【发布时间】:2018-02-21 05:38:55
【问题描述】:
我目前正在尝试使用线程以并行方式获取文件中每个单词的计数,但目前当我添加一个额外的线程时,我的代码会变得更慢。我觉得随着线程的增加,时间应该会减少,直到我的 CPU 出现瓶颈,然后我的时间应该会再次变慢。我不明白为什么它不并行。
这里是代码
import thread
import threading
import time
import sys
class CountWords(threading.Thread):
def __init__(self,lock,tuple):
threading.Thread.__init__(self)
self.lock = lock
self.list = tuple[1]
self.dit = tuple[0]
def run(self):
for word in self.list:
#self.lock.acquire()
if word in self.dit.keys():
self.dit[word] = self.dit[word] + 1
else:
self.dit[word] = 1
#self.lock.release()
def getWordsFromFile(numThreads, fileName):
lists = []
for i in range(int(numThreads)):
k = []
lists.append(k)
print len(lists)
file = open(fileName, "r") # uses .read().splitlines() instead of readLines() to get rid of "\n"s
all_words = map(lambda l: l.split(" "), file.read().splitlines())
all_words = make1d(all_words)
cur = 0
for word in all_words:
lists[cur].append(word)
if cur == len(lists) - 1:
cur = 0
else:
cur = cur + 1
return lists
def make1d(list):
newList = []
for x in list:
newList += x
return newList
def printDict(dit):# prints the dictionary nicely
for key in sorted(dit.keys()):
print key, ":", dit[key]
if __name__=="__main__":
print "Starting now"
start = int(round(time.time() * 1000))
lock=threading.Lock()
ditList=[]
threadList = []
args = sys.argv
numThreads = args[1]
fileName = "" + args[2]
for i in range(int(numThreads)):
ditList.append({})
wordLists = getWordsFromFile(numThreads, fileName)
zipped = zip(ditList,wordLists)
print "got words from file"
for tuple in zipped:
threadList.append(CountWords(lock,tuple))
for t in threadList:
t.start()
for t in threadList:
if t.isAlive():
t.join()
fin = int(round(time.time() * 1000)) - start
print "with", numThreads, "threads", "counting the words took :", fin, "ms"
#printDict(dit)
【问题讨论】:
-
你是用线程来学习的吗?因为我认为这段代码不会从线程中受益,因为在 python 中我们不能并行运行代码。通过添加线程,您只会增加开销,这就是它变慢的原因。当你不想用昂贵的计算或 i/o 阻塞你的代码时,线程主要在 python 中使用。
标签: python multithreading parallel-processing