Design a data structure that ingests an integer stream and supports online queries for maximum, mean, and mode. 1) Describe your update and query operations and their time/space complexity. 2) If values are guaranteed to be in the range [1, 1001], propose an exact solution and compute the memory required to maintain the mode. 3) If the value domain is unbounded or memory is constrained, describe how you would approximate the mode, including the accuracy trade-offs. 4) Extend your design to support returning the max, mean, and mode over only the most recent k elements (a sliding window). Explain how you maintain these statistics as the window slides, analyze the complexity, and discuss how you handle ties and empty-window cases.

This question evaluates skills in streaming algorithms, online data-structure design, statistical aggregation (max, mean, mode), and probabilistic approximation techniques for memory-constrained scenarios.

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This is a Medium difficulty Coding & Algorithms question, commonly asked during Technical Screen rounds at Akuna Capital.

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This question is commonly asked for Data Scientist candidates at Akuna Capital during technical interviews.

Design streaming stats with sliding window | Akuna Capital Interview Question

Design a data structure that ingests an integer stream and supports online queries for maximum, mean, and mode.

Describe your update and query operations and their time/space complexity.
If values are guaranteed to be in the range [1, 1001], propose an exact solution and compute the memory required to maintain the mode.
If the value domain is unbounded or memory is constrained, describe how you would approximate the mode, including the accuracy trade-offs.
Extend your design to support returning the max, mean, and mode over only the most recent k elements (a sliding window). Explain how you maintain these statistics as the window slides, analyze the complexity, and discuss how you handle ties and empty-window cases.

Design a data structure that ingests an integer stream and supports online queries for maximum, mean, and mode.

Describe your update and query operations and their time/space complexity.
If values are guaranteed to be in the range [1, 1001], propose an exact solution and compute the memory required to maintain the mode.
If the value domain is unbounded or memory is constrained, describe how you would approximate the mode, including the accuracy trade-offs.
Extend your design to support returning the max, mean, and mode over only the most recent k elements (a sliding window). Explain how you maintain these statistics as the window slides, analyze the complexity, and discuss how you handle ties and empty-window cases.

Design streaming stats with sliding window

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Design streaming stats with sliding window

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