Optimizing Sorting for Large Datasets

Context

Sorting is a core operation in systems that process logs, rankings, events, or large analytical inputs. For large datasets, the best approach depends on memory limits, data characteristics, and whether the data fits in RAM.

Core Question

How would you approach optimizing a sorting algorithm for large datasets?

In your answer, explain:

1. How you would choose between comparison-based sorts and specialized linear-time approaches.
2. What changes when the dataset fits in memory versus when it requires external storage.
3. Which practical factors matter most, including stability, cache behavior, parallelism, and partially sorted input.

Scope Guidance

The interviewer expects more than naming algorithms like quicksort or mergesort. You should discuss trade-offs, complexity, implementation concerns, and how dataset properties drive the choice of sorting strategy in real systems.