LeetCode 460: LFU Cache Solution

Master LeetCode problem 460 (LFU Cache), a hard challenge, with our optimized solutions in Java, C++, and Python. Explore detailed explanations, test your code in our interactive editor, and prepare for coding interviews.

460. LFU Cache

Hard

Hash Table Linked List Design Doubly-Linked List

Problem Explanation

Explanation

To implement an LFU cache, we need to keep track of the frequency of each key and also maintain the order of keys based on their frequency and recent usage. We can achieve this by using a combination of data structures: a HashMap to store key-value pairs, a HashMap to store key-frequency pairs, and a TreeMap or a LinkedHashMap to maintain the order of keys based on their frequency and recent usage.

Here are the high-level steps:

Use a HashMap to store the key-value pairs.
Use another HashMap to store the key-frequency pairs.
Use a TreeMap or a LinkedHashMap to maintain the order of keys based on their frequency and recent usage.
Implement get and put methods to update frequencies and order accordingly.

Solution Code

import java.util.*;

class LFUCache {
    private int capacity;
    private Map<Integer, Integer> values;
    private Map<Integer, Integer> frequencies;
    private Map<Integer, LinkedHashSet<Integer>> frequencyMap;
    private int minFrequency;

    public LFUCache(int capacity) {
        this.capacity = capacity;
        values = new HashMap<>();
        frequencies = new HashMap<>();
        frequencyMap = new HashMap<>();
        frequencyMap.put(1, new LinkedHashSet<>());
        minFrequency = 0;
    }

    public int get(int key) {
        if (!values.containsKey(key)) {
            return -1;
        }

        int freq = frequencies.get(key);
        frequencies.put(key, freq + 1);
        frequencyMap.get(freq).remove(key);

        if (freq == minFrequency && frequencyMap.get(freq).size() == 0) {
            minFrequency++;
        }

        if (!frequencyMap.containsKey(freq + 1)) {
            frequencyMap.put(freq + 1, new LinkedHashSet<>());
        }
        frequencyMap.get(freq + 1).add(key);

        return values.get(key);
    }

    public void put(int key, int value) {
        if (capacity <= 0) {
            return;
        }

        if (values.containsKey(key)) {
            values.put(key, value);
            get(key);
            return;
        }

        if (values.size() >= capacity) {
            int evict = frequencyMap.get(minFrequency).iterator().next();
            frequencyMap.get(minFrequency).remove(evict);
            values.remove(evict);
            frequencies.remove(evict);
        }

        values.put(key, value);
        frequencies.put(key, 1);
        frequencyMap.get(1).add(key);
        minFrequency = 1;
    }
}

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