Sorting Questions at Pinterest: What to Expect

Sorting questions appear in roughly 20% of Pinterest’s technical interviews. This focus exists because Pinterest’s core product—organizing and discovering visual content—relies heavily on ordering data. Whether it’s ranking pins in a user’s home feed, displaying search results by relevance, or organizing boards, the ability to efficiently sort and merge datasets is fundamental. Interviewers use these problems to assess your grasp of algorithmic efficiency, your ability to choose the right tool for a data processing task, and your skill in implementing clean, optimized code under constraints.

What to Expect — Types of Problems

You will rarely be asked to implement a basic sorting algorithm like quicksort from scratch. Instead, Pinterest’s sorting questions are typically applied problems where sorting is a key step in the solution. Common patterns include:

• Custom Sorting: Ordering objects based on multiple, sometimes complex, criteria (e.g., sort pins by a weighted score of recency and engagement).
• Merge Intervals: Combining overlapping or adjacent ranges, which is common in scheduling content or managing user sessions.
• Top K Elements: Finding the most frequent, largest, or most relevant items, often solved efficiently with a heap after partial sorting.
• Two-Pointer Techniques on Sorted Data: Problems like finding pairs with a target sum or removing duplicates, which become trivial once data is ordered. Expect the problems to be framed within a product context, such as ordering search results or deduplicating user activity logs.

How to Prepare — Study Tips with One Code Example

Master the theory behind comparison-based sorts (O(n log n)) and linear sorts like Counting Sort for limited integer ranges. Understand the trade-offs between stable and unstable sorts. Most importantly, practice applying sorting as a preprocessing step to simplify more complex problems.

A fundamental pattern is Custom Sorting. You must be comfortable writing comparator functions or using language-specific key functions to define sort order.

# Example: Sort pins by score descending, then by pin_id ascending if tied.
pins = [
    {'pin_id': 101, 'score': 85},
    {'pin_id': 102, 'score': 92},
    {'pin_id': 103, 'score': 85}
]

# Using a lambda as the sort key
pins.sort(key=lambda x: (-x['score'], x['pin_id']))

# Using a custom comparator function (via functools.cmp_to_key)
from functools import cmp_to_key

def compare(a, b):
    if a['score'] != b['score']:
        return b['score'] - a['score']  # Descending score
    return a['pin_id'] - b['pin_id']    # Ascending pin_id

pins.sort(key=cmp_to_key(compare))

Recommended Practice Order

1. Core Algorithms: Understand quicksort and mergesort internals.
2. Basic Application: Solve easy LeetCode problems involving sorting arrays and custom comparators.
3. Key Patterns: Drill medium-difficulty problems on Merge Intervals and Top K Elements.
4. Integration: Tackle hard problems where sorting is one component of a multi-step solution (e.g., finding the minimum number of meeting rooms, which uses sorting and a heap).

Practice Sorting at Pinterest