Python 3 Multiprocessing Pool is slow with large variables

I'm running into a very peculiar issue with using multiprocessing pools in Python 3... See the code below:

import multiprocessing as MP                                       

class c(object):                                                   
    def __init__(self):                                            
        self.foo = ""                                              

    def a(self, b):                                                
        return b                                                   

    def main(self):                                                
        with open("/path/to/2million/lines/file", "r") as f:
            self.foo = f.readlines()                               

o = c()                                                            
o.main()                                                           
p = MP.Pool(5)                                                     
for r in p.imap(o.a, range(1,10)):                                 
    print(r)                                                       

If I execute this code as is, this is my extremely slow result:

1
2
3
4
5
6
7
8
9

real    0m6.641s
user    0m7.256s
sys     0m1.824s                    

However, if i removed the line o.main(), then I get much faster execution time:

1
2
3
4
5
6
7
8
9

real    0m0.155s
user    0m0.048s
sys     0m0.004s

My environment has plenty of power, and I've made sure I'm not running into any memory limits. I also tested it with a smaller file, and execution time is much more acceptable. Any insight?

EDIT: I removed the disk IO part, and just created a list instead. I can prove the disk IO has nothing to do with the problem...

for i in range(1,500000):
    self.foo.append("foobar%d\n"%i)

real    0m1.763s user    0m1.944s sys     0m0.452s

for i in range(1,1000000):
    self.foo.append("foobar%d\n"%i)
real    0m3.808s user    0m4.064s sys     0m1.016s