Fastest way to download 3 million objects from a S3 bucket

Question

I\'ve tried using Python + boto + multiprocessing, S3cmd and J3tset but struggling with all of them.

Any suggestions, perhaps a ready-made script you\'ve been using or a

Answer 1

Okay, I figured out a solution based on @Matt Billenstien's hint. It uses eventlet library. The first step is most important here (monkey patching of standard IO libraries).

Run this script in the background with nohup and you're all set.

from eventlet import *
patcher.monkey_patch(all=True)

import os, sys, time
from boto.s3.connection import S3Connection
from boto.s3.bucket import Bucket

import logging

logging.basicConfig(filename="s3_download.log", level=logging.INFO)


def download_file(key_name):
    # Its imp to download the key from a new connection
    conn = S3Connection("KEY", "SECRET")
    bucket = Bucket(connection=conn, name="BUCKET")
    key = bucket.get_key(key_name)

    try:
        res = key.get_contents_to_filename(key.name)
    except:
        logging.info(key.name+":"+"FAILED")

if __name__ == "__main__":
    conn = S3Connection("KEY", "SECRET")
    bucket = Bucket(connection=conn, name="BUCKET")

    logging.info("Fetching bucket list")
    bucket_list = bucket.list(prefix="PREFIX")

    logging.info("Creating a pool")
    pool = GreenPool(size=20)

    logging.info("Saving files in bucket...")
    for key in bucket.list():
        pool.spawn_n(download_file, key.key)
    pool.waitall()

Answer 2

Use eventlet to give you I/O parallelism, write a simple function to download one object using urllib, then use a GreenPile to map that to a list of input urls -- a pile with 50 to 100 greenlets should do...