python - 使用 python 在大型 .txt 中进行二进制搜索(按哈希排序)

Question

我想搜索一个非常大的文本文件，其中 SHA1 哈希使用 Python 按哈希值排序。文本文件有 10GB 和 500 000 000 行。每行看起来像这样:

000009F0DA8DA60DFCC93B39F3DD51A088ED3FD9:27

我由此比较给定的哈希值是否出现在文件中。我用 BinarySearch 试过了，但它只适用于一个小的测试文件。如果我使用 10GB 的文件，搜索时间会太长，并且有时会终止进程，因为超过了 16GB RAM。

f=open('testfile.txt', 'r')
text=f.readlines()
data=text
#print data
x = '000009F0DA8DA60DFCC93B39F3DD51A088ED3FD9:27'
def binarySearch(data, l, r, x):

  while l <= r:
    mid = l + (r - l)/2;
    # Check if x is present at mid
    if data[mid] == x:
        return mid
    # If x is greater, ignore left half
    elif data[mid] < x:
        l = mid + 1
        #print l
    # If x is smaller, ignore right half
    else:
        r = mid - 1
        #print r
# If we reach here, then the element
# was not present
  return -1


result = binarySearch(data,0, len(data)-1, x)
if result != -1:
   print "Element is present at index % d" % result
else:
   print "Element is not present in array"

有没有办法将 10GB 文本文件一次加载到 RAM 中并一遍又一遍地访问它？我有可用的 16GB RAM。这应该够了吧？ 我还能做些什么来加快搜索速度吗？不幸的是我不知道了。

Answer 1

将您的示例输入作为 input.txt，如下所示

000000005AD76BD555C1D6D771DE417A4B87E4B4:4
00000000A8DAE4228F821FB418F59826079BF368:3
00000000DD7F2A1C68A35673713783CA390C9E93:630
00000001E225B908BAC31C56DB04D892E47536E0:5
00000006BAB7FC3113AA73DE3589630FC08218E7:2
00000008CD1806EB7B9B46A8F87690B2AC16F617:4
0000000A0E3B9F25FF41DE4B5AC238C2D545C7A8:15
0000000A1D4B746FAA3FD526FF6D5BC8052FDB38:16
0000000CAEF405439D57847A8657218C618160B2:15
0000000FC1C08E6454BED24F463EA2129E254D43:40

然后删除计数，使您的文件变为(in.txt 下面):

000000005AD76BD555C1D6D771DE417A4B87E4B4
00000000A8DAE4228F821FB418F59826079BF368
00000000DD7F2A1C68A35673713783CA390C9E93
00000001E225B908BAC31C56DB04D892E47536E0
00000006BAB7FC3113AA73DE3589630FC08218E7
00000008CD1806EB7B9B46A8F87690B2AC16F617
0000000A0E3B9F25FF41DE4B5AC238C2D545C7A8
0000000A1D4B746FAA3FD526FF6D5BC8052FDB38
0000000CAEF405439D57847A8657218C618160B2
0000000FC1C08E6454BED24F463EA2129E254D43

这将确保每个条目的大小都是固定的。

现在您可以使用基于 mmap 的文件读取方法，如此处 https://docs.python.org/3/library/mmap.html

import mmap
import os

FIELD_SIZE=40+1  # also include newline separator

def binarySearch(mm, l, r, x):
    while l <= r:
        mid = int(l + (r - l)/2);
        # Check if x is present at mid
        mid_slice = mm[mid*FIELD_SIZE:(mid+1)*FIELD_SIZE]
        mid_slice = mid_slice.decode('utf-8').strip()
        # print(mid_slice)
        if mid_slice == x:
            return mid
        # If x is greater, ignore left half
        elif mid_slice < x:
            l = mid + 1
            #print l
        # If x is smaller, ignore right half
        else:
            r = mid - 1
            #print r

    # If we reach here, then the element
    # was not present
    return -1

# text=f.readlines()
# data=text
#print data
x = '0000000CAEF405439D57847A8657218C618160B2'

with open('in.txt', 'r+b') as f:
    mm = mmap.mmap(f.fileno(), 0)
    f.seek(0, os.SEEK_END)
    size = f.tell()
    result = binarySearch(mm, 0, size/FIELD_SIZE, x)
    if result != -1:
        print("Element is present at index % d" % result)
    else:
        print("Element is not present in array")

输出:

$ python3 find.py 
Element is present at index  8

由于文件在内存中没有被完全读取，所以不会出现内存不足的错误。