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Problem solution · Java

Online Majority Element In Subarray

Online Majority Element In Subarray: a Java solution using binary search. Learn the idea, check the complexity, and read the full code, with credit to walkccc LeetCode Solutions.

Technique
Binary search
Source
walkccc LeetCode Solutions
Length
35 lines
Start with the idea.

Try the problem first. If you get stuck, read the approach below, then write your own solution. The full code is at the bottom.

Approach

Binary search

For Online Majority Element In Subarray, the implementation exploits a monotonic condition to discard half of the remaining search space after every check.

  1. Identify the ordered answer range or sorted search domain.
  2. Write a predicate whose truth changes only once.
  3. Move the appropriate boundary after each midpoint check and return the final feasible position.

Code notes

  • 35 lines of Java from the credited upstream file 1157.java.
  • The implementation visibly relies on sequence storage, hash lookup, ordered lookup.
  • 2 loop blocks detected.

Complexity

Multiply the logarithmic number of midpoint checks by the cost of one predicate evaluation.

Check the problem constraints before deciding whether this complexity will pass.

Source

Code and credit

This code comes from walkccc LeetCode Solutions by P.-Y. Chen (walkccc) and is used under the MIT licence.

Open problem ↗Original source ↗
Full codeOnline Majority Element In Subarray · JavaJava
Use this to learn the idea, then write your own version.
class MajorityChecker {  public MajorityChecker(int[] arr) {    this.arr = arr;    for (int i = 0; i < arr.length; ++i) {      if (!numToIndices.containsKey(arr[i]))        numToIndices.put(arr[i], new ArrayList<>());      numToIndices.get(arr[i]).add(i);    }  }   public int query(int left, int right, int threshold) {    for (int i = 0; i < TIMES; ++i) {      final int randIndex = rand.nextInt(right - left + 1) + left;      final int num = arr[randIndex];      List<Integer> indices = numToIndices.get(num);      final int l = firstGreaterEqual(indices, left);      final int r = firstGreaterEqual(indices, right + 1);      if (r - l >= threshold)        return num;    }     return -1;  }   private static final int TIMES = 20; // 2^TIMES >> |arr|  private int[] arr;  private Map<Integer, List<Integer>> numToIndices = new HashMap<>();  private Random rand = new Random();   private int firstGreaterEqual(List<Integer> A, int target) {    final int i = Collections.binarySearch(A, target);    return i < 0 ? -i - 1 : i;  }}

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