引言
本文就 《基于LinkedHashMap实现LRU缓存调度算法原理及应用 》一文作为材料,记录一些常见问题,备忘。
延伸出两道常见的Java面试题:
- 插入Entry节点到table表的链表中时,Hashmap 和LinkedHashmap使用头茶法还是尾茶法?遍历map的时候,Entry.Entryset()获取的set集合,是按照从头到尾还是从尾到头的顺序存储的?
- 实现LRU算法最合适的数据结构?
如果读者可以打出来,不用继续看下边的资料了。初学者请继续阅读。相信你读完之后可以找到问题的答案。
LinkedHashMap基础
LinkedHashMap继承了HashMap底层是通过Hash表+单向链表实现Hash算法,内部自己维护了一套元素访问顺序的列表。
- /**
- * The head of the doubly linked list.
- */
- private transient Entry<K,V> header;
- .....
- /**
- * LinkedHashMap entry.
- */
- private static class Entry<K,V> extends HashMap.Entry<K,V> {
- // These fields comprise the doubly linked list used for iteration.
- Entry<K,V> before, after;
HashMap构造函数中回调了子类的init方法实现对元素初始化
- void init() {
- header = new Entry<K,V>(-1, null, null, null);
- header.before = header.after = header;
- }
LinkedHashMap中有一个属性可以执行列表元素的排序算法
- /**
- * The iteration ordering method for this linked hash map: <tt>true</tt>
- * for access-order, <tt>false</tt> for insertion-order.
- *
- * @serial
- */
- private final boolean accessOrder;
accessOrder为true使用访问顺序排序,false使用插入顺序排序那么在哪里可以设置这个值。
- /**
- * Constructs an empty <tt>LinkedHashMap</tt> instance with the
- * specified initial capacity, load factor and ordering mode.
- *
- * @param initialCapacity the initial capacity.
- * @param loadFactor the load factor.
- * @param accessOrder the ordering mode - <tt>true</tt> for
- * access-order, <tt>false</tt> for insertion-order.
- * @throws IllegalArgumentException if the initial capacity is negative
- * or the load factor is nonpositive.
- */
- public LinkedHashMap(int initialCapacity,
- float loadFactor,
- boolean accessOrder) {
- super(initialCapacity, loadFactor);
- this.accessOrder = accessOrder;
- }
LRU算法
使用有访问顺序排序方式实现LRU,那么哪里LinkedHashMap是如何实现LRU的呢?
- //LinkedHashMap方法
- public V get(Object key) {
- Entry<K,V> e = (Entry<K,V>)getEntry(key);
- if (e == null)
- return null;
- e.recordAccess(this);
- return e.value;
- }
- //HashMap方法
- public V put(K key, V value) {
- if (key == null)
- return putForNullKey(value);
- int hash = hash(key.hashCode());
- int i = indexFor(hash, table.length);
- for (Entry<K,V> e = table[i]; e != null; e = e.next) {
- Object k;
- if (e.hash == hash && ((k = e.key) == key || key.equals(k))) {
- V oldValue = e.value;
- e.value = value;
- e.recordAccess(this);
- return oldValue;
- }
- }
- modCount++;
- addEntry(hash, key, value, i);
- return null;
- }
当调用get或者put方法的时候,如果K-V已经存在,会回调Entry.recordAccess()方法
我们再看一下LinkedHashMap的Entry实现
- /**
- * This method is invoked by the superclass whenever the value
- * of a pre-existing entry is read by Map.get or modified by Map.set.
- * If the enclosing Map is access-ordered, it moves the entry
- * to the end of the list; otherwise, it does nothing.
- */
- void recordAccess(HashMap<K,V> m) {
- LinkedHashMap<K,V> lm = (LinkedHashMap<K,V>)m;
- if (lm.accessOrder) {
- lm.modCount++;
- remove();
- addBefore(lm.header);
- }
- }
- /**
- * Remove this entry from the linked list.
- */
- private void remove() {
- before.after = after;
- after.before = before;
- }
- /**
- * Insert this entry before the specified existing entry in the list.
