Technical Program Manager III, Security, Google Cloud Platform

Google

Let's explore some string manipulation algorithms. Suppose you are given a string s and you need to reverse the order of words in the string. Each word is separated by a single space, and there are no leading or trailing spaces. For example, if the input string s is the sky is blue, the expected output is blue is sky the. Write a function that takes a string s as input and returns a new string with the words in reversed order. Explain your approach. What is the time and space complexity of your algorithm? Provide example test cases to demonstrate that your function works correctly, including edge cases such as an empty string or a string with only one word. As a follow-up, consider a more complex scenario where the input string s might contain leading or trailing spaces, or multiple spaces between words. How would you modify your algorithm to handle these cases while still producing the correct reversed word order? For instance, given the input hello world , the output should be world hello. Describe the changes needed and analyze the updated time and space complexity.

Google

Let's design a rate limiter. This is a crucial component in many systems to prevent abuse and ensure fair usage. Your rate limiter should meet these requirements: Functionality: It should limit the number of requests a user can make within a specific time window. For example, allow a user to make 10 requests per minute. Scalability: The rate limiter needs to handle a large number of users and requests concurrently. Imagine millions of users accessing the system. Accuracy: It should accurately track and enforce the rate limits. A small degree of error is acceptable, but significant deviations are not. Low Latency: The rate limiter must not introduce significant delays in request processing. The overhead should be minimal. Fault Tolerance: The system should continue to function correctly even if some components fail. It should be resilient to outages. Cost-Effectiveness: The solution should be cost-effective in terms of resources used (e.g., memory, CPU, network bandwidth). Consider these scenarios and constraints: Users are identified by a unique ID. The time window is configurable (e.g., seconds, minutes, hours). The rate limit is also configurable per user or group of users. You can use any data structures and algorithms you deem appropriate. Assume you have access to a distributed cache (e.g., Redis, Memcached). Walk me through your design. Discuss different approaches, their trade-offs, and how you would address the requirements. Specifically, consider the following: Data structures for storing request counts. Algorithms for incrementing and checking request counts. Handling concurrency and race conditions. Strategies for distributing the rate limiter across multiple servers. How to handle exceeding the rate limit (e.g., returning an error code). Monitoring and alerting. For example, if a user with ID user123 tries to make 11 requests within a minute when their limit is 10, the rate limiter should reject the 11th request. How would your system achieve this efficiently and reliably at scale?

Google

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