📌 HackerRank SQL: Revising the Select Query II (02. Revising-the-Select-Query-II)

• Problem Link: HackerRank - Revising the Select Query II
• Dialect: PostgreSQL
• Difficulty: Easy
• Category: Basic Select
• Schema File: schema.sql
• Query File: query.sql
• Shared Runner: sql_runner.py

📋 Problem Statement

Query the dataset to solve Revising the Select Query II.

Constraints & Data Types

• PostgreSQL 15+ compatible engine.
• Proper handling of NULL values and index utilization.

📊 Schema & Mock Seed Data

CREATE TABLE SampleTable (
    id INT PRIMARY KEY,
    name VARCHAR(255),
    value VARCHAR(255)
);

🏋️ Space to Practice

📝 Query Thought Process Framework

1. Identify Source Tables: Determine target tables and JOIN criteria.
2. Filter Conditions: Apply WHERE filters and handling of NULLs.
3. Aggregations & Grouping: GROUP BY, HAVING, and aggregate functions.
4. Ordering & Projection: SELECT required columns and ORDER BY.

💻 My PostgreSQL Query Draft

SELECT id, name
FROM SampleTable
WHERE value = 'Y';

💡 Multi-Solution Analysis (Deep Step-by-Step Explanations)

Approach 1: Standard Optimal Query ⭐

Intuition & Concept

Filtering rows directly using indexed columns.

PostgreSQL Source Code

SELECT id, name
FROM SampleTable
WHERE value = 'Y';

Performance & Indexing Analysis

• Execution Plan: Index Scan / Sequential Scan depending on table cardinality.
• Optimization Tip: Create composite or B-tree index on filtered columns if dataset size $N>10^5$.

🛠️ PostgreSQL Specific Optimization Tips

1. Use COALESCE(val, default) instead of IFNULL.
2. Test query execution plan using EXPLAIN ANALYZE.