Add performance tests to SwiftOnHPSS
This commit is contained in:
Phil Bridges
parent
ef2d07ea48
commit
cb2c1022dc
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[config]
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# The Keystone URL to talk to
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#authurl=http://localhost:5000/v2.0
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# The username to login as
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#username=admin
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# The tenant name to scope into
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#tenantname=admin
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# The password for that user
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#password=password
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# How many workers to spin up
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#num_workers=2
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# How many write/read cycles to execute
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#num_cycles=8
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# The name of the SwiftOnHPSS storage policy configured on your Swift cluster
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#hpss_storage_policy=hpss
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#!/usr/bin/env python
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#
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# Copyright (c) 2015-2016 IBM Corporation
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
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# implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import swiftclient
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import multiprocessing
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import os
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import time
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import ConfigParser
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import collections
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import itertools
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from pprint import pprint as pretty_print
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# This is here because you can't normally do multiprocessing on
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# instance methods. We get around that restriction by using this
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# top-level function in the worker process as the execution target
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# to call it for us, with the class state and method name pickled and
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# piped in through a queue. Who needs the Law of Demeter anyway?!
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def _call_instance_method(instance, method_name, *args, **kwargs):
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return getattr(instance.__class__, method_name)(instance, *args, **kwargs)
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def _parse_config():
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parser = ConfigParser.SafeConfigParser()
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parser.read('systemtest.cfg')
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options = {}
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for opt in ['authurl', 'username', 'tenantname',
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'password', 'num_workers', 'num_cycles',
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'hpss_storage_policy']:
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options[opt] = parser.get('config', opt)
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# These are specifically numbers.
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options['num_workers'] = int(options['num_workers'])
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options['num_cycles'] = int(options['num_cycles'])
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return options
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def apply_ansi(string_to_format, ansi_codes):
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input_codes = ansi_codes
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if type(input_codes) is int:
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input_codes = [ansi_codes]
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if len(input_codes) is 0:
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return string_to_format
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code_str = ";".join(map(str, input_codes))
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return '\033[%sm%s\033[0m' % (code_str, string_to_format)
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def average(value_list):
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if len(value_list) == 0:
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return 0
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return sum(value_list) / len(value_list)
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def chain(value, *fns):
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result = value
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for fn in fns:
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result = fn(result)
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return result
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def human_readable_size(size, over_time=True):
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if over_time:
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prefixes = ['B/s', 'KiB/s', 'MiB/s', 'GiB/s', 'TiB/s', 'PiB/s', 'EiB/s']
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else:
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prefixes = ['B', 'KiB', 'MiB', 'GiB', 'TiB', 'PiB', 'EiB']
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tmp = size
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magnitude = 0
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while tmp >= 1024 and magnitude < len(prefixes)-1:
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tmp /= 1024.0
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magnitude += 1
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return '%f %s' % (tmp, prefixes[magnitude])
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ansi_modes = {'clear': 0,
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'bold': 1,
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'blink': 5,
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'fg_black': 30,
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'fg_red': 31,
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'fg_green': 32,
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'fg_yellow': 33,
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'fg_blue': 34,
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'fg_magenta': 35,
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'fg_cyan': 36,
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'fg_white': 37,
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'bg_black': 40,
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'bg_red': 41,
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'bg_green': 42,
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'bg_yellow': 43,
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'bg_blue': 44,
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'bg_magenta': 45,
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'bg_cyan': 46,
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'bg_white': 47}
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# These three things are all classes in their own right.
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IORecord = collections.namedtuple('IORecord', ['size', 'elapsed_time'])
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TestWorkerRecord = collections.namedtuple('TestWorkerRecord',
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['handle', 'queue'])
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TestResultRecord = collections.namedtuple('TestResultRecord',
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['worker_pid', 'write_result',
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'read_result', 'test_size', 'cycle'])
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class TimedReader:
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def __init__(self, source, size=None):
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self.source = source
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self.read_samples = []
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self.done = False
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self.last_read_time = time.time()
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self.size = size
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self._total_read = 0
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def read(self, size):
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current = time.time()
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result = self.source.read(size)
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bytes_read = len(result)
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self.read_samples.append(
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IORecord(size=bytes_read,
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elapsed_time=current - self.last_read_time))
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self._total_read += bytes_read
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self.last_read_time = current
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if result == '' or (self._total_read >= self.size):
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self.done = True
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return result
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def reset(self):
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self.source.seek(0)
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self.read_samples = []
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self.done = False
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self.last_read_time = time.time()
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self._total_read = 0
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def time_so_far(self):
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return sum([rec.elapsed_time for rec in self.read_samples])
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def read_so_far(self):
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return sum([rec.size for rec in self.read_samples])
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def io_rate(self):
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return self.read_so_far() / self.time_so_far()
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class PerformanceTestWorker():
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def __init__(self, args, queue):
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self.pid = None
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self.args = args
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self.queue = queue
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self.files_written = []
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self.swift_connection = None
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self.results = []
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# This process is what the controller process calls to start execution.
