Heaps & Intervals

Two patterns share this lesson because they answer the same question in a Palantir round. What is the least work that gets you the part of the data you need? Intervals come up when a range covers some stretch of a line and you care about what is covered, what is free, or how much overlaps. Heaps come up when you need the top few of a large set, or the next item off a stream, without paying to sort everything behind it. Neither is the widest bucket in the coding loop, which arrays and graphs own, but both land often enough that fumbling one on screen costs you a round.

These are canonical problems, and Palantir asks them close to the way you already know them. The pressure is the same pressure the whole loop applies. The code runs against cases in a shared editor, so a solution that only clears the happy path gets caught on the empty input or the boundary in front of the interviewer. The prompts also arrive wrapped in a scenario about sensors, feeds, or field data. The first move is pulling the real interval-or-heap question out of the story before you type. A clean merge and a clean size-k heap that you can write without stalling buy you the room to handle the follow-up that almost always comes next.

The Palantir angle

Coverage-and-gap questions are how Palantir dresses interval merging, because monitoring a real thing is mostly about finding the stretches nobody is watching. A survey craft flies a line and each sensor covers a segment around its position. A set of deployments each guard a slice of a timeline. The task is to fold the covered ranges together and report the gaps that fall through, since the gap is where the risk lives. That is a Premium question plus the complement, asked with a mission wrapped around it. Sort by start, merge anything that touches or overlaps, then walk from the low end emitting the space between one merged block and the next.