LeetCode #1484 — EASY

Group Sold Products By The Date

Build confidence with an intuition-first walkthrough focused on core interview patterns fundamentals.

The Problem

Problem Statement

Table Activities:

+-------------+---------+
| Column Name | Type    |
+-------------+---------+
| sell_date   | date    |
| product     | varchar |
+-------------+---------+
There is no primary key (column with unique values) for this table. It may contain duplicates.
Each row of this table contains the product name and the date it was sold in a market.

Write a solution to find for each date the number of different products sold and their names.

The sold products names for each date should be sorted lexicographically.

Return the result table ordered by sell_date.

The result format is in the following example.

Example 1:

Input: 
Activities table:
+------------+------------+
| sell_date  | product     |
+------------+------------+
| 2020-05-30 | Headphone  |
| 2020-06-01 | Pencil     |
| 2020-06-02 | Mask       |
| 2020-05-30 | Basketball |
| 2020-06-01 | Bible      |
| 2020-06-02 | Mask       |
| 2020-05-30 | T-Shirt    |
+------------+------------+
Output: 
+------------+----------+------------------------------+
| sell_date  | num_sold | products                     |
+------------+----------+------------------------------+
| 2020-05-30 | 3        | Basketball,Headphone,T-shirt |
| 2020-06-01 | 2        | Bible,Pencil                 |
| 2020-06-02 | 1        | Mask                         |
+------------+----------+------------------------------+
Explanation: 
For 2020-05-30, Sold items were (Headphone, Basketball, T-shirt), we sort them lexicographically and separate them by a comma.
For 2020-06-01, Sold items were (Pencil, Bible), we sort them lexicographically and separate them by a comma.
For 2020-06-02, the Sold item is (Mask), we just return it.

Step 01

Brute Force Baseline

Problem summary: Table Activities: +-------------+---------+ | Column Name | Type | +-------------+---------+ | sell_date | date | | product | varchar | +-------------+---------+ There is no primary key (column with unique values) for this table. It may contain duplicates. Each row of this table contains the product name and the date it was sold in a market. Write a solution to find for each date the number of different products sold and their names. The sold products names for each date should be sorted lexicographically. Return the result table ordered by sell_date. The result format is in the following example.

Baseline thinking

Start with the most direct exhaustive search. That gives a correctness anchor before optimizing.

Pattern signal: General problem-solving

Example 1

{"headers":{"Activities":["sell_date","product"]},"rows":{"Activities":[["2020-05-30","Headphone"],["2020-06-01","Pencil"],["2020-06-02","Mask"],["2020-05-30","Basketball"],["2020-06-01","Bible"],["2020-06-02","Mask"],["2020-05-30","T-Shirt"]]}}

Core Insight

What unlocks the optimal approach

No official hints in dataset. Start from constraints and look for a monotonic or reusable state.

Interview move: turn each hint into an invariant you can check after every iteration/recursion step.

Step 03

Algorithm Walkthrough

Iteration Checklist

Define state (indices, window, stack, map, DP cell, or recursion frame).
Apply one transition step and update the invariant.
Record answer candidate when condition is met.
Continue until all input is consumed.

Use the first example testcase as your mental trace to verify each transition.

Step 04

Edge Cases

Minimum Input

Single element / shortest valid input

Validate boundary behavior before entering the main loop or recursion.

Duplicates & Repeats

Repeated values / repeated states

Decide whether duplicates should be merged, skipped, or counted explicitly.

Extreme Constraints

Upper-end input sizes

Re-check complexity target against constraints to avoid time-limit issues.

Invalid / Corner Shape

Empty collections, zeros, or disconnected structures

Handle special-case structure before the core algorithm path.

Step 05

Full Annotated Code

Source-backed implementations are provided below for direct study and interview prep.

