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Efficient Data Processing Implementation
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Efficient Data Processing Implementation

MediumPython

Problem

A ThoughtWorks MLOps pipeline receives an array of integer feature IDs emitted by model-serving events. Implement a function that returns the k most frequently occurring feature IDs.

Rank IDs by descending frequency. If two IDs have the same frequency, rank the smaller ID first. Return exactly k IDs, or all distinct IDs if fewer than k exist.

Formal Specification

Implement top_k_features(events, k):

  • Input events: a list of integers, where each integer is a feature ID.
  • Input k: a positive integer.
  • Output: a list of up to k distinct integers ordered by descending frequency and then ascending feature ID.

The result must not contain duplicate IDs. The algorithm should avoid sorting every distinct ID when k is much smaller than the number of distinct IDs.

Constraints

  • 1 <= len(events) <= 10^5
  • 1 <= k <= 10^5
  • 0 <= events[i] <= 10^9
  • The input may contain repeated feature IDs

Function Signature

def top_k_features(events, k):
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