- */
- private void addBefore(Entry<K,V> existingEntry) {
- after = existingEntry;
- before = existingEntry.before;
- before.after = this;
- after.before = this;
- }
recordAccess方法会accessOrder为true会先调用remove清楚的当前首尾元素的指向关系,之后调用addBefore方法,将当前元素加入header之前。
当有新元素加入Map的时候会调用Entry的addEntry方法,会调用removeEldestEntry方法,这里就是实现LRU元素过期机制的地方,默认的情况下removeEldestEntry方法只返回false表示元素永远不过期。
- /**
- * This override alters behavior of superclass put method. It causes newly
- * allocated entry to get inserted at the end of the linked list and
- * removes the eldest entry if appropriate.
- */
- void addEntry(int hash, K key, V value, int bucketIndex) {
- createEntry(hash, key, value, bucketIndex);
- // Remove eldest entry if instructed, else grow capacity if appropriate
- Entry<K,V> eldest = header.after;
- if (removeEldestEntry(eldest)) {
- removeEntryForKey(eldest.key);
- } else {
- if (size >= threshold)
- resize(2 * table.length);
- }
- }
- /**
- * This override differs from addEntry in that it doesn't resize the
- * table or remove the eldest entry.
- */
- void createEntry(int hash, K key, V value, int bucketIndex) {
- HashMap.Entry<K,V> old = table[bucketIndex];
- Entry<K,V> e = new Entry<K,V>(hash, key, value, old);
- table[bucketIndex] = e;
- e.addBefore(header);
- size++;
- }
- protected boolean removeEldestEntry(Map.Entry<K,V> eldest) {
- return false;
- }
基本的原理已经介绍完了,那基于LinkedHashMap我们看一下是该如何实现呢?
import java.util.LinkedHashMap; public class URLLinkedListHashMap<K, V> extends LinkedHashMap<K, V> { /** * */ private static final long serialVersionUID = 1L; /** 最大数据存储容量 */ private static final int LRU_MAX_CAPACITY = 1024; /** 存储数据容量 */ private int capacity; /** * 默认构造方法 */ public URLLinkedListHashMap() { super(); } /** * 带参数构造方法 * @param initialCapacity 容量 * @param loadFactor 装载因子 * @param isLRU 是否使用lru算法,true:使用(按方案顺序排序);false:不使用(按存储顺序排序) */ public URLLinkedListHashMap(int initialCapacity, float loadFactor, boolean isLRU) { super(initialCapacity, loadFactor, isLRU); capacity = LRU_MAX_CAPACITY; } public URLLinkedListHashMap(int initialCapacity, float loadFactor, boolean isLRU,int lruCapacity) { super(initialCapacity, loadFactor, isLRU); this.capacity = lruCapacity; } @Override protected boolean removeEldestEntry(java.util.Map.Entry<K, V> eldest) { // TODO Auto-generated method stub return super.removeEldestEntry(eldest); } }
测试代码:
import java.util.LinkedHashMap; import java.util.Map.Entry; public class LRUTest { public static void main(String[] args) { LinkedHashMap<String, String> map = new URLLinkedListHashMap(16, 0.75f, false); map.put("a", "a"); //a a map.put("b", "b"); //a a b map.put("c", "c"); //a a b c map.put("a", "a"); // b c a map.put("d", "d"); //b b c a d map.put("a", "a"); // b c d a map.put("b", "b"); // c d a b map.put("f", "f"); //c c d a b f map.put("g", "g"); //c c d a b f g map.get("d"); //c a b f g d for (Entry<String, String> entry : map.entrySet()) { System.out.print(entry.getValue() + ", "); } System.out.println(); map.get("a"); //c b f g d a for (Entry<String, String> entry : map.entrySet()) { System.out.print(entry.getValue() + ", "); } System.out.println(); map.get("c"); //b f g d a c for (Entry<String, String> entry : map.entrySet()) { System.out.print(entry.getValue() + ", "); } System.out.println(); map.get("b"); //f g d a c b for (Entry<String, String> entry : map.entrySet()) { System.out.print(entry.getValue() + ", "); } System.out.println(); map.put("h", "h"); //f f g d a c b h for (Entry<String, String> entry : map.entrySet()) { System.out.print(entry.getValue() + ", "); } System.out.println(); } }
答案:
-
插入Entry节点到table表的链表中时,Hashmap 和LinkedHashmap使用头茶法。遍历map的时候,Entry.Entryset()获取的set集合,是按照从尾到头的顺序存储的,采用FIFO原理打印。
- 实现LRU算法最合适的数据结构是LinkedHashmap