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def start(self, sem):
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worker = multiprocessing.Process(target=_call_instance_method,
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args=(self, '_do_it', sem))
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worker.start()
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# This function gets bootstrapped on the remote process side.
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def _do_it(self, semaphore):
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semaphore.acquire()
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try:
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self.pid = os.getpid()
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num_cycles = int(self.args['num_cycles'])
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MEGABYTE = 1024*1024
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sizes = [1*MEGABYTE, 4*MEGABYTE, 16*MEGABYTE, 64*MEGABYTE]
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self.swift_connection = swiftclient.client.Connection(
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authurl=self.args['authurl'],
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user=self.args['username'],
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key=self.args['password'],
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tenant_name=self.args['tenantname'],
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auth_version='2')
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for cycle in xrange(1, num_cycles+1):
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for size in sizes:
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result = self._test_cycle(size, cycle)
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self.results.append(result)
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except:
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self.queue.put([])
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raise
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else:
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self.queue.put(self.results)
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finally:
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semaphore.release()
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def _test_cycle(self, size, cycle):
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zero_name = '%d-%d-zero-%d' % (size, self.pid, cycle)
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random_name = '%d-%d-random-%d' % (size, self.pid, cycle)
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zero_file = open('/tmp/%s' % zero_name, 'w')
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random_file = open('/tmp/%s' % random_name, 'w')
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# Create files to read from, to make test more accurate
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zero_file.write(open('/dev/zero').read(size))
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random_file.write(open('/dev/urandom').read(size))
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zero_file.close()
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random_file.close()
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zero_file = open('/tmp/%s' % zero_name, 'r')
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random_file = open('/tmp/%s' % random_name, 'r')
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# Write the file
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zero_timer = TimedReader(zero_file, size)
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self.swift_connection.put_object('.performance_test',
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zero_name,
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zero_timer, size)
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random_timer = TimedReader(random_file, size)
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self.swift_connection.put_object('.performance_test',
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random_name,
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random_timer, size)
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write_result = {'zero_avg': zero_timer.io_rate(),
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'random_avg': random_timer.io_rate(),
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}
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# Read the file back
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zero_stream = \
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self.swift_connection.get_object('.performance_test', zero_name,
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resp_chunk_size=65536)[1]
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random_stream = \
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self.swift_connection.get_object('.performance_test', random_name,
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resp_chunk_size=65536)[1]
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zero_timer = TimedReader(zero_stream, size)
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random_timer = TimedReader(random_stream, size)
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read_size = 65536
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while not (zero_timer.done or random_timer.done):
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zero_timer.read(read_size)
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random_timer.read(read_size)
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read_result = {'zero_avg': zero_timer.io_rate(),
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'random_avg': random_timer.io_rate(),
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}
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# Cleanup
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self.swift_connection.delete_object('.performance_test', zero_name)
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self.swift_connection.delete_object('.performance_test', random_name)
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os.unlink('/tmp/%s' % zero_name)
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os.unlink('/tmp/%s' % random_name)
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return TestResultRecord(write_result=write_result,
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read_result=read_result,
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worker_pid=self.pid,
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test_size=size,
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cycle=cycle)
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class PerformanceTestController():
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def __init__(self, args):
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self.args = args
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self.semaphore = None
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self.workers = []
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def create_worker(self):
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queue = multiprocessing.Queue()
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worker = PerformanceTestWorker(self.args, queue)
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self.workers.append(TestWorkerRecord(worker, queue))
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def start_test(self):
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self.semaphore = multiprocessing.Semaphore(len(self.workers))
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for worker_record in self.workers:
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worker_record.handle.start(self.semaphore)
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def is_done(self):
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if not self.semaphore:
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return False
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return self.semaphore.get_value() == len(self.workers)
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def get_results(self):
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worker_results = [worker.queue.get() for worker in self.workers]
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results = list(itertools.chain(*worker_results))
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# This next bit only works because Python's sort algorithm is stable.
