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Leetcode #1122: Relative Sort Array

In this guide, we solve Leetcode #1122 Relative Sort Array in Python and focus on the core idea that makes the solution efficient.

You will see the intuition, the step-by-step method, and a clean Python implementation you can use in interviews.

Leetcode

Problem Statement

Given two arrays arr1 and arr2, the elements of arr2 are distinct, and all elements in arr2 are also in arr1. Sort the elements of arr1 such that the relative ordering of items in arr1 are the same as in arr2.

Quick Facts

  • Difficulty: Easy
  • Premium: No
  • Tags: Array, Hash Table, Counting Sort, Sorting

Intuition

Fast membership checks and value lookups are the heart of this problem, which makes a hash map the natural choice.

By storing what we have already seen (or counts/indexes), we can answer the question in one pass without backtracking.

Approach

Scan the input once, using the map to detect when the condition is satisfied and to update state as you go.

This keeps the solution linear while remaining easy to explain in an interview setting.

Steps:

  • Initialize a hash map for seen items or counts.
  • Iterate through the input, querying/updating the map.
  • Return the first valid result or the final computed value.

Example

Input: arr1 = [2,3,1,3,2,4,6,7,9,2,19], arr2 = [2,1,4,3,9,6] Output: [2,2,2,1,4,3,3,9,6,7,19]

Python Solution

class Solution: def relativeSortArray(self, arr1: List[int], arr2: List[int]) -> List[int]: pos = {x: i for i, x in enumerate(arr2)} return sorted(arr1, key=lambda x: pos.get(x, 1000 + x))

Complexity

The time complexity is O(n×log⁡n+m)O(n \times \log n + m)O(n×logn+m), and the space complexity is O(n+m)O(n + m)O(n+m). The space complexity is O(n+m)O(n + m)O(n+m).

Edge Cases and Pitfalls

Watch for boundary values, empty inputs, and duplicate values where applicable. If the problem involves ordering or constraints, confirm the invariant is preserved at every step.

Summary

This Python solution focuses on the essential structure of the problem and keeps the implementation interview-friendly while meeting the constraints.


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