Hello,
I am trying to implement the multiprocessing in my application to take
advantage of multiple cores. I have created two
Separate process something like this.
que = Queue
Process(target = getData, args=(que , section, MdbFile,)).start()
Process(target = getData, args=(que , section, MdbFile,)).start()
In getData function I create the object(max 7MB size) and add in to queue
(que.put (object)).
After that I fetch the object using que.get () and use in my application.
but it takes more time to get the data.
Any one can help me out this problem.
Thanks,
Sibtey
My code<<<<<
from multiprocessing import Process, Queue
def getData(queue, section, mdbFile):
"""
This function returns the gapappdata for the given mdb file.
"""
app = MdbFile(mdbFile)
mdbData = app.data#it is a heavy object
queue.put((section,mdbData))
def getData2(mdbFile):
"""
This function returns the gapappdata for the given mdb file.
"""
app = MdbFile(mdbFile)
mdbData = app.data#it is a heavy object
return mdbData
def test_multipleProcess(fromMdbFile, toMdbFile):
#multipleProcess
t1 = time.time()
queue = Queue()
sections = ['From', 'To']
Process(target= getData_1, args=(queue, 'From',fromMdbFile,)).start()
Process(target= getData_1, args=(queue, 'To',toMdbFile,)).start()
section, gapAppData = queue.get()
section, gapAppData = queue.get()
t2 = time.time()
print "total time using multiProcessing:",t2-t1
d1 = getData2(fromMdbFile)
d2 = getData2(toMdbFile)
print "total time withought multiProcessing:", time.time()-t2
if __name__=='__main__':
f1 =r" a.mdb"
f2 =r"b.mdb"
test_multipleProcess(f1,f2)
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