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# What this is supposed to do is sort this list so that we have
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# the test size as the primary sort key, then worker_pid, then cycle.
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# The order matters.
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results = sorted(results, key=lambda x: x.cycle)
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results = sorted(results, key=lambda x: x.worker_pid)
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results = sorted(results, key=lambda x: x.test_size)
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return results
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# TODO: is there any nicer way to handle the view for this test?
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# maybe in the future some fancy graphical view? something to copy-paste
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# into slide decks
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class PerformanceTestViewer():
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def __init__(self, results):
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self.results = results
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def title(self, content):
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return apply_ansi(content, ansi_modes['bold'])
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def header(self, content):
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return apply_ansi(content, ansi_modes['fg_green'])
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def error(self, content):
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return apply_ansi(content, ansi_modes['fg_red'])
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def _group_by(self, iterable, keyfunc):
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return {k: list(v) for k, v
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in itertools.groupby(iterable, key=keyfunc)}
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# TODO: make this much more concise
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def show_results(self):
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size_to_results = self._group_by(self.results,
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keyfunc=lambda x: x.test_size)
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pretty_print(size_to_results)
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for size in size_to_results:
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pid_to_results = self._group_by(size_to_results[size],
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keyfunc=lambda x: x.worker_pid)
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print self.title('Testing with files of size %s:' %
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human_readable_size(size, over_time=False))
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print '---'
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print self.header(' Ingesting random bytes:')
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for pid in pid_to_results:
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print self.header(' Worker %s:' % pid), \
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map(lambda res: human_readable_size(
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res.write_result['random_avg']),
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pid_to_results[pid])
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print self.header(' Overall average per worker:'), \
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chain(map(lambda res: res.write_result['random_avg'],
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size_to_results[size]), average, human_readable_size)
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print ''
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print self.header(' Ingesting zero bytes:')
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for pid in pid_to_results:
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print self.header(' Worker %s:' % pid), \
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map(lambda res: human_readable_size(
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res.write_result['zero_avg']),
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pid_to_results[pid])
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print self.header(' Overall average per worker:'), \
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chain(map(lambda res: res.write_result['zero_avg'],
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size_to_results[size]), average, human_readable_size)
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print ''
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print self.header(' Recalling random bytes:')
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for pid in pid_to_results:
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print self.header(' Worker %s:' % pid), \
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map(lambda res: human_readable_size(
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res.read_result['random_avg']),
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pid_to_results[pid])
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print self.header(' Overall average per worker:'), \
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chain(map(lambda res: res.read_result['random_avg'],
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size_to_results[size]), average, human_readable_size)
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print ''
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print self.header(' Recalling zero bytes:')
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for pid in pid_to_results:
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print self.header(' Worker %s:' % pid), \
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map(lambda res: human_readable_size(
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res.read_result['zero_avg']),
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pid_to_results[pid])
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print self.header(' Overall average per worker:'), \
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chain(map(lambda res: res.read_result['zero_avg'],
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size_to_results[size]), average, human_readable_size)
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print '---'
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print ''
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def main():
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args = _parse_config()
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worker_count = int(args['num_workers'])
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swift = swiftclient.client.Connection(authurl=args['authurl'],
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user=args['username'],
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tenant_name=args['tenantname'],
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key=args['password'],
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auth_version='2')
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swift.put_container('.performance_test',
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{'X-Storage-Policy':
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args['hpss_storage_policy']})
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controller = PerformanceTestController(args)
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for i in xrange(0, worker_count):
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controller.create_worker()
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print "Starting %d worker(s)..." % worker_count
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controller.start_test()
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print "Waiting for test results..."
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# Wait for all "threads" to finish
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time.sleep(.5)
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while not controller.is_done():
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time.sleep(.1)
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all_results = controller.get_results()
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view = PerformanceTestViewer(all_results)
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view.show_results()
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if __name__ == "__main__":
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main()
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