python上传大文件s3_如何用Python高效地将小文件上传到Amazon S3

最近，我需要实现一个程序，以便尽快将位于Amazon EC2中的文件上传到Python中的S3。文件大小为30KB。

我尝试过一些解决方案，使用多线程、多处理、共同例程。下面是我在Amazon EC2上的性能测试结果。

3600(文件数量)*30K(文件大小)~~105M(总计)-->**5.5s [ 4 process + 100 coroutine ]**

10s [ 200 coroutine ]

14s [ 10 threads ]

代码如下所示

用于多线程def mput(i, client, files):

for f in files:

if hash(f) % NTHREAD == i:

put(client, os.path.join(DATA_DIR, f))

def test_multithreading():

client = connect_to_s3_sevice()

files = os.listdir(DATA_DIR)

ths = [threading.Thread(target=mput, args=(i, client, files)) for i in range(NTHREAD)]

for th in ths:

th.daemon = True

th.start()

for th in ths:

th.join()

用于协程client = connect_to_s3_sevice()

pool = eventlet.GreenPool(int(sys.argv[2]))

xput = functools.partial(put, client)

files = os.listdir(DATA_DIR)

for f in files:

pool.spawn_n(xput, os.path.join(DATA_DIR, f))

pool.waitall()

用于多处理def pproc(i):

client = connect_to_s3_sevice()

files = os.listdir(DATA_DIR)

pool = eventlet.GreenPool(100)

xput = functools.partial(put, client)

for f in files:

if hash(f) % NPROCESS == i:

pool.spawn_n(xput, os.path.join(DATA_DIR, f))

pool.waitall()

def test_multiproc():

procs = [multiprocessing.Process(target=pproc, args=(i, )) for i in range(NPROCESS)]

for p in procs:

p.daemon = True

p.start()

for p in procs:

p.join()

机器的配置为Ubuntu 14.04、2个cpu(2.50GHz)、4G内存

达到的最高速度约为19Mb/s(105/5.5)。总的来说，太慢了。有没有办法加快速度？无堆栈python可以更快吗？