標籤:
死結
線上程間共用多個資源的時候,如果兩個線程分別佔有一部分資源並且同時等待對方的資源,就會造成死結。儘管死結很少發生,但一旦發生就會造成應用的停止回應。下面看一個死結的例子:
按 Ctrl+C 複製代碼按 Ctrl+C 複製代碼
執行結果:
Thread-1 got resA
Thread-1 got resB
Thread-1 got resB
Thread-1 got resA
Thread-2 got resA
Thread-2 got resB
Thread-2 got resB
Thread-2 got resA
Thread-3 got resA
Thread-3 got resB
Thread-3 got resB
Thread-3 got resA
Thread-5 got resA
Thread-5 got resB
Thread-5 got resB
Thread-4 got resA
此時進程已經死掉。
可重新進入鎖
更簡單的死結情況是一個線程“迭代”請求同一個資源,直接就會造成死結:
import threading
import time
class MyThread(threading.Thread):
def run(self):
global num
time.sleep(1)
if mutex.acquire(1):
num = num+1
msg = self.name+‘ set num to ‘+str(num)
print msg
mutex.acquire()
mutex.release()
mutex.release()
num = 0
mutex = threading.Lock()
def test():
for i in range(5):
t = MyThread()
t.start()
if __name__ == ‘__main__‘:
test()
為了支援在同一線程中多次請求同一資源,python提供了“可重新進入鎖”:threading.RLock。RLock內部維護著一個Lock和一個counter變數,counter記錄了acquire的次數,從而使得資源可以被多次require。直到一個線程所有的acquire都被release,其他的線程才能獲得資源。上面的例子如果使用RLock代替Lock,則不會發生死結:
import threading
import time
class MyThread(threading.Thread):
def run(self):
global num
time.sleep(1)
if mutex.acquire(1):
num = num+1
msg = self.name+‘ set num to ‘+str(num)
print msg
mutex.acquire()
mutex.release()
mutex.release()
num = 0
mutex = threading.RLock()
def test():
for i in range(5):
t = MyThread()
t.start()
if __name__ == ‘__main__‘:
test()
執行結果:
Thread-1 set num to 1
Thread-3 set num to 2
Thread-2 set num to 3
Thread-5 set num to 4
Thread-4 set num to 5
python多線程編程(3): 死結和可重新進入鎖