In this Amazon continuous interview session, the candidate faced three classic problems:

1. Real-time Event Processing System
2. File Search Library (like Unix find)
3. Build Dependency Ordering

Unlike just giving hints, CSOahelp outputs full annotated solutions in real time. The candidate only needs to reproduce the explanation naturally, ensuring structured and confident performance throughout.

Problem 1: Real-time Event Processing System

📜 Original Problem

You are designing a real-time event processing system that ingests a continuous stream of events from multiple sources.
Each event has:

timestamp | Representing time in seconds  
event_id  | Unique identifier  
type      | Event category (e.g., "click", "purchase", "login")  
metadata  | Arbitrary key-value pairs  

The system must support:

1. Insert an event
2. Retrieve the most recent k events
3. Retrieve the most recent k events of a specific type
4. Reject duplicate events (same event_id)
5. Clean up old events (retain only the last N seconds)

✅ Solution Explanation

• Core design:
  • Use a global queue for all events (time-ordered).
  • Maintain a per-type queue for type-specific queries.
  • Use a hash set/map to detect duplicates.
• Operations:
  • Insert → update all structures, then trigger cleanup.
  • Get recent k (all) → read from the end of the global queue.
  • Get recent k (by type) → read from the end of the type queue.
  • Cleanup → evict events older than N seconds from all structures.
• Complexity: Insert O(1), queries O(k), space O(N).
• Extensions:
  • Out-of-order events → need a min-heap or balanced tree.
  • High throughput → integrate Kafka/message queue for batching.
  • Multi-node scaling → partition by event_id or type with consistent hashing.

👉 With CSOahelp’s full solution output, could simply articulate the design clearly, covering both correctness and scalability.

Problem 2: File Search Library (Unix find)

📜 Original Problem

The Unix find command allows searching for files under a directory with criteria.
Two examples:

• Find all files over 5 MB
• Find all XML files

Design a library in a high-level language (like Java) that supports these use cases and is flexible enough for more filters.

✅ Solution Explanation

• Core goal: Don’t just implement recursion — design a reusable, extensible library.
• Framework:
  • Define a FileIterator for directory traversal (lazy evaluation).
  • Define Filter abstraction (SizeFilter, ExtensionFilter), combinable via AND/OR/NOT.
  • Expose a Find API where users can chain filters naturally.
• Extensions:
  • New filters (modified time, regex name match, owner).
  • Error handling (unreadable directories, symlink loops).
  • Parallel traversal for large file systems.
• Complexity: O(F) time to traverse F files; space proportional to traversal depth.

👉 CSOahelp’s prepared solution emphasized API design and extensibility—exactly what Amazon interviewers want to hear.

Problem 3: Build Dependency Ordering

📜 Original Problem

Design an algorithm that simulates a build tool.

Input: A list of components, each with dependencies.
Output: An ordered list of components showing the order in which they should be built, or a message indicating that building is not possible.

✅ Solution Explanation

• Core idea: This is a topological sorting problem.
• Two approaches:
  1. Kahn’s Algorithm (in-degree method)
     • Track indegree counts, repeatedly take nodes with indegree 0.
     • If nodes remain unprocessed → cycle exists.
  2. DFS with cycle detection
     • Three-color marking to detect cycles.
     • Post-order traversal gives a valid build order.
• Complexity: O(V+E), with V = components, E = dependencies.
• Extensions:
  • Incremental builds: only rebuild the affected subgraph.
  • Parallel builds: execute nodes of the same level simultaneously.
  • Deterministic order: use a min-heap to ensure stable lexicographic order.

👉 CSOahelp’s solution included not only the standard algorithms but also real-world extensions like incremental and parallel build systems, which made the candidate’s explanation stand out.

🎯 Final Takeaway

Amazon continuous interviews test not just coding ability but also:

• Can you quickly clarify requirements?
• Can you present a structured, complete solution?
• Can you discuss extensions and complexity analysis?

💡 CSOahelp’s value: Instead of hints, we provide full, annotated answers in real time. The candidate only needs to reproduce them naturally, ensuring confidence and completeness.

In one sentence: We turn potential into performance.

If you’re preparing for algorithm and system design interviews at Apple, Meta, TikTok, etc., but aren’t sure how to break down problems and handle edge cases, get North American interview secrets. We also offer interview proxy, interview assistance, OA writing, and more to help you land your dream job sooner~

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