Senior Software Engineer, Machine Learning, Google Cloud AI

Google

Given an unsorted array of integers, write a function to sort the array in ascending order using the merge sort algorithm. Explanation of Merge Sort:** Briefly explain the merge sort algorithm, highlighting its divide-and-conquer approach. Implementation:** Provide a step-by-step implementation of the merge sort algorithm. This includes: A mergeSort function that recursively divides the array into smaller subarrays. A merge function that merges two sorted subarrays into a single sorted array. Example:** Input array: [38, 27, 43, 3, 9, 82, 10] Expected output: [3, 9, 10, 27, 38, 43, 82] Efficiency:** Discuss the time and space complexity of merge sort. Why is merge sort considered an efficient sorting algorithm? How does it compare to other sorting algorithms like bubble sort or quicksort in terms of performance (best, average, and worst-case scenarios)? Constraints:** You are not allowed to use built-in sorting functions. The array can contain positive and negative integers. The solution must be implemented in a language of your choice (e.g., Python, Java, C++). Follow-up:** How would you modify the merge sort algorithm to sort the array in descending order? Could you implement an iterative version of merge sort instead of the recursive one? What are the trade-offs?

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

Where do you see yourself in 5 years?