// Accepted solution for LeetCode #1484: Group Sold Products By The Date
// Auto-generated Java example from rust.
class Solution {
    public void exampleSolution() {
    }
}
// Reference (rust):
// // Accepted solution for LeetCode #1484: Group Sold Products By The Date
// pub fn sql_example() -> &'static str {
//     r#"
// -- Accepted solution for LeetCode #1484: Group Sold Products By The Date
// SELECT
//     sell_date,
//     COUNT(DISTINCT product) AS num_sold,
//     GROUP_CONCAT(DISTINCT product) AS products
// FROM Activities
// GROUP BY sell_date
// ORDER BY sell_date;
// "#
// }

// Accepted solution for LeetCode #1484: Group Sold Products By The Date
// Auto-generated Go example from rust.
func exampleSolution() {
}
// Reference (rust):
// // Accepted solution for LeetCode #1484: Group Sold Products By The Date
// pub fn sql_example() -> &'static str {
//     r#"
// -- Accepted solution for LeetCode #1484: Group Sold Products By The Date
// SELECT
//     sell_date,
//     COUNT(DISTINCT product) AS num_sold,
//     GROUP_CONCAT(DISTINCT product) AS products
// FROM Activities
// GROUP BY sell_date
// ORDER BY sell_date;
// "#
// }

# Accepted solution for LeetCode #1484: Group Sold Products By The Date
# Auto-generated Python example from rust.
def example_solution() -> None:
    return
# Reference (rust):
# // Accepted solution for LeetCode #1484: Group Sold Products By The Date
# pub fn sql_example() -> &'static str {
#     r#"
# -- Accepted solution for LeetCode #1484: Group Sold Products By The Date
# SELECT
#     sell_date,
#     COUNT(DISTINCT product) AS num_sold,
#     GROUP_CONCAT(DISTINCT product) AS products
# FROM Activities
# GROUP BY sell_date
# ORDER BY sell_date;
# "#
# }

// Accepted solution for LeetCode #1484: Group Sold Products By The Date
pub fn sql_example() -> &'static str {
    r#"
-- Accepted solution for LeetCode #1484: Group Sold Products By The Date
SELECT
    sell_date,
    COUNT(DISTINCT product) AS num_sold,
    GROUP_CONCAT(DISTINCT product) AS products
FROM Activities
GROUP BY sell_date
ORDER BY sell_date;
"#
}

// Accepted solution for LeetCode #1484: Group Sold Products By The Date
// Auto-generated TypeScript example from rust.
function exampleSolution(): void {
}
// Reference (rust):
// // Accepted solution for LeetCode #1484: Group Sold Products By The Date
// pub fn sql_example() -> &'static str {
//     r#"
// -- Accepted solution for LeetCode #1484: Group Sold Products By The Date
// SELECT
//     sell_date,
//     COUNT(DISTINCT product) AS num_sold,
//     GROUP_CONCAT(DISTINCT product) AS products
// FROM Activities
// GROUP BY sell_date
// ORDER BY sell_date;
// "#
// }

Step 06

Interactive Study Demo

Use this to step through a reusable interview workflow for this problem.

Custom checkpoints (one per line)

Press Step or Run All to begin.

Step 07

Complexity Analysis

Time

O(n)

Space

O(1)

Approach Breakdown

BRUTE FORCE

O(n²) time

O(1) space

Two nested loops check every pair or subarray. The outer loop fixes a starting point, the inner loop extends or searches. For n elements this gives up to n²/2 operations. No extra space, but the quadratic time is prohibitive for large inputs.

OPTIMIZED

O(n) time

O(1) space

Most array problems have an O(n²) brute force (nested loops) and an O(n) optimal (single pass with clever state tracking). The key is identifying what information to maintain as you scan: a running max, a prefix sum, a hash map of seen values, or two pointers.

Shortcut: If you are using nested loops on an array, there is almost always an O(n) solution. Look for the right auxiliary state.

Coach Notes

Common Mistakes

Review these before coding to avoid predictable interview regressions.

Off-by-one on range boundaries

Wrong move: Loop endpoints miss first/last candidate.

Usually fails on: Fails on minimal arrays and exact-boundary answers.

Fix: Re-derive loops from inclusive/exclusive ranges before coding.