使用多处理读取多个文件

Question

使用多处理读取多个文件

Rug*_*rra 5 python performance multiprocessing

我需要读取一些非常大的文本文件(100+ Mb),使用正则表达式处理每一行并将数据存储到结构中.我的结构继承自defaultdict,它有一个read(self)方法,读取self.file_name文件.

看看这个非常简单(但不是真实的)的例子,我没有使用正则表达式,但我正在拆分行:


import multiprocessing
from collections import defaultdict

def SingleContainer():
    return list()

class Container(defaultdict):
    """
    this class store odd line in self["odd"] and even line in self["even"].
    It is stupid, but it's only an example. In the real case the class
    has additional methods that do computation on readen data.
    """
    def __init__(self,file_name):
        if type(file_name) != str:
            raise AttributeError, "%s is not a string" % file_name
        defaultdict.__init__(self,SingleContainer)
        self.file_name = file_name
        self.readen_lines = 0
    def read(self):
        f = open(self.file_name)
        print "start reading file %s" % self.file_name
        for line in f:
            self.readen_lines += 1
            values = line.split()
            key = {0: "even", 1: "odd"}[self.readen_lines %2]
            self[key].append(values)
        print "readen %d lines from file %s" % (self.readen_lines, self.file_name)

def do(file_name):
    container = Container(file_name)
    container.read()
    return container.items()

if __name__ == "__main__":
    file_names = ["r1_200909.log", "r1_200910.log"]
    pool = multiprocessing.Pool(len(file_names))
    result = pool.map(do,file_names)
    pool.close()
    pool.join()
    print "Finish"

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最后,我需要将每个结果加入一个Container中.重要的是保持线的顺序.返回值时,我的方法太慢了.好的解决方案我在Linux上使用python 2.6