparison.

How you actually get good at SQL

Reading explains SQL. Writing it, over and over with instant feedback, is what makes you fluent.

That's the whole SQLMaxx loop: 600+ real problems, instant AI feedback, mastery you can actually see, and spaced review that won't let you forget.

A stack of SQL practice problem cards, the top card showing an employees table.
615 problems · 66 concepts

Real problems. Not toy examples.

615 hand-built problems spanning all 66 concepts, from basic SELECTs to window functions, built on real schemas and real business questions, the kind you'll actually get asked on the job. Enough reps to make SQL automatic.

A retro computer showing a SQL query marked correct with a green checkmark.
Instant AI feedback

Write a query. Know if it's right in one second.

No copying an answer and hoping it clicked. The AI grader checks your real query against real data, catches exactly what's wrong, and explains the fix in plain English, like a senior analyst reading over your shoulder on every problem.

A circular mastery progress dial filling from blue to green, the SQLMaxx diamond at its center.
Mastery tracking

Stop guessing whether you actually know it.

SQLMaxx tracks every concept and shows you what you've mastered and what's still shaky. Your skills fill in one concept at a time, so 'I think I get joins' becomes something you can prove.

A SQL query editor circled by a blue return arrow with a clock, scheduled to come back for review.
Spaced review

Learn it once. Keep it for good.

Most of what you learn this week fades by next week. So when a concept comes due for review, SQLMaxx hands you a fresh problem to solve from a blank editor, not a flashcard to re-read. A research-backed spaced-repetition algorithm (FSRS) times each return for right before you'd forget, so your SQL is still there months later, when the interview or the job actually needs it.

Practice, feedback, mastery, review. That's the loop that turns reading into real skill.

Start free

No account, no credit card. Start solving in under a minute.