OpenAI VO Interview Question #2: Credits System Design - Out-of-Order Request Processing Expert Guide

OAVOService Exclusive Analysis: Why This Question Defeats 90% of Candidates

This OpenAI credits system design question appears simple but is actually a comprehensive examination of distributed systems, temporal processing, and state management. Many candidates stumble at the "out-of-order requests" critical point, leading to complete interview failure.

OAVOService Professional Reminder: This type of system design question tests not only programming ability but also understanding of real-world business scenarios. We've helped 300+ students successfully tackle OpenAI VO interviews, with a 95% pass rate on this specific question.

Complete Problem Description

You need to build a balance tracking system for the OpenAI API credit purchasing system.

Core Functional Requirements

1. Credit Grants: Users can purchase credit quotas, each quota has ID, activation time, and expiration time
2. Credit Subtraction: Deduct credits during API calls, prioritizing soon-to-expire quotas
3. Balance Queries: Get available balance at specified timestamp

Key Challenge: Out-of-Order Request Processing

Core Difficulty: Due to network instability, requests may arrive out of order. For example:

• Subtraction requests may arrive before grant requests
• Even when grant requests have earlier timestamps

Interface Definition

class Credits:
    def create_grant(
        self, 
        timestamp: int, 
        grant_id: str, 
        amount: int, 
        expiration_timestamp: int
    ) -> None:
        """Create credit grant"""
        pass
    
    def subtract(self, timestamp: int, amount: int) -> None:
        """Subtract credits (prioritize soon-to-expire grants)"""
        pass
    
    def get_balance(self, timestamp: int) -> int | None:
        """Get balance at specified timestamp"""
        pass

OAVOService Expert-Level Solutions

Core Design Philosophy

1. Event Sourcing: Record all operations, reorder and execute by timestamp
2. Lazy Computation: Recalculate state only when queried, ensuring correct temporal order
3. Priority Queue: Automatically handle expiration time priorities

Complete Implementation Solution

from heapq import heappush, heappop
from collections import defaultdict
import bisect

class Credits:
    def __init__(self):
        # Store all events sorted by timestamp
        self.events = []  # [(timestamp, event_type, data), ...]
        
        # Cache computed states
        self.state_cache = {}  # {timestamp: (grants, balance)}
        self.sorted_timestamps = []
    
    def create_grant(self, timestamp, grant_id, amount, expiration_timestamp):
        """Create credit grant event"""
        event = (timestamp, 'grant', {
            'grant_id': grant_id,
            'amount': amount,
            'expiration_timestamp': expiration_timestamp
        })
        
        # Insert event maintaining temporal order
        bisect.insort(self.events, event)
        
        # Clear affected cache
        self._invalidate_cache_from(timestamp)
    
    def subtract(self, timestamp, amount):
        """Create subtraction event"""
        event = (timestamp, 'subtract', {'amount': amount})
        bisect.insort(self.events, event)
        self._invalidate_cache_from(timestamp)
    
    def get_balance(self, timestamp):
        """Get balance at specified timestamp"""
        if timestamp in self.state_cache:
            return self.state_cache[timestamp][1]
        
        # Recompute state to target timestamp
        balance = self._compute_balance_at(timestamp)
        return balance
    
    def _compute_balance_at(self, target_timestamp):
        """Calculate balance at specified timestamp"""
        # Get all events before or at target time
        relevant_events = [
            event for event in self.events 
            if event[0] <= target_timestamp
        ]
        
        # Maintain active grants (min-heap sorted by expiration time)
        active_grants = []  # [(expiration_time, grant_id, remaining_amount)]
        
        for timestamp, event_type, data in relevant_events:
            if event_type == 'grant':
                # Only activate if grant time <= target_timestamp
                if timestamp <= target_timestamp:
                    heappush(active_grants, (
                        data['expiration_timestamp'],
                        data['grant_id'], 
                        data['amount']
                    ))
            
            elif event_type == 'subtract':
                # Execute subtraction operation
                remaining_to_subtract = data['amount']
                temp_grants = []
                
                # Subtract from earliest expiring first
                while active_grants and remaining_to_subtract > 0:
                    exp_time, grant_id, remaining = heappop(active_grants)
                    
                    # Check if expired
                    if exp_time <= target_timestamp:
                        continue  # Skip expired grants
                    
                    if remaining <= remaining_to_subtract:
                        # This grant fully consumed
                        remaining_to_subtract -= remaining
                    else:
                        # Partially consumed
                        temp_grants.append((exp_time, grant_id, remaining - remaining_to_subtract))
                        remaining_to_subtract = 0
                
                # Put back unconsumed grants
                for grant in temp_grants:
                    heappush(active_grants, grant)
                
                if remaining_to_subtract > 0:
                    # Insufficient balance, but don't throw exception (per requirements)
                    return 0
        
        # Calculate final balance (filter expired grants)
        total_balance = 0
        for exp_time, grant_id, remaining in active_grants:
            if exp_time > target_timestamp:  # Not expired
                total_balance += remaining
        
        # Cache result
        self.state_cache[target_timestamp] = (active_grants.copy(), total_balance)
        bisect.insort(self.sorted_timestamps, target_timestamp)
        
        return total_balance
    
    def _invalidate_cache_from(self, timestamp):
        """Clear all cache from specified timestamp onwards"""
        # Find cache entries to clear
        idx = bisect.bisect_left(self.sorted_timestamps, timestamp)
        
        # Clear cache
        for ts in self.sorted_timestamps[idx:]:
            self.state_cache.pop(ts, None)
        
        self.sorted_timestamps = self.sorted_timestamps[:idx]

