编写线程安全的Java缓存读写机制 （原创）

一种习以为常的缓存写法：

IF value in cached THENreturn value from cache ELSEcompute valuesave value in cachereturn value END IF

看上去逻辑无比正确，但实际上会造成2种问题：

1、这种方法是不线程安全的。

2、产生数值写入重复，造成错误的数据。

如下图，在线程1执行计算数值的过程中，线程2也进入数据检查，将多次写入数据，程序非常危险。

 

 

演示错误代码：

//最容易产生的错误写法，先读取缓存，读不到就写缓存public Long getNumber(final long index) {if (cache.containsKey(index)) {return cache.get(index);}final long value = getNumber(index - 1) + getNumber(index - 2);cache.put(index, value);return value;}

 

1、传统的解决办法，使用重入锁 （getNumberByLock 方法）或者同步锁（getNumberBySynchroniz 方法）。

代码

import java.util.ArrayList; import java.util.HashMap; import java.util.List; import java.util.Map; import java.util.concurrent.ExecutorService; import java.util.concurrent.Executors; import java.util.concurrent.Future; import java.util.concurrent.TimeUnit; import java.util.concurrent.locks.Lock; import java.util.concurrent.locks.ReentrantLock;public class NaiveCacheExample {private final Map<Long, Long> cache = new HashMap<>();private Object o=new Object();Lock lock =new ReentrantLock();public NaiveCacheExample() {cache.put(0L, 1L);cache.put(1L, 1L);}//最容易产生的错误写法，先读取缓存，读不到就写缓存public Long getNumber(final long index) {if (cache.containsKey(index)) {return cache.get(index);}final long value = getNumber(index - 1) + getNumber(index - 2);cache.put(index, value);return value;}//使用折返锁，使读写同步public Long getNumberByLock(final long index) { long value =0;try {lock.lock(); if (cache.containsKey(index)) {return cache.get(index);}value = getNumberByLock(index - 1) + getNumberByLock(index - 2);cache.put(index, value);return value;}catch (Exception e){}finally{lock.unlock();}return 0l;}//使用同步，使读写同步public Long getNumberBySynchroniz(final long index) {synchronized (o){long value =0;try {if (cache.containsKey(index)) {return cache.get(index);}value = getNumberBySynchroniz(index - 1) + getNumberBySynchroniz(index - 2);cache.put(index, value);return value;}catch (Exception e){}finally{}}return 0l;}public static void main(final String[] args) {NaiveCacheExample naiveCacheExample =new NaiveCacheExample();Thread threadA =new Thread(new Runnable(){@Overridepublic void run() {System.out.println(naiveCacheExample.getNumberBySynchroniz(1000)); }},"Thread-A");threadA.start();final Thread threadB = new Thread(new Runnable() {public void run() {System.out.println(naiveCacheExample.getNumberBySynchroniz(1000));}}, "Thread-B");threadB.start();} }

 

 

2、一个更好的缓存算法可以用 Callable 和 Future 。 缓存的值将存储在一个实例 ConcurrentMap 中 ，ConcurrentMap 是线程安全的。

代码：

import java.util.concurrent.Callable; import java.util.concurrent.ConcurrentHashMap; import java.util.concurrent.ConcurrentMap; import java.util.concurrent.ExecutionException; import java.util.concurrent.Future; import java.util.concurrent.FutureTask;public class GenericCacheExample<K, V> {private final ConcurrentMap<K, Future<V>> cache = new ConcurrentHashMap<>();private Future<V> createFutureIfAbsent(final K key, final Callable<V> callable) {Future<V> future = cache.get(key);if (future == null) {final FutureTask<V> futureTask = new FutureTask<V>(callable);future = cache.putIfAbsent(key, futureTask);if (future == null) {future = futureTask;futureTask.run();}}return future;}public V getValue(final K key, final Callable<V> callable) throws InterruptedException, ExecutionException {try {final Future<V> future = createFutureIfAbsent(key, callable);return future.get();} catch (final InterruptedException e) {cache.remove(key);throw e;} catch (final ExecutionException e) {cache.remove(key);throw e;} catch (final RuntimeException e) {cache.remove(key);throw e;}}public void setValueIfAbsent(final K key, final V value) {createFutureIfAbsent(key, new Callable<V>() {@Overridepublic V call() throws Exception {return value;}});}}

 

参考博客：

http://www.javacreed.com/how-to-cache-results-to-boost-performance/

转载于:https://www.cnblogs.com/starcrm/p/4968223.html

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