def setThreads(self, file):
''' Funcio que calcula els parametres per la funcio map i crea N threads que executraran el map().
En aquesta funcio els parametres depenen del tamany en bytes del tros que volem que un thread analitzi. Es el parametre
self.size '''
num_threads = self.getThreads(file)
total_size = os.path.getsize(file)
size_thread = total_size / num_threads
if 'i' in self.arguments:
self.printInformation(file)
pos_start_read = 0
size_to_read = 0
for iteration in range(num_threads):
if iteration + 1 == num_threads:
#last thread reads left data
size_to_read = total_size - pos_start_read
else:
size_to_read = self.checkSize(file, size_thread,
pos_start_read)
thread = threading.Thread(target=self.map,
args=(file, size_to_read,
pos_start_read))
thread.run()
size_to_read += pos_start_read
pos_start_read = size_to_read
self.reduce(file)
os._exit(0) #acaba el proces
''' MAP REDUCE'''
def wrapped( *args, **kwargs ): thread = Enhanced( notifier.Callback( func, *args, **kwargs ), finished_func ) thread.run()
import thread
hi = 1
def prin():
if hi == "y":
print(no)
a = 1
no = 1 / a
p = prin()
print(a)
while True:
hi = input()
a = a + 2
no = no - 1 / a
a = a + 2
no = no + 1 / a
thread.run(p)
def run_async_calculate_center(thread):
thread.run()
