/usr/lib/python2.7/dist-packages/gnocchi/storage/ceph.py is in python-gnocchi 3.0.4-3.
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#
# Copyright © 2014-2015 eNovance
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
from collections import defaultdict
import contextlib
import datetime
import errno
import itertools
import uuid
from oslo_config import cfg
from oslo_log import log
from oslo_utils import importutils
from gnocchi import storage
from gnocchi.storage import _carbonara
LOG = log.getLogger(__name__)
for RADOS_MODULE_NAME in ('cradox', 'rados'):
rados = importutils.try_import(RADOS_MODULE_NAME)
if rados is not None:
break
else:
RADOS_MODULE_NAME = None
if rados is not None and hasattr(rados, 'run_in_thread'):
rados.run_in_thread = lambda target, args, timeout=None: target(*args)
LOG.info("rados.run_in_thread is monkeypatched.")
OPTS = [
cfg.StrOpt('ceph_pool',
default='gnocchi',
help='Ceph pool name to use.'),
cfg.StrOpt('ceph_username',
help='Ceph username (ie: admin without "client." prefix).'),
cfg.StrOpt('ceph_secret', help='Ceph key', secret=True),
cfg.StrOpt('ceph_keyring', help='Ceph keyring path.'),
cfg.StrOpt('ceph_conffile',
default='/etc/ceph/ceph.conf',
help='Ceph configuration file.'),
]
class CephStorage(_carbonara.CarbonaraBasedStorage):
WRITE_FULL = False
def __init__(self, conf):
super(CephStorage, self).__init__(conf)
self.pool = conf.ceph_pool
options = {}
if conf.ceph_keyring:
options['keyring'] = conf.ceph_keyring
if conf.ceph_secret:
options['key'] = conf.ceph_secret
if not rados:
raise ImportError("No module named 'rados' nor 'cradox'")
if not hasattr(rados, 'OmapIterator'):
raise ImportError("Your rados python module does not support "
"omap feature. Install 'cradox' (recommended) "
"or upgrade 'python-rados' >= 9.1.0 ")
LOG.info("Ceph storage backend use '%s' python library" %
RADOS_MODULE_NAME)
# NOTE(sileht): librados handles reconnection itself,
# by default if a call timeout (30sec), it raises
# a rados.Timeout exception, and librados
# still continues to reconnect on the next call
self.rados = rados.Rados(conffile=conf.ceph_conffile,
rados_id=conf.ceph_username,
conf=options)
self.rados.connect()
self.ioctx = self.rados.open_ioctx(self.pool)
# NOTE(sileht): constants can't be class attributes because
# they rely on presence of rados module
# NOTE(sileht): We allow to read the measure object on
# outdated replicats, that safe for us, we will
# get the new stuffs on next metricd pass.
self.OMAP_READ_FLAGS = (rados.LIBRADOS_OPERATION_BALANCE_READS |
rados.LIBRADOS_OPERATION_SKIPRWLOCKS)
# NOTE(sileht): That should be safe to manipulate the omap keys
# with any OSDs at the same times, each osd should replicate the
# new key to others and same thing for deletion.
# I wonder how ceph handle rm_omap and set_omap run at same time
# on the same key. I assume the operation are timestamped so that will
# be same. If not, they are still one acceptable race here, a rm_omap
# can finish before all replicats of set_omap are done, but we don't
# care, if that occurs next metricd run, will just remove it again, no
# object with the measure have already been delected by previous, so
# we are safe and good.
self.OMAP_WRITE_FLAGS = rados.LIBRADOS_OPERATION_SKIPRWLOCKS
def stop(self):
self.ioctx.aio_flush()
self.ioctx.close()
self.rados.shutdown()
super(CephStorage, self).stop()
def upgrade(self, index):
super(CephStorage, self).upgrade(index)
# Move names stored in xattrs to omap
try:
xattrs = tuple(k for k, v in
self.ioctx.get_xattrs(self.MEASURE_PREFIX))
except rados.ObjectNotFound:
return
with rados.WriteOpCtx() as op:
self.ioctx.set_omap(op, xattrs, xattrs)
self.ioctx.operate_write_op(op, self.MEASURE_PREFIX,
flags=self.OMAP_WRITE_FLAGS)
for xattr in xattrs:
self.ioctx.rm_xattr(self.MEASURE_PREFIX, xattr)
def _store_new_measures(self, metric, data):
# NOTE(sileht): list all objects in a pool is too slow with
# many objects (2min for 20000 objects in 50osds cluster),
# and enforce us to iterrate over all objects
# So we create an object MEASURE_PREFIX, that have as
# omap the list of objects to process (not xattr because
# it doesn't allow to configure the locking behavior)
name = "_".join((
self.MEASURE_PREFIX,
str(metric.id),
str(uuid.uuid4()),
datetime.datetime.utcnow().strftime("%Y%m%d_%H:%M:%S")))
self.ioctx.write_full(name, data)
with rados.WriteOpCtx() as op:
self.ioctx.set_omap(op, (name,), ("",))
self.ioctx.operate_write_op(op, self.MEASURE_PREFIX,
flags=self.OMAP_WRITE_FLAGS)
def _build_report(self, details):
names = self._list_object_names_to_process()
metrics = set()
count = 0
metric_details = defaultdict(int)
for name in names:
count += 1
metric = name.split("_")[1]
metrics.add(metric)
if details:
metric_details[metric] += 1
return len(metrics), count, metric_details if details else None
def _list_object_names_to_process(self, prefix=""):
with rados.ReadOpCtx() as op:
omaps, ret = self.ioctx.get_omap_vals(op, "", prefix, -1)
try:
self.ioctx.operate_read_op(
op, self.MEASURE_PREFIX, flag=self.OMAP_READ_FLAGS)
except rados.ObjectNotFound:
# API have still written nothing
return ()
