Question

我正在尝试允许python应用程序访问存储在S3中的多GB文件中的各个位置。我想创建一个替换文件类型的替换对象，它可以在一个单独的线程中智能地从S3下载数据块，以满足seek（）和read（）请求。

我是否可以使用简单的数据结构来存储文件的任意间隔？

它必须支持O（log n）查找和O（n）插入（n =块的数量，而不是文件的大小）。它还需要支持快速查询间隙，以便加载线程可以有效地找到它应下载的下一个块。目前SortedCollection之类的内容不支持此功能，这表明我可能需要在新容器中手动使用bisect_ *。

示例用法是：

import os
import time
from bigfile import BigFile

chunksize = (2**20)*64 # 64MB

bf = BigFile('my_bucket', 'key_name', chunksize=chunksize)

# read from beginning (blocks until first chunk arrives)
bf.read(100)

# continues downloading subsequent chunks in background
time.sleep(10)

# seek into second chunk and read (should not block)
bf.seek(blocksize, os.SEEK_SET)
bf.read(100)

# seek far into the file
bf.seek(blocksize*100 + 54, os.SEEK_SET) # triggers chunk download starting at new location
bf.read(100) # blocks until chunk arrives

# seek back to beginning (should not block, already have this chunk)
bf.seek(0, os.SEEK_SET)
bf.read(100)

# read entire rest of file (blocks until all chunks are downloaded)
bf.read()

Answer 1

此实现使用固定大小和偏移量的块。如果块非常大并且网络非常慢，则读取可能会长时间阻塞（考虑从块的最后一个字节开始读取，它必须等待整个前一个块加载，然后是下一个块）。

理想情况下，我们可以使用任意大小和位置的块，因此我们可以优化加载以从读取点开始。但下面是一个很好的80％解决方案。

import boto
import threading
import tempfile
import os

DEFAULT_CHUNK_SIZE = 2**20 * 64 # 64 MB per request

class BigFile(object):
    def __init__(self, file_obj, file_size, chunksize=DEFAULT_CHUNK_SIZE, start=True):
        self._file_obj = file_obj
        self._file_size = file_size
        self._lock = threading.RLock()
        self._load_condition = threading.Condition(self._lock)
        self._load_run = True
        self._loc = 0
        self._chunk_size = chunksize
        chunk_count = self._file_size // self._chunk_size
        chunk_count += 1 if self._file_size % self._chunk_size else 0
        self._chunks = [None for _ in xrange(chunk_count)]
        self._load_thread = threading.Thread(target=self._load)
        if start:
            self._load_thread.start()

    def _chunk_loc(self):
        ' Returns (chunk_num, chunk_offset) for a given location in the larger file '
        return self._loc // self._chunk_size, self._loc % self._chunk_size

    def _load_chunk(self, chunk_num):
        tf = tempfile.TemporaryFile()
        start_idx = chunk_num * self._chunk_size
        self._file_obj.seek(start_idx)
        tf.write(self._file_obj.read(self._chunk_size))
        with self._lock:
            self._chunks[chunk_num] = (tf, tf.tell()) # (tempfile, size)
            self._load_condition.notify()

    def _load(self):
        while self._load_run:
            # check current chunk, load if needed
            with self._lock:
                chunk_num, _ = self._chunk_loc()
                chunk_and_size = self._chunks[chunk_num]
            if chunk_and_size is None:
                self._load_chunk(chunk_num)

            # find next empty chunk
            for i in xrange(len(self._chunks)):
                cur_chunk = chunk_num + i
                    cur_chunk %= len(self._chunks) # loop around
                if self._chunks[cur_chunk] is None:
                    self._load_chunk(cur_chunk)
                    break
            else:
                # all done, stop thread
                break

    def seek(self, loc, rel=os.SEEK_SET):
        with self._lock:
            if rel == os.SEEK_CUR:
                self._loc += loc
            elif rel == os.SEEK_SET:
                self._loc = loc
            elif rel == os.SEEK_END:
                self._loc = self._file_size + loc

    def read(self, bytes_to_read):
        ret = []
        with self._lock:
            chunk_num, chunk_offset = self._chunk_loc()
            while (bytes_to_read > 0 or bytes_to_read == -1) and chunk_num < len(self._chunks):
                while not self._chunks[chunk_num]:
                    self._load_condition.wait()
                chunk, size = self._chunks[chunk_num]
                cur_chunk_bytes = min(self._chunk_size-chunk_offset, bytes_to_read, size)
                chunk.seek(chunk_offset, os.SEEK_SET)
                data = chunk.read(cur_chunk_bytes)
                ret.append(data)
                bytes_to_read -= len(data)
                chunk_num += 1
        return ''.join(ret)

    def start(self):
        self._load_thread.start()

    def join(self):
        self._load_thread.join()

    def stop(self):
        self._load_run = False

class S3RangeReader:
    def __init__(self, key_obj):
        self._key_obj = key_obj
        self.size = self._key_obj.size
        self._pos = 0

    def __len__(self):
        return self.size

    def seek(self, pos, rel=os.SEEK_SET):
        if rel == os.SEEK_CUR:
            self._pos += pos
        elif rel == os.SEEK_SET:
            self._pos = pos
        elif rel == os.SEEK_END:
            self._pos = self.size + pos

    def read(self, bytes=-1):
        if bytes == 0 or self._pos >= self.size:
            return ''
        else:
            if bytes == -1:
                bytes = self.size
            headers = {'Range': 'bytes=%s-%s' % (self._pos, self._pos + bytes - 1)} # S3 ranges are closed ranges: [start,end]
            return self._key_obj.get_contents_as_string(headers=headers)

if __name__ == '__main__':
    key = boto.s3_connect().get_bucket('mybucket').get_key('my_key')
    reader = S3RangeReader(key)
    bf = BigFile(reader, len(reader)) # download starts by default
    bf.seek(1000000)
    bf.read(100) # blocks
    bf.seek(0)
    bf.read(100) # should not block

从S3下载透明背景文件

1 个答案: