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This is a medium difficulty Coding & Algorithms question, commonly asked during Technical Screen rounds at Rippling.

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This question is commonly asked for Software Engineer candidates at Rippling during technical interviews.

Compute max simultaneous drivers last 24 hours

Quick Overview

This question evaluates proficiency in reasoning about time-interval overlap, event aggregation, and online data structures for streaming interval queries, testing skills in algorithm design and temporal data handling within the Coding & Algorithms domain.

Company: Rippling

Role: Software Engineer

Category: Coding & Algorithms

Difficulty: medium

Interview Round: Technical Screen

Given delivery intervals (driverId, startTime, endTime) already recorded, implement maxSimultaneousDriverInPast24Hours() that returns the maximum number of distinct drivers who were simultaneously on a delivery at any instant within the window (now−24h, now]. Precisely define "simultaneous" and the interval semantics (open/closed). If multiple times achieve the maximum, optionally also return one such timestamp or the corresponding maximal intervals. Describe an efficient algorithm and data structures that support online inserts from RecordDelivery and queries with strong performance guarantees, and analyze time and space complexity.

Quick Answer: This question evaluates proficiency in reasoning about time-interval overlap, event aggregation, and online data structures for streaming interval queries, testing skills in algorithm design and temporal data handling within the Coding & Algorithms domain.

You are given delivery records that have already been recorded. Each record is a tuple (driverId, startTime, endTime), where times are integer minutes and 24 hours equals 1440 minutes. Implement solution(deliveries, now) to return the maximum number of distinct drivers who were simultaneously on a delivery at any instant within the query window (now - 1440, now]. A delivery interval is half-open: a driver is active at instant t if startTime <= t < endTime. The query window is open on the left and closed on the right. Multiple overlapping or duplicate deliveries for the same driver count as one active driver at that instant. If multiple instants achieve the maximum, return only the maximum count. In an interview follow-up, you may discuss maintaining the same result online under RecordDelivery inserts and repeated queries, but this coding task asks for one query over the current records.

Constraints

0 <= len(deliveries) <= 200000
-10^9 <= startTime < endTime <= now <= 10^9
driverId is an integer
All times are integer minutes; 24 hours = 1440 minutes
Delivery records may be unsorted and may contain duplicate or overlapping intervals for the same driver

Examples

Input: ([], 1000)

Expected Output: 0

Explanation: There are no delivery records, so no driver can be active.

Input: ([(1, 0, 60), (2, 30, 90), (3, 45, 50)], 100)

Expected Output: 3

Explanation: All three distinct drivers are active during the interval [45, 50), so the maximum is 3.

Input: ([(1, 0, 100), (1, 50, 150), (2, 75, 125), (3, 130, 160)], 200)

Expected Output: 2

Explanation: Driver 1's overlapping records merge into one active span [0, 150). The maximum distinct active drivers is 2, for example drivers 1 and 2 during [75, 125).

Input: ([(1, 10, 20), (1, 10, 20), (2, 15, 18)], 30)

Expected Output: 2

Explanation: The duplicate records for driver 1 still count as only one active driver. During [15, 18), drivers 1 and 2 are active.

Input: ([(1, 100, 560), (2, 560, 600), (3, 550, 570), (4, 600, 700), (5, 1990, 2000)], 2000)

Expected Output: 2

Explanation: The window is (560, 2000]. Driver 1's delivery ends exactly at the open left boundary and is ignored. Drivers 2 and 3 overlap just after 560, giving a maximum of 2.

Input: ([(1, 0, 10), (2, 10, 20), (3, 20, 30)], 30)

Expected Output: 1

Explanation: Because delivery intervals are half-open, [0, 10) and [10, 20) do not overlap at time 10. The maximum is 1.

Hints

A same driver can have overlapping records, but must only be counted once. Consider clipping records to the 24-hour window, then merging intervals per driver first.
After each driver's intervals are disjoint, use a sweep line: interval starts add 1 and interval ends subtract 1. Group events with the same timestamp to respect half-open interval semantics.

Quick Overview