# NOTE(sileht): after reading the libradospy, I'm
# not sure that ret will have the correct value
# get_omap_vals transforms the C int to python int
# before operate_read_op is called, I dunno if the int
# content is copied during this transformation or if
# this is a pointer to the C int, I think it's copied...
if ret == errno.ENOENT:
return ()
return (k for k, v in omaps)
def _pending_measures_to_process_count(self, metric_id):
object_prefix = self.MEASURE_PREFIX + "_" + str(metric_id)
return len(list(self._list_object_names_to_process(object_prefix)))
def list_metric_with_measures_to_process(self, size, part, full=False):
names = self._list_object_names_to_process()
if full:
objs_it = names
else:
objs_it = itertools.islice(names, size * part, size * (part + 1))
return set([name.split("_")[1] for name in objs_it])
def _delete_unprocessed_measures_for_metric_id(self, metric_id):
object_prefix = self.MEASURE_PREFIX + "_" + str(metric_id)
object_names = self._list_object_names_to_process(object_prefix)
# Now clean objects and xattrs
with rados.WriteOpCtx() as op:
# NOTE(sileht): come on Ceph, no return code
# for this operation ?!!
self.ioctx.remove_omap_keys(op, tuple(object_names))
self.ioctx.operate_write_op(op, self.MEASURE_PREFIX,
flags=self.OMAP_WRITE_FLAGS)
for n in object_names:
self.ioctx.aio_remove(n)
@contextlib.contextmanager
def _process_measure_for_metric(self, metric):
object_prefix = self.MEASURE_PREFIX + "_" + str(metric.id)
object_names = list(self._list_object_names_to_process(object_prefix))
measures = []
for n in object_names:
data = self._get_object_content(n)
measures.extend(self._unserialize_measures(n, data))
yield measures
# Now clean objects and xattrs
with rados.WriteOpCtx() as op:
# NOTE(sileht): come on Ceph, no return code
# for this operation ?!!
self.ioctx.remove_omap_keys(op, tuple(object_names))
self.ioctx.operate_write_op(op, self.MEASURE_PREFIX,
flags=self.OMAP_WRITE_FLAGS)
for n in object_names:
self.ioctx.aio_remove(n)
@staticmethod
def _get_object_name(metric, timestamp_key, aggregation, granularity,
version=3):
name = str("gnocchi_%s_%s_%s_%s" % (
metric.id, timestamp_key, aggregation, granularity))
return name + '_v%s' % version if version else name
def _object_exists(self, name):
try:
self.ioctx.stat(name)
return True
except rados.ObjectNotFound:
return False
def _create_metric(self, metric):
name = "gnocchi_%s_container" % metric.id
if self._object_exists(name):
raise storage.MetricAlreadyExists(metric)
else:
self.ioctx.write_full(name, "metric created")
def _store_metric_measures(self, metric, timestamp_key, aggregation,
granularity, data, offset=None, version=3):
name = self._get_object_name(metric, timestamp_key,
aggregation, granularity, version)
if offset is None:
self.ioctx.write_full(name, data)
else:
self.ioctx.write(name, data, offset=offset)
self.ioctx.set_xattr("gnocchi_%s_container" % metric.id, name, "")
def _delete_metric_measures(self, metric, timestamp_key, aggregation,
granularity, version=3):
name = self._get_object_name(metric, timestamp_key,
aggregation, granularity, version)
self.ioctx.rm_xattr("gnocchi_%s_container" % metric.id, name)
self.ioctx.aio_remove(name)
def _delete_metric(self, metric):
try:
xattrs = self.ioctx.get_xattrs("gnocchi_%s_container" % metric.id)
except rados.ObjectNotFound:
pass
else:
for xattr, _ in xattrs:
self.ioctx.aio_remove(xattr)
for name in ('container', 'none'):
self.ioctx.aio_remove("gnocchi_%s_%s" % (metric.id, name))
def _get_measures(self, metric, timestamp_key, aggregation, granularity,
version=3):
try:
name = self._get_object_name(metric, timestamp_key,
aggregation, granularity, version)
return self._get_object_content(name)
except rados.ObjectNotFound:
if self._object_exists("gnocchi_%s_container" % metric.id):
raise storage.AggregationDoesNotExist(metric, aggregation)
else:
raise storage.MetricDoesNotExist(metric)
def _list_split_keys_for_metric(self, metric, aggregation, granularity,
version=None):
try:
xattrs = self.ioctx.get_xattrs("gnocchi_%s_container" % metric.id)
except rados.ObjectNotFound:
raise storage.MetricDoesNotExist(metric)
keys = set()
for xattr, value in xattrs:
meta = xattr.split('_')
if (aggregation == meta[3] and granularity == float(meta[4]) and
self._version_check(xattr, version)):
keys.add(meta[2])
return keys
@staticmethod
def _build_unaggregated_timeserie_path(metric, version):
return (('gnocchi_%s_none' % metric.id)
+ ("_v%s" % version if version else ""))
def _get_unaggregated_timeserie(self, metric, version=3):
try:
return self._get_object_content(
self._build_unaggregated_timeserie_path(metric, version))
except rados.ObjectNotFound:
raise storage.MetricDoesNotExist(metric)
def _store_unaggregated_timeserie(self, metric, data, version=3):
self.ioctx.write_full(
self._build_unaggregated_timeserie_path(metric, version), data)
def _delete_unaggregated_timeserie(self, metric, version=3):
self.ioctx.aio_remove(
self._build_unaggregated_timeserie_path(metric, version))
def _get_object_content(self, name):
offset = 0
content = b''
while True:
data = self.ioctx.read(name, offset=offset)
if not data:
break
content += data
offset += len(data)
return content
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