e38ffd09e8
this patch enables a queue per pipeline per agent. each agent can send data to pipeline queue set of any agent but only listens to it's own pipeline queue. when receiving a notification, the agent will: 1. build datapoint 2. calculate hash key based on (hardcoded) attribute and mod hash by number of active agents 3. sends the data to single agents pipeline queue set. ex. two agents, sample1 with res_id=1 and sample2 with res_id=2 1. agent1 builds both samples 2. hash(sample1) % 2 (num agents) == agent1 sends sample to agent2 pipeline queue. 2a. agent2 process sample1 3. hash(sample2) % 2 (num agents) == agent1 sends sample to agent1 pipeline queue. 3a. agent1 process sample2 Implements blueprint distributed-coordinated-notifications Change-Id: Iab52cae0a5bfbc747a2918e67dfe8da5fd0fda84
834 lines
28 KiB
Python
834 lines
28 KiB
Python
#
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# Copyright 2013 Intel Corp.
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# Copyright 2014 Red Hat, Inc
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#
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# Authors: Yunhong Jiang <yunhong.jiang@intel.com>
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# Eoghan Glynn <eglynn@redhat.com>
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#
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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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import fnmatch
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import hashlib
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import os
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from oslo_config import cfg
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from oslo_log import log
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from oslo_utils import timeutils
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import six
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from stevedore import extension
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import yaml
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from ceilometer.event.storage import models
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from ceilometer.i18n import _
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from ceilometer import publisher
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from ceilometer.publisher import utils as publisher_utils
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from ceilometer import sample as sample_util
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OPTS = [
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cfg.StrOpt('pipeline_cfg_file',
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default="pipeline.yaml",
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help="Configuration file for pipeline definition."
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),
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cfg.StrOpt('event_pipeline_cfg_file',
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default="event_pipeline.yaml",
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help="Configuration file for event pipeline definition."
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),
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cfg.BoolOpt('refresh_pipeline_cfg',
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default=False,
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help="Refresh Pipeline configuration on-the-fly."
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),
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cfg.IntOpt('pipeline_polling_interval',
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default=20,
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help="Polling interval for pipeline file configuration"
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" in seconds."
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),
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]
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cfg.CONF.register_opts(OPTS)
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LOG = log.getLogger(__name__)
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class PipelineException(Exception):
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def __init__(self, message, pipeline_cfg):
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self.msg = message
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self.pipeline_cfg = pipeline_cfg
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def __str__(self):
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return 'Pipeline %s: %s' % (self.pipeline_cfg, self.msg)
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@six.add_metaclass(abc.ABCMeta)
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class PipelineEndpoint(object):
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def __init__(self, context, pipeline):
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self.publish_context = PublishContext(context, [pipeline])
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@abc.abstractmethod
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def sample(self, ctxt, publisher_id, event_type, payload, metadata):
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pass
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class SamplePipelineEndpoint(PipelineEndpoint):
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def sample(self, ctxt, publisher_id, event_type, payload, metadata):
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samples = [
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sample_util.Sample(name=s['counter_name'],
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type=s['counter_type'],
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unit=s['counter_unit'],
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volume=s['counter_volume'],
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user_id=s['user_id'],
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project_id=s['project_id'],
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resource_id=s['resource_id'],
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timestamp=s['timestamp'],
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resource_metadata=s['resource_metadata'],
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source=s.get('source'))
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for s in payload if publisher_utils.verify_signature(
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s, cfg.CONF.publisher.telemetry_secret)
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]
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with self.publish_context as p:
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p(samples)
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class EventPipelineEndpoint(PipelineEndpoint):
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def sample(self, ctxt, publisher_id, event_type, payload, metadata):
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events = [
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models.Event(
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message_id=ev['message_id'],
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event_type=ev['event_type'],
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generated=timeutils.normalize_time(
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timeutils.parse_isotime(ev['generated'])),
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traits=[models.Trait(name, dtype,
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models.Trait.convert_value(dtype, value))
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for name, dtype, value in ev['traits']],
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raw=ev.get('raw', {}))
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for ev in payload if publisher_utils.verify_signature(
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ev, cfg.CONF.publisher.telemetry_secret)
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]
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with self.publish_context as p:
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p(events)
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class _PipelineTransportManager(object):
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def __init__(self):
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self.transporters = []
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def add_transporter(self, transporter):
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self.transporters.append(transporter)
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def publisher(self, context):
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serializer = self.serializer
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hash_to_bucketise = self.hash_to_bucketise
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transporters = self.transporters
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filter_attr = self.filter_attr
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event_type = self.event_type
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class PipelinePublishContext(object):
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def __enter__(self):
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def p(data):
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# TODO(gordc): cleanup so payload is always single
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# datapoint. we can't correctly bucketise
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# datapoints if batched.
