Find all missing IDs between 1 and 10 in the `orders` table.
Problem Statement
<p>Find all missing IDs between 1 and 10 in the <code>orders</code> table.</p>
Examples
Input: orders table: +----+ | id | +----+ | 1 | | 2 | | 4 | | 7 | | 9 | | 10 | +----+
Output: +------------+ | missing_id | +------------+ | 5 | | 8 | | 6 | | 3 | +------------+
Explanation: The query retrieves the requested records satisfying all problem requirements.
Complexity
Time Complexity: -
Space Complexity: -
Hints
š” Hint 1:
Determine which tables contain the required columns and relate them using LEFT JOIN on the corresponding foreign/primary keys.
š” Hint 2:
Write out the ON condition matching key fields (e.g. ON a.key = b.key) and apply any filtering in the WHERE clause.
š” Hint 3:
Select only the requested columns in the SELECT clause with clear aliases if needed: SELECT ... FROM ... LEFT JOIN ... ON ...;
Editorial & Approach
Problem Overview & Intuition
To solve "Find Missing IDs (Gap Analysis)", we query the relational database engine using declarative SQL. The goal is to find all missing ids between 1 and 10 in the `orders` table. By formulating an optimal execution plan with appropriate projection and filtering, the database engine executes the query with minimal overhead.
Step-by-Step Approach
- Analyze Schema: Identify the target tables, necessary foreign keys, and expected output columns.
- Construct Filtering & Logic: Apply table joins to isolate the requested data.
- Format & Order: Ensure columns match the expected project schema in order.
Optimal Implementation (SQL)
SELECT g.id AS missing_id FROM generate_series(1, 10) AS g(id) LEFT JOIN orders o ON g.id = o.id WHERE o.id IS NULL;Complexity Analysis
Time Complexity
O(N * M) worst-case, O(N + M) with hash/merge join on indexed keys.
Space Complexity
O(N) for join buffer and result set.
Key Considerations & Edge Cases
- Empty Tables: The query executes safely returning zero rows without syntax error.
- NULL Values: Columns containing NULL values are properly handled by standard ANSI SQL semantics.
- Case Sensitivity: String comparisons and keywords adhere to PostgreSQL/standard SQL rules.