9073f7591e
When trying to upload volume to glance as image, currently all the format transformation is done by software and the performance is not good. Leverage hardware accelerator to do the image compression, so as to offload CPU, release CPU to do more common and complex thing. Professional hardware accelerator will get better performance and shorter conversion time than software solution. Currently hardware accelerator is getting more popular and some are integrated in server chipset by default. This patch includes: 1. Uses the new image container_format 'compressed' introduced by Glance in the Train release 2. Implemented a simple framework: if there's an accelerator detected in system, then try to use it 3. Supported Intel QAT as one of the accelerator 4. Add command filter for command 'qzip' and 'gzip' in rootwrap 5. New configuration option 'allow_compression_on_image_upload' and 'compression_format' added 6. Releasenote added Change-Id: I8460f58d2ad95a6654cf4d6a6bb367f3c537536b Implements: blueprint leverage-compression-accelerator Signed-off-by: Liang Fang <liang.a.fang@intel.com>
106 lines
3.0 KiB
Python
106 lines
3.0 KiB
Python
#
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# Licensed under the Apache License, Version 2.0 (the "License"); you may
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# not use this file except in compliance with the License. You may obtain
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# 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, WITHOUT
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# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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# License for the specific language governing permissions and limitations
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# under the License.
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import abc
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from oslo_config import cfg
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from oslo_log import log as logging
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from oslo_utils import importutils
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import six
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from cinder import exception
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from cinder.i18n import _
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LOG = logging.getLogger(__name__)
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CONF = cfg.CONF
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# NOTE(ZhengMa): The order of the option is improtant, accelerators
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# are looked by this list order
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# Be careful to edit it
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_ACCEL_PATH_PREFERENCE_ORDER_LIST = [
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'cinder.image.accelerators.qat.AccelQAT',
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'cinder.image.accelerators.gzip.AccelGZIP',
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]
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@six.add_metaclass(abc.ABCMeta)
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class AccelBase(object):
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def __init__(self):
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return
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@abc.abstractmethod
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def is_accel_exist(self):
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return
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@abc.abstractmethod
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def compress_img(self, run_as_root):
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return
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@abc.abstractmethod
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def decompress_img(self, run_as_root):
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return
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class ImageAccel(object):
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def __init__(self, src, dest):
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self.src = src
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self.dest = dest
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self.compression_format = CONF.compression_format
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if(self.compression_format == 'gzip'):
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self._accel_engine_path = _ACCEL_PATH_PREFERENCE_ORDER_LIST
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else:
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self._accel_engine_path = None
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self.engine = self._get_engine()
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def _get_engine(self, *args, **kwargs):
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if self._accel_engine_path:
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for accel in self._accel_engine_path:
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engine_cls = importutils.import_class(accel)
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eng = engine_cls(*args, **kwargs)
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if eng.is_accel_exist():
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return eng
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ex_msg = _("No valid accelerator")
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raise exception.CinderException(ex_msg)
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def is_engine_ready(self):
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if not self.engine:
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return False
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if not self.engine.is_accel_exist():
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return False
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return True
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def compress_img(self, run_as_root):
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if not self.is_engine_ready():
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return
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self.engine.compress_img(self.src,
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self.dest,
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run_as_root)
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def decompress_img(self, run_as_root):
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if not self.is_engine_ready():
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return
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self.engine.decompress_img(self.src,
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self.dest,
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run_as_root)
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def is_gzip_compressed(image_file):
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# The first two bytes of a gzip file are: 1f 8b
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GZIP_MAGIC_BYTES = b'\x1f\x8b'
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with open(image_file, 'rb') as f:
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return f.read(2) == GZIP_MAGIC_BYTES
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