Invalid Tweets | Leetcode 1683 | SQL 50 Study Plan

This chapter covers LeetCode 1683 ("Invalid Tweets"), focusing on string character manipulation, length-filtering functions in SQL, and handling text-based constraints in relational databases.

1. Why Do We Need String Length Filtering?

In modern social media applications and content platforms, text moderation and data validation are crucial engineering requirements. Databases often need to enforce business rules on user-generated text, such as maximum post lengths, minimum requirements, or anomaly detection.

• The Problem: Given a table of social media tweets, identify all "invalid" tweets where the text content violates platform length policies.
• The Business Rule: Any tweet whose content exceeds a specific character limit is categorized as invalid and must be flagged or retrieved for auditing.

2. Core Schema and Database Design

The problem introduces a single relational table named Tweets. Understanding its structure and column types is the first step toward writing an optimal query.

Table Definition: Tweets

Note: A Primary Key is a column (or set of columns) whose values uniquely identify every row in a table. No two rows can have the same primary key value, and it cannot contain NULL.

3. Defining an "Invalid Tweet"

Before writing any SQL code, we must translate the business requirement into a precise logical condition:

• A tweet is considered invalid if and only if the number of characters used in its content is strictly greater than 15 ($> 15$).
• Crucial Edge Case Note: White spaces (spaces, tabs, newlines) are counted as characters toward the total length of the string.

4. Naive Approach vs. Production-Ready Query

When dealing with string operations, beginners might attempt complex string parsing or procedural loops. However, SQL provides native built-in functions designed to evaluate string lengths efficiently at the database engine level.

Naive Conceptual Attempt (Incorrect / Inefficient)

Iterating through strings character by character in application code or attempting custom substring slicing:

-- Conceptual pseudocode (Not recommended)
SELECT * FROM Tweets WHERE custom_manual_counter(content) > 15;

Production-Ready Approach

We use SQL’s dedicated length-evaluation functions combined with a simple WHERE clause filter.

SELECT tweet_id
FROM Tweets
WHERE CHAR_LENGTH(content) > 15;

5. Step-by-Step Flow Walkthrough

Let's trace how the database evaluates our query against a sample dataset.

Sample Input Data (Tweets Table)

Execution Pipeline

6. Deep Dive: CHAR_LENGTH() vs. LENGTH() in SQL

A common point of confusion in SQL string manipulation is choosing between CHAR_LENGTH() and LENGTH(). While they sound identical, they behave differently depending on character encodings (such as UTF-8).

7. Complete SQL Query Implementation

Here is the clean, final query submitted and accepted on LeetCode:

-- Return the tweet_id of all invalid tweets where content length > 15 characters
SELECT tweet_id 
FROM Tweets 
WHERE CHAR_LENGTH(content) > 15;

8. Summary and Key Takeaways

• Understand the Constraint: Always read problem statements carefully regarding boundaries—here, "strictly greater than 15" means $length > 15$ (excluding 15).
• White Spaces Count: Remember that spaces, punctuation marks, and special characters all contribute to the final character count of a string.
• Primary Keys: Use the specified primary key column (tweet_id) in the SELECT clause when asked to return record identifiers.
• Choose the Right Function: Prefer CHAR_LENGTH() over LENGTH() when validating character limits to ensure multi-byte safety.
• Filter with WHERE: Apply scalar string functions inside the WHERE clause to filter rows at the database query level efficiently.
• Test with Edge Cases: Always verify your queries against edge cases such as exact boundaries (e.g., exactly 15 characters vs. 16 characters).