Technical Program Manager II, Google Cloud Business Platforms

Google

Given a tree data structure, and a set of nodes within that tree, how do you find all of their common parents? For example, consider a tree where node A is the root, and it has children B and C. Node B has children D and E, and node C has a child F. If the input set of nodes is {D, E, F}, then the common parents would be {B, C, A}. If the input set of nodes is {D, E}, then the common parents would be {B, A}. Design an algorithm to efficiently find these common parents, considering potential optimizations for different tree structures and sizes.

Google

Let's design a system for URL shortening, like TinyURL. Assume that we need to handle a large number of requests, say billions of URLs per day. Consider the following: Functional Requirements: The system should generate a shorter, unique alias for a given URL. Users should be able to enter a shortened URL and be redirected to the original URL. The shortened URLs should be relatively short. Non-Functional Requirements: The system should be highly available. URL redirection should be as fast as possible. The shortened URLs should be unique. The system should be scalable to handle a large number of URLs and requests. Considerations: How would you design the data model to store the mappings between shortened and original URLs? What algorithms would you use to generate the shortened URLs? Consider the trade-offs between different algorithms. How would you handle collisions (when the same shortened URL is generated for two different original URLs)? What kind of database would you use and why? How would you handle the high volume of traffic and ensure low latency for redirection? Consider caching strategies. How would you scale the system to handle future growth? Walk me through your design, explaining your choices and the rationale behind them. Include diagrams and specific technologies where appropriate. Explain how you would ensure the system meets the requirements for availability, performance, and scalability.

Google

Describe a time you faced a tough technical problem. What made it so difficult, and how did you approach solving it? What resources did you consult, and what was the final outcome? What did you learn from this experience, and how has it shaped your problem-solving skills since then? For example, perhaps you were tasked with optimizing a slow-running query in a large database. The initial attempts to improve performance, such as adding indexes, didn't yield the desired results. You then had to dive deep into the query execution plan, identify bottlenecks, and rewrite the query using more efficient techniques, like leveraging window functions or temporary tables. You could also describe the challenges faced while integrating a new feature into a legacy system with poorly documented code. You might have had to reverse engineer parts of the system, deal with unexpected dependencies, and carefully test the integration to avoid breaking existing functionality. Elaborate on the specific tools and methodologies you employed during these challenges, such as debuggers, profilers, or version control systems. Also, explain how you collaborated with team members or sought assistance from external resources like online forums or documentation to overcome the obstacles.