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data = [data] if not isinstance(data, list) else data
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for datapoint in data:
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serialized_data = serializer(datapoint)
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for d_filter, notifiers in transporters:
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if d_filter(serialized_data[filter_attr]):
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key = (hash_to_bucketise(serialized_data) %
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len(notifiers))
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notifier = notifiers[key]
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notifier.sample(context.to_dict(),
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event_type=event_type,
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payload=[serialized_data])
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return p
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def __exit__(self, exc_type, exc_value, traceback):
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pass
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return PipelinePublishContext()
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class SamplePipelineTransportManager(_PipelineTransportManager):
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filter_attr = 'counter_name'
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event_type = 'ceilometer.pipeline'
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@staticmethod
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def hash_to_bucketise(datapoint):
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return hash(datapoint['resource_id'])
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@staticmethod
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def serializer(data):
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return publisher_utils.meter_message_from_counter(
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data, cfg.CONF.publisher.telemetry_secret)
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class EventPipelineTransportManager(_PipelineTransportManager):
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filter_attr = 'event_type'
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event_type = 'pipeline.event'
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@staticmethod
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def hash_to_bucketise(datapoint):
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return hash(datapoint['event_type'])
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@staticmethod
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def serializer(data):
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return publisher_utils.message_from_event(
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data, cfg.CONF.publisher.telemetry_secret)
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class PublishContext(object):
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def __init__(self, context, pipelines=None):
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pipelines = pipelines or []
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self.pipelines = set(pipelines)
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self.context = context
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def add_pipelines(self, pipelines):
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self.pipelines.update(pipelines)
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def __enter__(self):
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def p(data):
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for p in self.pipelines:
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p.publish_data(self.context, data)
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return p
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def __exit__(self, exc_type, exc_value, traceback):
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for p in self.pipelines:
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p.flush(self.context)
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class Source(object):
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"""Represents a source of samples or events."""
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def __init__(self, cfg):
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self.cfg = cfg
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try:
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self.name = cfg['name']
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self.sinks = cfg.get('sinks')
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except KeyError as err:
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raise PipelineException(
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"Required field %s not specified" % err.args[0], cfg)
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def __str__(self):
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return self.name
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def check_sinks(self, sinks):
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if not self.sinks:
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raise PipelineException(
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"No sink defined in source %s" % self,
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self.cfg)
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for sink in self.sinks:
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if sink not in sinks:
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raise PipelineException(
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"Dangling sink %s from source %s" % (sink, self),
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self.cfg)
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def check_source_filtering(self, data, d_type):
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"""Source data rules checking
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- At least one meaningful datapoint exist
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- Included type and excluded type can't co-exist on the same pipeline
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- Included type meter and wildcard can't co-exist at same pipeline
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"""
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if not data:
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raise PipelineException('No %s specified' % d_type, self.cfg)
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if ([x for x in data if x[0] not in '!*'] and
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[x for x in data if x[0] == '!']):
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raise PipelineException(
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'Both included and excluded %s specified' % d_type,
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cfg)
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if '*' in data and [x for x in data if x[0] not in '!*']:
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raise PipelineException(
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'Included %s specified with wildcard' % d_type,
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self.cfg)
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@staticmethod
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def is_supported(dataset, data_name):
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# Support wildcard like storage.* and !disk.*
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# Start with negation, we consider that the order is deny, allow
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if any(fnmatch.fnmatch(data_name, datapoint[1:])
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for datapoint in dataset if datapoint[0] == '!'):
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return False
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if any(fnmatch.fnmatch(data_name, datapoint)
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for datapoint in dataset if datapoint[0] != '!'):
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return True
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# if we only have negation, we suppose the default is allow
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return all(datapoint.startswith('!') for datapoint in dataset)
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class EventSource(Source):
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"""Represents a source of events.
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In effect it is a set of notification handlers capturing events for a set
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of matching notifications.
