Senior Software Engineer, Pixel Camera

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 simplified distributed key-value store. Assume we need to handle a high volume of read and write requests. The key-value store should support the following operations: get(key): Retrieves the value associated with the given key. put(key, value): Stores the value associated with the given key. Here are some specific considerations for the design: Scalability: The system should be able to scale horizontally to handle increasing amounts of data and traffic. Consider how data will be distributed across multiple servers. Consistency: Discuss the consistency model you would implement. Would you choose strong consistency or eventual consistency? What are the trade-offs? Provide a rationale for your choice. Elaborate on how your design ensures that reads return the most up-to-date data (or how it handles potential inconsistencies, if any). Fault Tolerance: How would the system handle server failures? Describe the mechanisms you would implement to ensure data durability and availability in the face of node failures. Explain the role of replication and how it impacts consistency. Data Partitioning: Describe your data partitioning strategy. Consider using techniques like consistent hashing or range-based partitioning. Explain how your chosen strategy affects load balancing and data locality. Provide a concrete example of how keys would be mapped to specific servers in your design. Caching: Where would you incorporate caching in your system to improve read performance? Discuss different caching strategies (e.g., client-side caching, server-side caching) and their implications. Walk me through the architectural components of your key-value store, including the roles of different servers, the communication protocols used, and the data flow for get and put operations. Explain any potential bottlenecks and how you would address them. For example, if consistent hashing is used, how do you handle nodes being added or removed from the cluster?

Google

Tell me about the most challenging project you have ever handled. To provide more context, please consider the following aspects in your response: Describe the project briefly: What were the project's goals, and what was your role? What made it challenging? Was it a technical hurdle, a difficult deadline, a complex team dynamic, ambiguous requirements, or something else? Provide specific examples of the challenges you faced. How did you overcome these challenges? What steps did you take to address the issues? What resources did you utilize? Did you have to learn new skills or technologies on the fly? What was the outcome? Were you able to successfully complete the project? If not, what were the lessons learned? What would you do differently next time? What was your biggest takeaway from the project? How did this experience shape your approach to future projects? Did it change your perspective on teamwork, problem-solving, or project management? For instance, perhaps you led a project to migrate a legacy system to a new cloud-based platform, and you encountered unexpected compatibility issues that required you to develop innovative workarounds. Or maybe you were part of a team that was tasked with developing a new feature for a popular product, but the requirements changed frequently, and the timeline was extremely tight. Sharing these types of details will help me understand the scope and complexity of the project and how you responded to the challenges involved.