Abstract / Summary

Check each tweet for invalid characters and ensure its length is within the allowed limit.

Note

The full problem description, including helpful examples, can be found on LeetCode.

This problem is ranked as

and has an acceptance rate of about 85% (1+ million submissions).

Typical patterns to solve this problem:

• Database

Every single line of code was written by me, 100% from scratch, between August 2023 and August 2024.
However, two years later I set up this website and used various AI tools to generate most of the walkthrough / explanations below.

See this dedicated page for more details.

Overview

The provided SQL statement retrieves identifiers of tweets whose textual content exceeds fifteen characters. It operates on a single table, Tweets, and filters rows based on the length of the content column. The result set consists solely of the tweet_id column, which is useful when only the identifiers of qualifying tweets are needed for further processing.

SELECT tweet_id
  FROM Tweets
 WHERE LENGTH(content) > 15

Key Steps

The query execution follows a straightforward pipeline. First, the database engine scans the Tweets table to locate rows. For each row, the LENGTH function evaluates the number of characters in the content field. The predicate > 15 determines whether the row satisfies the length condition. Rows that meet the condition are projected to include only the tweet_id column, which forms the final output.

Edge Cases

When the content column contains a NULL value, the LENGTH function returns NULL. In SQL's three-valued logic, the comparison NULL > 15 yields an unknown result, causing the row to be excluded from the result set. This behavior effectively filters out tweets with missing content without raising an error. Additionally, if the content field holds an empty string, LENGTH('') evaluates to zero, which also fails the length check, ensuring that only tweets with actual textual data are considered.

Performance Optimizations

The query benefits from any existing index that includes the tweet_id column, allowing the engine to retrieve identifiers directly without additional lookups. Moreover, if the database supports functional or expression indexes, an index on LENGTH(content) can accelerate the filtering step by enabling the engine to locate qualifying rows without scanning the entire table. In environments where the Tweets table is partitioned by creation date or another logical key, the engine may prune irrelevant partitions early, reducing the amount of data examined during the length evaluation. The projection of a single column (tweet_id) also minimizes the amount of data transferred from storage to the client, contributing to overall efficiency.

Imagine a giant box filled with cards that have messages written on them. This box is called the Tweets table. The code looks through all the cards in that box one by one. It checks the back of each card to see how long the message is. If the message has more than fifteen letters or spaces, that card is a winner. The final part of the instructions says to write down the special identification number found on the winners so that those numbers can be saved on a new list.

Several LLMs ranked my code quality on a scale from 1 (very poor) to 10 (outstanding):

Time: linear
As a rule of thumb, the maximum input size for one second execution time is

• factorial: up to 10 elements
• exponential: up to 20 elements
• polynomial: a few thousand elements
• loglinear: up to 100,000 elements
• linear: a few million elements
• logarithmic: a billion elements
• constant: practically unlimited

I wrote a basic crawler to find other solutions to that problem.
Obviously, I did that after I solved the problem myself.

In general, AlgoMonster and WalkCCC solutions are high-quality and always worth a look.
I haven't checked most of the other solutions, but they might be helpful as well.

And of course, the LeetCode forum is always a good place (or even the best) to look for alternative approaches.

(click on a column header to sort the table)

	author
author	solutions
www	AlgoMonster		C++	Java	Python	TS
	WalkCCC	SQL
	leetcode.ca	SQL
	Progiez		C++	Java	Python
github	everthis	SQL
	muhammadfarhankt	SQL
	suxrobGM	SQL
AlgoMonster	C++, Python, Java, TypeScript
WalkCCC	SQL
leetcode.ca	SQL
Progiez	C++, Java, Python
everthis	SQL
muhammadfarhankt	SQL
suxrobGM	SQL

There are a few extra pages giving you some insights into my setup:

• Tech Stack - my development environment and tools
• AI - how AI helped me create this website (NOT solving the problems)
• Progress - progression over time
• Quality - code quality