Efficiently Sort Large Datasets | Dataford Interview Questions

ZoomInfo processes large collections of prospect and company records that may exceed the practical working memory available to a single operation. Given a list of integers representing sortable record keys, sort the data efficiently by dividing it into bounded chunks and performing a k-way merge.

Implement sort_large_dataset(nums, chunk_size) and return a new list containing all values in nondecreasing order. Each chunk must be sorted independently, then merged using a min-heap rather than repeatedly scanning every chunk.

Formal Specification

Input: nums, a list of integers, and chunk_size, a positive integer.
Output: A new list containing the same values as nums, sorted in nondecreasing order.
The input list must not be modified.

Constraints

0 <= len(nums) <= 100,000
1 <= chunk_size <= 10,000
-10^9 <= nums[i] <= 10^9
The input list must remain unchanged

Function Signature

def sort_large_dataset(nums, chunk_size):

Your question is Efficiently Sort Large Datasets. Start with the requirements in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.

Problem

Formal Specification

Input: nums, a list of integers, and chunk_size, a positive integer.
Output: A new list containing the same values as nums, sorted in nondecreasing order.
The input list must not be modified.

Constraints

0 <= len(nums) <= 100,000
1 <= chunk_size <= 10,000
-10^9 <= nums[i] <= 10^9
The input list must remain unchanged

Function Signature

def sort_large_dataset(nums, chunk_size):

Your question is Efficiently Sort Large Datasets. Start with the requirements in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.