The E-commerce Inventory Bottleneck

A popular online retail platform is experiencing significant performance issues during peak sales hours. The core problem lies in their inventory management system, where multiple users (buyers and administrators) attempt to access and modify inventory levels concurrently. This leads to race conditions, data inconsistencies, and ultimately, lost sales and frustrated customers. Your task is to design a solution that ensures efficient and accurate concurrent access to inventory data.

Problem Description

You are tasked with simulating and optimizing the concurrent access to an Inventory table in a database. The Inventory table stores information about products, including their current stock levels. Multiple operations will be performed concurrently on this table:

• Decrement Stock: When a customer purchases an item, the stock level for that product needs to be decremented.
• Increment Stock: When new stock arrives, or an order is cancelled and items are returned, the stock level needs to be incremented.
• Check Stock: Before allowing a purchase, the system needs to check if sufficient stock is available.

The primary goal is to ensure that these operations can be performed by multiple users simultaneously without leading to data corruption, such as:

• Lost Updates: Two transactions decrementing the same item's stock, where one update overwrites the other.
• Inconsistent Reads: A transaction reading the stock level, performing an action based on it, and then another transaction modifying the stock before the first transaction completes.
• Dirty Reads: A transaction reading data that has been modified by another transaction but not yet committed.

Your solution should demonstrate a strategy for handling these concurrency issues effectively.

Examples

Example 1: Simulating Concurrent Purchases

Initial Inventory:
{ "product_id": 1, "stock_level": 10 }

Concurrent Operations:
1. Transaction A: Attempt to purchase 5 units of product_id 1.
2. Transaction B: Attempt to purchase 7 units of product_id 1.
3. Transaction C: Attempt to purchase 3 units of product_id 1.

Expected Output (after all operations complete, assuming a robust concurrency control mechanism):
Inventory:
{ "product_id": 1, "stock_level": 0 }

Explanation:
Due to concurrency control (e.g., transactions, locks), only one purchase can effectively "reserve" the stock at a time. If Transaction A successfully reserves 5, 5 remain. If Transaction B then tries to reserve 7, it will fail as only 5 are available. If Transaction C then tries to reserve 3, it will succeed (leaving 2). Or, a different order might occur. The key is that the final stock level is consistent and reflects only successful purchases up to the initial stock. The above output assumes a scenario where A, B, and C's attempts would ultimately result in the depletion of stock if executed sequentially or with proper locking, but the specific order of successful decrements matters. For instance, if A buys 5, then C buys 3, then B tries to buy 7 and fails, the final stock would be 2. If the requirement is to *allow* purchases only if stock is available, then the total requested units (5+7+3 = 15) exceeding the initial stock (10) means not all will succeed. A robust system would prevent over-selling. The example output of 0 implies a strict "first-come, first-served" within the available stock.

Example 2: Handling Stock Arrival

Initial Inventory:
{ "product_id": 2, "stock_level": 15 }

Concurrent Operations:
1. Transaction D: Purchase 5 units of product_id 2.
2. Transaction E: Add 20 units to product_id 2 stock.
3. Transaction F: Purchase 12 units of product_id 2.

Expected Output (after all operations complete, assuming a robust concurrency control mechanism):
Inventory:
{ "product_id": 2, "stock_level": 18 }

Explanation:
Transaction D attempts to decrement stock. Transaction E attempts to increment. Transaction F attempts to decrement. A proper system would ensure that E's increment is visible to F before F attempts to decrement, or that E's increment doesn't interfere with D's decrement. For instance, if D succeeds (stock becomes 10), then E succeeds (stock becomes 30), then F succeeds (stock becomes 18). Or, if E succeeds first (stock becomes 35), then D succeeds (stock becomes 30), then F succeeds (stock becomes 18). The crucial aspect is that the final stock accurately reflects additions and subtractions.

Example 3: Edge Case - Stock Depletion and Re-check

Initial Inventory:
{ "product_id": 3, "stock_level": 1 }

Concurrent Operations:
1. Transaction G: Check if stock_level >= 1 for product_id 3. (Returns true)
2. Transaction H: Attempt to purchase 1 unit of product_id 3.
3. Transaction I: Attempt to purchase 1 unit of product_id 3.

Expected Output (after all operations complete, assuming a robust concurrency control mechanism):
Inventory:
{ "product_id": 3, "stock_level": 0 }

Explanation:
Transaction G checks and finds 1 unit available. If G then proceeds to *reserve* that unit and another transaction (like H) also tries to purchase the same unit, only one should succeed. Transaction I should fail as no stock is available after H successfully decrements it. This highlights the importance of atomic check-and-update operations.

Constraints

• The Inventory table has a primary key product_id and a stock_level column (integer).
• Assume a maximum of 1000 concurrent transactions can be active at any given time.
• The stock_level will not exceed 1,000,000 for any single product.
• The number of concurrent operations per product ID can be high, potentially thousands per second during peak times.
• Your solution should aim for minimal locking overhead while guaranteeing correctness.

Notes

Consider different concurrency control mechanisms available in database systems. Think about how transactions are defined and how isolation levels impact concurrent access. The goal is not to write actual SQL, but to describe or pseudocode the approach to optimize for concurrent access. You might describe the use of specific SQL features or patterns. What guarantees can you provide about the state of the inventory data?