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package com.leetcode.design; | ||
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import java.util.LinkedHashMap; | ||
import java.util.Map; | ||
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import static org.junit.jupiter.api.Assertions.assertEquals; | ||
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/** | ||
* Level: Medium | ||
* Link: https://leetcode.com/problems/lru-cache/ | ||
* Description: | ||
* Design and implement a data structure for Least Recently Used (LRU) cache. It should support the following | ||
* operations: get and put. | ||
* | ||
* get(key) - Get the value (will always be positive) of the key if the key exists in the cache, otherwise return -1. | ||
* put(key, value) - Set or insert the value if the key is not already present. When the cache reached its capacity, it | ||
* should invalidate the least recently used item before inserting a new item. | ||
* | ||
* The cache is initialized with a positive capacity. | ||
* | ||
* Follow up: | ||
* Could you do both operations in O(1) time complexity? | ||
* | ||
* Runtime: <a href="https://leetcode.com/submissions/detail/253383205/">54 ms</a>. | ||
* | ||
* @author rampatra | ||
* @since 2019-08-20 | ||
*/ | ||
public class LRUCache { | ||
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private LinkedHashMap<Integer, Integer> cache; | ||
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public LRUCache(int capacity) { | ||
this.cache = new LinkedHashMap<Integer, Integer>(capacity, 0.75f, true) { | ||
@Override | ||
protected boolean removeEldestEntry(Map.Entry eldest) { | ||
return size() > capacity; | ||
} | ||
}; | ||
} | ||
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public int get(int key) { | ||
Integer val = cache.get(key); | ||
return val == null ? -1 : val; | ||
} | ||
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public void put(int key, int value) { | ||
cache.put(key, value); | ||
} | ||
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public static void main(String[] args) { | ||
LRUCache cache = new LRUCache(2); | ||
cache.put(1,1); | ||
cache.put(2,2); | ||
cache.put(1,1); | ||
cache.put(3,3); | ||
assertEquals(1, cache.get(1)); | ||
assertEquals(-1, cache.get(2)); | ||
assertEquals(3, cache.get(3)); | ||
} | ||
} |