Python3.x 如何将具有多个参数的函数传递给 python concurrent.futures.ProcessPoolExecutor.map()

我想调用一个包含两个或更多参数的函数.在下面的示例中，我使用了lambda函数，并将ref定义为一个大小与numberlist相同、值相同的array.

1st Question:有更好的方法吗？在numberlist的大小可能是百万到十亿个元素的情况下，因此ref size必须遵循numberlist，这种方法不必要地占用宝贵的内存，我希望避免这种情况.我这样做是因为我读到map函数将终止其映射，直到到达最短的数组末端.

import concurrent.futures as cf

nmax = 10
numberlist = range(nmax)
ref = [5, 5, 5, 5, 5, 5, 5, 5, 5, 5]
workers = 3


def _findmatch(listnumber, ref):    
    print('def _findmatch(listnumber, ref):')
    x=''
    listnumber=str(listnumber)
    ref = str(ref)
    print('listnumber = {0} and ref = {1}'.format(listnumber, ref))
    if ref in listnumber:
        x = listnumber
    print('x = {0}'.format(x))
    return x 

a = map(lambda x, y: _findmatch(x, y), numberlist, ref)
for n in a:
    print(n)
    if str(ref[0]) in n:
        print('match')

with cf.ProcessPoolExecutor(max_workers=workers) as executor:
    #for n in executor.map(_findmatch, numberlist):
    for n in executor.map(lambda x, y: _findmatch(x, ref), numberlist, ref):
        print(type(n))
        print(n)
        if str(ref[0]) in n:
            print('match')

运行上面的代码，我发现map函数能够实现我想要的结果.然而，当我把同样的条款转移到concurrent时.期货处理池执行器.map()，Python 3.5因以下错误而失败:

Traceback (most recent call last):
  File "/usr/lib/python3.5/multiprocessing/queues.py", line 241, in _feed
    obj = ForkingPickler.dumps(obj)
  File "/usr/lib/python3.5/multiprocessing/reduction.py", line 50, in dumps
    cls(buf, protocol).dump(obj)
_pickle.PicklingError: Can't pickle <function <lambda> at 0x7fd2a14db0d0>: attribute lookup <lambda> on __main__ failed

Question 2:为什么会发生此错误，以及如何获得并发.期货处理池执行器.map()调用具有多个参数的函数？