ceph/qa/tasks/recovery_bench.py
2016-12-14 11:29:55 -06:00

209 lines
5.5 KiB
Python

"""
Recovery system benchmarking
"""
from cStringIO import StringIO
import contextlib
import gevent
import json
import logging
import random
import time
import ceph_manager
from teuthology import misc as teuthology
log = logging.getLogger(__name__)
@contextlib.contextmanager
def task(ctx, config):
"""
Benchmark the recovery system.
Generates objects with smalliobench, runs it normally to get a
baseline performance measurement, then marks an OSD out and reruns
to measure performance during recovery.
The config should be as follows:
recovery_bench:
duration: <seconds for each measurement run>
num_objects: <number of objects>
io_size: <io size in bytes>
example:
tasks:
- ceph:
- recovery_bench:
duration: 60
num_objects: 500
io_size: 4096
"""
if config is None:
config = {}
assert isinstance(config, dict), \
'recovery_bench task only accepts a dict for configuration'
log.info('Beginning recovery bench...')
first_mon = teuthology.get_first_mon(ctx, config)
(mon,) = ctx.cluster.only(first_mon).remotes.iterkeys()
manager = ceph_manager.CephManager(
mon,
ctx=ctx,
logger=log.getChild('ceph_manager'),
)
num_osds = teuthology.num_instances_of_type(ctx.cluster, 'osd')
while len(manager.get_osd_status()['up']) < num_osds:
time.sleep(10)
bench_proc = RecoveryBencher(
manager,
config,
)
try:
yield
finally:
log.info('joining recovery bencher')
bench_proc.do_join()
class RecoveryBencher:
"""
RecoveryBencher
"""
def __init__(self, manager, config):
self.ceph_manager = manager
self.ceph_manager.wait_for_clean()
osd_status = self.ceph_manager.get_osd_status()
self.osds = osd_status['up']
self.config = config
if self.config is None:
self.config = dict()
else:
def tmp(x):
"""
Local wrapper to print value.
"""
print x
self.log = tmp
log.info("spawning thread")
self.thread = gevent.spawn(self.do_bench)
def do_join(self):
"""
Join the recovery bencher. This is called after the main
task exits.
"""
self.thread.get()
def do_bench(self):
"""
Do the benchmarking.
"""
duration = self.config.get("duration", 60)
num_objects = self.config.get("num_objects", 500)
io_size = self.config.get("io_size", 4096)
osd = str(random.choice(self.osds))
(osd_remote,) = self.ceph_manager.ctx.cluster.only('osd.%s' % osd).remotes.iterkeys()
testdir = teuthology.get_testdir(self.ceph_manager.ctx)
# create the objects
osd_remote.run(
args=[
'adjust-ulimits',
'ceph-coverage',
'{tdir}/archive/coverage'.format(tdir=testdir),
'smalliobench'.format(tdir=testdir),
'--use-prefix', 'recovery_bench',
'--init-only', '1',
'--num-objects', str(num_objects),
'--io-size', str(io_size),
],
wait=True,
)
# baseline bench
log.info('non-recovery (baseline)')
p = osd_remote.run(
args=[
'adjust-ulimits',
'ceph-coverage',
'{tdir}/archive/coverage'.format(tdir=testdir),
'smalliobench',
'--use-prefix', 'recovery_bench',
'--do-not-init', '1',
'--duration', str(duration),
'--io-size', str(io_size),
],
stdout=StringIO(),
stderr=StringIO(),
wait=True,
)
self.process_samples(p.stderr.getvalue())
self.ceph_manager.raw_cluster_cmd('osd', 'out', osd)
time.sleep(5)
# recovery bench
log.info('recovery active')
p = osd_remote.run(
args=[
'adjust-ulimits',
'ceph-coverage',
'{tdir}/archive/coverage'.format(tdir=testdir),
'smalliobench',
'--use-prefix', 'recovery_bench',
'--do-not-init', '1',
'--duration', str(duration),
'--io-size', str(io_size),
],
stdout=StringIO(),
stderr=StringIO(),
wait=True,
)
self.process_samples(p.stderr.getvalue())
self.ceph_manager.raw_cluster_cmd('osd', 'in', osd)
def process_samples(self, input):
"""
Extract samples from the input and process the results
:param input: input lines in JSON format
"""
lat = {}
for line in input.split('\n'):
try:
sample = json.loads(line)
samples = lat.setdefault(sample['type'], [])
samples.append(float(sample['latency']))
except Exception:
pass
for type in lat:
samples = lat[type]
samples.sort()
num = len(samples)
# median
if num & 1 == 1: # odd number of samples
median = samples[num / 2]
else:
median = (samples[num / 2] + samples[num / 2 - 1]) / 2
# 99%
ninety_nine = samples[int(num * 0.99)]
log.info("%s: median %f, 99%% %f" % (type, median, ninety_nine))