gst*_*low 2 java concurrency multithreading concurrenthashmap completable-future
我有以下代码:
ConcurrentHashMap taskMap= new ConcurrentHashMap();
....
taskMap.compute(key, (k, queue) -> {
CompletableFuture<Void> future = (queue == null)
? CompletableFuture.runAsync(myTask, poolExecutor)
: queue.whenCompleteAsync((r, e) -> myTask.run(), poolExecutor);
//to prevent OutOfMemoryError in case if we will have too much keys
future.whenComplete((r, e) -> taskMap.remove(key, future));
return future;
});
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如果future已经完成的whenComplete函数参数在与调用相同的线程中compute调用,则此代码的问题。在此方法的主体中,我们从地图中删除条目。但是计算方法文档禁止这样做并且应用程序冻结。
我该如何解决这个问题?
最明显的解决方案是使用whenCompleteAsync代替whenComplete,因为前者保证使用提供的Executor而不是调用线程来执行操作。可以用
Executor ex = r -> { System.out.println("job scheduled"); new Thread(r).start(); };
for(int run = 0; run<2; run++) {
boolean completed = run==0;
System.out.println("*** "+(completed? "with already completed": "with async"));
CompletableFuture<String> source = completed?
CompletableFuture.completedFuture("created in "+Thread.currentThread()):
CompletableFuture.supplyAsync(() -> {
LockSupport.parkNanos(TimeUnit.SECONDS.toNanos(1));
return "created in "+Thread.currentThread();
}, ex);
source.thenApplyAsync(s -> s+"\nprocessed in "+Thread.currentThread(), ex)
.whenCompleteAsync((s,t) -> {
if(t!=null) t.printStackTrace(); else System.out.println(s);
System.out.println("consumed in "+Thread.currentThread());
}, ex)
.join();
}
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这将打印出类似的东西
Executor ex = r -> { System.out.println("job scheduled"); new Thread(r).start(); };
for(int run = 0; run<2; run++) {
boolean completed = run==0;
System.out.println("*** "+(completed? "with already completed": "with async"));
CompletableFuture<String> source = completed?
CompletableFuture.completedFuture("created in "+Thread.currentThread()):
CompletableFuture.supplyAsync(() -> {
LockSupport.parkNanos(TimeUnit.SECONDS.toNanos(1));
return "created in "+Thread.currentThread();
}, ex);
source.thenApplyAsync(s -> s+"\nprocessed in "+Thread.currentThread(), ex)
.whenCompleteAsync((s,t) -> {
if(t!=null) t.printStackTrace(); else System.out.println(s);
System.out.println("consumed in "+Thread.currentThread());
}, ex)
.join();
}
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所以你可以使用
taskMap.compute(key, (k, queue) -> {
CompletableFuture<Void> future = (queue == null)
? CompletableFuture.runAsync(myTask, poolExecutor)
: queue.whenCompleteAsync((r, e) -> myTask.run(), poolExecutor);
//to prevent OutOfMemoryError in case if we will have too much keys
future.whenCompleteAsync((r, e) -> taskMap.remove(key, future), poolExecutor);
return future;
});
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如果提前完成的可能性很大,则可以使用以下方法减少开销
taskMap.compute(key, (k, queue) -> {
CompletableFuture<Void> future = (queue == null)
? CompletableFuture.runAsync(myTask, poolExecutor)
: queue.whenCompleteAsync((r, e) -> myTask.run(), poolExecutor);
//to prevent OutOfMemoryError in case if we will have too much keys
if(future.isDone()) future = null;
else future.whenCompleteAsync((r, e) -> taskMap.remove(key, future), poolExecutor);
return future;
});
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也许,你没有想到这个明显的解决方案,因为你不喜欢依赖动作总是被安排为池的新任务,即使完成已经发生在不同的任务中。您可以使用专门的执行程序解决此问题,该执行程序只会在必要时重新安排任务:
Executor inPlace = Runnable::run;
Thread forbidden = Thread.currentThread();
Executor forceBackground
= r -> (Thread.currentThread()==forbidden? poolExecutor: inPlace).execute(r);
…
future.whenCompleteAsync((r, e) -> taskMap.remove(key, future), forceBackground);
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但是您可能会重新考虑是否真的需要这种复杂的每个映射清理逻辑。这不仅很复杂,而且可能会产生显着的开销,可能会安排大量的清理操作,这些操作在执行时已经过时时并不是真正需要的。
执行起来可能更简单,甚至更高效
taskMap.values().removeIf(CompletableFuture::isDone);
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不时清理整个地图。
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