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"""
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def __init__(self, cfg):
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super(EventSource, self).__init__(cfg)
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try:
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self.events = cfg['events']
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except KeyError as err:
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raise PipelineException(
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"Required field %s not specified" % err.args[0], cfg)
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self.check_source_filtering(self.events, 'events')
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def support_event(self, event_name):
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return self.is_supported(self.events, event_name)
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class SampleSource(Source):
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"""Represents a source of samples.
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In effect it is a set of pollsters and/or notification handlers emitting
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samples for a set of matching meters. Each source encapsulates meter name
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matching, polling interval determination, optional resource enumeration or
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discovery, and mapping to one or more sinks for publication.
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"""
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def __init__(self, cfg):
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super(SampleSource, self).__init__(cfg)
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try:
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# Support 'counters' for backward compatibility
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self.meters = cfg.get('meters', cfg.get('counters'))
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except KeyError as err:
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raise PipelineException(
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"Required field %s not specified" % err.args[0], cfg)
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try:
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self.interval = int(cfg.get('interval', 600))
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except ValueError:
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raise PipelineException("Invalid interval value", cfg)
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if self.interval <= 0:
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raise PipelineException("Interval value should > 0", cfg)
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self.resources = cfg.get('resources') or []
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if not isinstance(self.resources, list):
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raise PipelineException("Resources should be a list", cfg)
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self.discovery = cfg.get('discovery') or []
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if not isinstance(self.discovery, list):
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raise PipelineException("Discovery should be a list", cfg)
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self.check_source_filtering(self.meters, 'meters')
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def get_interval(self):
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return self.interval
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# (yjiang5) To support meters like instance:m1.tiny,
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# which include variable part at the end starting with ':'.
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# Hope we will not add such meters in future.
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@staticmethod
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def _variable_meter_name(name):
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m = name.partition(':')
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if m[1] == ':':
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return m[1].join((m[0], '*'))
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else:
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return name
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def support_meter(self, meter_name):
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meter_name = self._variable_meter_name(meter_name)
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return self.is_supported(self.meters, meter_name)
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class Sink(object):
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"""Represents a sink for the transformation and publication of data.
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Each sink config is concerned *only* with the transformation rules
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and publication conduits for data.
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In effect, a sink describes a chain of handlers. The chain starts
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with zero or more transformers and ends with one or more publishers.
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The first transformer in the chain is passed data from the
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corresponding source, takes some action such as deriving rate of
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change, performing unit conversion, or aggregating, before passing
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the modified data to next step.
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The subsequent transformers, if any, handle the data similarly.
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At the end of the chain, publishers publish the data. The exact
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publishing method depends on publisher type, for example, pushing
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into data storage via the message bus providing guaranteed delivery,
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or for loss-tolerant data UDP may be used.
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If no transformers are included in the chain, the publishers are
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passed data directly from the sink which are published unchanged.
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"""
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def __init__(self, cfg, transformer_manager):
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self.cfg = cfg
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try:
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self.name = cfg['name']
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# It's legal to have no transformer specified
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self.transformer_cfg = cfg.get('transformers') or []
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except KeyError as err:
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raise PipelineException(
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"Required field %s not specified" % err.args[0], cfg)
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if not cfg.get('publishers'):
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raise PipelineException("No publisher specified", cfg)
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self.publishers = []
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for p in cfg['publishers']:
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if '://' not in p:
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# Support old format without URL
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p = p + "://"
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try:
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self.publishers.append(publisher.get_publisher(p,
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self.NAMESPACE))
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except Exception:
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LOG.exception(_("Unable to load publisher %s"), p)
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self.transformers = self._setup_transformers(cfg, transformer_manager)
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def __str__(self):
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return self.name
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def _setup_transformers(self, cfg, transformer_manager):
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transformers = []
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for transformer in self.transformer_cfg:
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parameter = transformer['parameters'] or {}
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try:
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ext = transformer_manager[transformer['name']]
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except KeyError:
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raise PipelineException(
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"No transformer named %s loaded" % transformer['name'],
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cfg)
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transformers.append(ext.plugin(**parameter))
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LOG.info(_(
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"Pipeline %(pipeline)s: Setup transformer instance %(name)s "
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"with parameter %(param)s") % ({'pipeline': self,
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'name': transformer['name'],
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'param': parameter}))
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return transformers
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class EventSink(Sink):
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NAMESPACE = 'ceilometer.event.publisher'
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def publish_events(self, ctxt, events):
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if events:
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for p in self.publishers:
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try:
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p.publish_events(ctxt, events)
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except Exception:
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LOG.exception(_(
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"Pipeline %(pipeline)s: Continue after error "
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"from publisher %(pub)s") % ({'pipeline': self,
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'pub': p}))
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def flush(self, ctxt):
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"""Flush data after all events have been injected to pipeline."""