Optimized Version: Incremental Updates

class OptimizedCredits:
    def __init__(self):
        self.grants = {}  # grant_id -> Grant object
        self.operations = []  # Time-ordered operation log
        self.snapshots = {}  # Timestamp snapshot cache
    
    def create_grant(self, timestamp, grant_id, amount, expiration_timestamp):
        self.grants[grant_id] = {
            'amount': amount,
            'expiration_timestamp': expiration_timestamp,
            'created_at': timestamp
        }
        
        operation = (timestamp, 'grant', grant_id, amount, expiration_timestamp)
        bisect.insort(self.operations, operation)
        
        # Clean affected snapshots
        self._cleanup_snapshots_from(timestamp)
    
    def subtract(self, timestamp, amount):
        operation = (timestamp, 'subtract', amount)
        bisect.insort(self.operations, operation)
        self._cleanup_snapshots_from(timestamp)
    
    def get_balance(self, timestamp):
        # Check cache
        if timestamp in self.snapshots:
            return self.snapshots[timestamp]
        
        # Find nearest snapshot as starting point
        start_snapshot = self._find_nearest_snapshot(timestamp)
        
        # Calculate from snapshot
        balance = self._compute_incremental_balance(start_snapshot, timestamp)
        
        # Save snapshot
        self.snapshots[timestamp] = balance
        
        return balance
    
    def _find_nearest_snapshot(self, timestamp):
        """Find nearest snapshot before timestamp"""
        best_ts = 0
        for ts in self.snapshots:
            if ts <= timestamp and ts > best_ts:
                best_ts = ts
        return best_ts
    
    def _compute_incremental_balance(self, from_timestamp, to_timestamp):
        """Incrementally compute from one timestamp to target"""
        if from_timestamp in self.snapshots:
            # Start from existing snapshot
            current_grants = self.snapshots[from_timestamp]['grants'].copy()
        else:
            # Start from zero
            current_grants = []
        
        # Process all operations in time range
        relevant_ops = [
            op for op in self.operations 
            if from_timestamp < op[0] <= to_timestamp
        ]
        
        for operation in relevant_ops:
            timestamp, op_type = operation[0], operation[1]
            
            if op_type == 'grant':
                _, _, grant_id, amount, exp_time = operation
                current_grants.append({
                    'grant_id': grant_id,
                    'amount': amount,
                    'expiration_timestamp': exp_time,
                    'remaining': amount
                })
            
            elif op_type == 'subtract':
                _, _, amount = operation
                self._process_subtraction(current_grants, amount, timestamp)
        
        # Calculate balance (excluding expired)
        total = sum(
            grant['remaining'] for grant in current_grants
            if grant['expiration_timestamp'] > to_timestamp
        )
        
        return total
    
    def _process_subtraction(self, grants, amount, current_time):
        """Process subtraction operation"""
        # Sort by expiration time (earliest expires first)
        grants.sort(key=lambda x: x['expiration_timestamp'])
        
        remaining = amount
        for grant in grants:
            if grant['expiration_timestamp'] <= current_time:
                continue  # Skip expired
            
            if grant['remaining'] <= 0:
                continue  # Skip depleted
            
            if remaining <= 0:
                break  # Subtraction complete
            
            deduct = min(grant['remaining'], remaining)
            grant['remaining'] -= deduct
            remaining -= deduct

Common Interviewer Follow-ups & OAVOService Standard Responses

Q1: How to handle concurrent access?

Expert Answer:

• Locking Mechanisms: Read-write separation locks for data consistency
• Version Control: Optimistic locking to avoid deadlocks
• Sharding Strategy: User ID-based sharding to reduce lock contention

Q2: How to optimize large historical data queries?

Technical Solutions:

• Snapshot Mechanism: Periodically save state snapshots
• Index Optimization: Timestamp indexes for faster lookups
• Data Archival: Tiered storage for historical data

Q3: How to design system disaster recovery?

Architectural Considerations:

• Master-Slave Replication: Real-time data synchronization
• Operation Logs: WAL ensures no data loss
• Failure Recovery: Rebuild state from logs

OAVOService Exclusive Interview Techniques

STAR-T Response Framework

1. Situation: Clarify business scenarios and technical challenges
2. Task: Break down specific technical tasks
3. Action: Demonstrate solution design thinking
4. Result: Explain solution advantages and trade-offs
5. Technical Deep Dive: Proactively dive into technical details

Code Implementation Key Points

1. Edge Case Handling: Zero balance, negative numbers, duplicate IDs, etc.
2. Performance Considerations: Time complexity analysis and optimization approaches
3. Scalability: How to support additional features (batch operations, transactions, etc.)

Related Extension Problems

• Distributed Transactions: Cross-service credit operations
• Real-time Risk Control: Anomaly behavior detection and limiting
• Data Consistency: Eventual consistency vs strong consistency trade-offs

Summary & Interview Success Strategy

Credits system design tests candidates' ability to abstract complex business scenarios and systematic thinking. Success keys include:

1. Correctly Understanding the essence of out-of-order request problems
2. Reasonably Choosing data structures and algorithms
3. Proactively Considering performance, concurrency, disaster recovery engineering issues
4. Clearly Expressing design thinking and technical trade-offs

OAVOService Professional Interview Assistance Advantages:

• ✅ System design guidance, avoiding directional errors
• ✅ Real-time code implementation assistance, ensuring logical correctness
• ✅ Follow-up response strategies, demonstrating engineering experience depth
• ✅ Technical highlight extraction, standing out to secure offers

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