forked from TrueCloudLab/s3-tests
e5f9783053
Static load test script now provides separate functions for generating a list of random-file pointers and uploading those files to an S3 store. When run as a script it still does both, but you can call each function individually from a different script after loading the module.
132 lines
4 KiB
Python
Executable file
132 lines
4 KiB
Python
Executable file
#! /usr/bin/python
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from boto.s3.connection import OrdinaryCallingFormat
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from boto.s3.connection import S3Connection
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from boto.s3.key import Key
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from optparse import OptionParser
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from realistic import RandomContentFile
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import realistic
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import traceback
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import random
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import common
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import yaml
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import boto
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import sys
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def parse_opts():
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parser = OptionParser();
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parser.add_option('-O' , '--outfile', help='write output to FILE. Defaults to STDOUT', metavar='FILE')
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parser.add_option('-b' , '--bucket', dest='bucket', help='push objects to BUCKET', metavar='BUCKET')
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parser.add_option('--seed', dest='seed', help='optional seed for the random number generator')
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return parser.parse_args()
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def connect_s3(host, access_key, secret_key):
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conn = S3Connection(
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calling_format = OrdinaryCallingFormat(),
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is_secure = False,
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host = host,
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aws_access_key_id = access_key,
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aws_secret_access_key = secret_key)
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return conn
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def get_random_files(quantity, mean, stddev, seed):
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"""Create file-like objects with pseudorandom contents.
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IN:
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number of files to create
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mean file size in bytes
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standard deviation from mean file size
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seed for PRNG
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OUT:
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list of file handles
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"""
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file_generator = realistic.files(mean, stddev, seed)
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return [file_generator.next() for _ in xrange(quantity)]
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def upload_objects(bucket, files, seed):
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"""Upload a bunch of files to an S3 bucket
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IN:
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boto S3 bucket object
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list of file handles to upload
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seed for PRNG
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OUT:
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list of boto S3 key objects
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"""
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keys = []
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name_generator = realistic.names(15, 4,seed=seed)
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for fp in files:
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print >> sys.stderr, 'sending file with size %dB' % fp.size
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key = Key(bucket)
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key.key = name_generator.next()
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key.set_contents_from_file(fp)
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keys.append(key)
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return keys
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def main():
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'''To run the static content load test, make sure you've bootstrapped your
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test environment and set up your config.yml file, then run the following:
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S3TEST_CONF=config.yml virtualenv/bin/python generate_objects.py -O urls.txt --seed 1234
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This creates a bucket with your S3 credentials (from config.yml) and
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fills it with garbage objects as described in generate_objects.conf.
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It writes a list of URLS to those objects to ./urls.txt.
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Once you have objcts in your bucket, run the siege benchmarking program:
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siege -rc ./siege.conf -r 5
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This tells siege to read the ./siege.conf config file which tells it to
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use the urls in ./urls.txt and log to ./siege.log. It hits each url in
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urls.txt 5 times (-r flag).
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Results are printed to the terminal and written in CSV format to
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./siege.log
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'''
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(options, args) = parse_opts();
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#SETUP
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random.seed(options.seed if options.seed else None)
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conn = common.s3.main
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if options.outfile:
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OUTFILE = open(options.outfile, 'w')
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elif common.config.file_generation.url_file:
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OUTFILE = open(common.config.file_generation.url_file, 'w')
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else:
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OUTFILE = sys.stdout
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if options.bucket:
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bucket = conn.create_bucket(options.bucket)
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else:
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bucket = common.get_new_bucket()
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keys = []
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print >> OUTFILE, 'bucket: %s' % bucket.name
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print >> sys.stderr, 'setup complete, generating files'
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for profile in common.config.file_generation.groups:
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seed = random.random()
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files = get_random_files(profile[0], profile[1], profile[2], seed)
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keys += upload_objects(bucket, files, seed)
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print >> sys.stderr, 'finished sending files. generating urls'
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for key in keys:
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print >> OUTFILE, key.generate_url(30758400) #valid for 1 year
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print >> sys.stderr, 'done'
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if __name__ == '__main__':
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common.setup()
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try:
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main()
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except Exception as e:
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traceback.print_exc()
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common.teardown()
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