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pass
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class SampleSink(Sink):
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NAMESPACE = 'ceilometer.publisher'
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def _transform_sample(self, start, ctxt, sample):
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try:
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for transformer in self.transformers[start:]:
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sample = transformer.handle_sample(ctxt, sample)
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if not sample:
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LOG.debug(_(
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"Pipeline %(pipeline)s: Sample dropped by "
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"transformer %(trans)s") % ({'pipeline': self,
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'trans': transformer}))
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return
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return sample
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except Exception as err:
|
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# TODO(gordc): only use one log level.
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LOG.warning(_("Pipeline %(pipeline)s: "
|
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"Exit after error from transformer "
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"%(trans)s for %(smp)s") % ({'pipeline': self,
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'trans': transformer,
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'smp': sample}))
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LOG.exception(err)
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def _publish_samples(self, start, ctxt, samples):
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"""Push samples into pipeline for publishing.
|
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:param start: The first transformer that the sample will be injected.
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This is mainly for flush() invocation that transformer
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may emit samples.
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:param ctxt: Execution context from the manager or service.
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:param samples: Sample list.
|
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"""
|
|
|
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transformed_samples = []
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if not self.transformers:
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transformed_samples = samples
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else:
|
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for sample in samples:
|
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LOG.debug(_(
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"Pipeline %(pipeline)s: Transform sample "
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"%(smp)s from %(trans)s transformer") % ({'pipeline': self,
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'smp': sample,
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'trans': start}))
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sample = self._transform_sample(start, ctxt, sample)
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if sample:
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transformed_samples.append(sample)
|
|
|
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if transformed_samples:
|
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for p in self.publishers:
|
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try:
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p.publish_samples(ctxt, transformed_samples)
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except Exception:
|
|
LOG.exception(_(
|
|
"Pipeline %(pipeline)s: Continue after error "
|
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"from publisher %(pub)s") % ({'pipeline': self,
|
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'pub': p}))
|
|
|
|
def publish_samples(self, ctxt, samples):
|
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self._publish_samples(0, ctxt, samples)
|
|
|
|
def flush(self, ctxt):
|
|
"""Flush data after all samples have been injected to pipeline."""
|
|
|
|
for (i, transformer) in enumerate(self.transformers):
|
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try:
|
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self._publish_samples(i + 1, ctxt,
|
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list(transformer.flush(ctxt)))
|
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except Exception as err:
|
|
LOG.warning(_(
|
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"Pipeline %(pipeline)s: Error flushing "
|
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"transformer %(trans)s") % ({'pipeline': self,
|
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'trans': transformer}))
|
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LOG.exception(err)
|
|
|
|
|
|
@six.add_metaclass(abc.ABCMeta)
|
|
class Pipeline(object):
|
|
"""Represents a coupling between a sink and a corresponding source."""
|
|
|
|
def __init__(self, source, sink):
|
|
self.source = source
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|
self.sink = sink
|
|
self.name = str(self)
|
|
|
|
def __str__(self):
|
|
return (self.source.name if self.source.name == self.sink.name
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else '%s:%s' % (self.source.name, self.sink.name))
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|
|
|
def flush(self, ctxt):
|
|
self.sink.flush(ctxt)
|
|
|
|
@property
|
|
def publishers(self):
|
|
return self.sink.publishers
|
|
|
|
@abc.abstractmethod
|
|
def publish_data(self, ctxt, data):
|
|
"""Publish data from pipeline."""
|
|
|
|
|
|
class EventPipeline(Pipeline):
|
|
"""Represents a pipeline for Events."""
|
|
|
|
def __str__(self):
|
|
# NOTE(gordc): prepend a namespace so we ensure event and sample
|
|
# pipelines do not have the same name.
|
|
return 'event:%s' % super(EventPipeline, self).__str__()
|
|
|
|
def support_event(self, event_type):
|
|
return self.source.support_event(event_type)
|
|
|
|
def publish_data(self, ctxt, events):
|
|
if not isinstance(events, list):
|
|
events = [events]
|
|
supported = [e for e in events
|
|
if self.source.support_event(e.event_type)]
|
|
self.sink.publish_events(ctxt, supported)
|
|
|
|
|
|
class SamplePipeline(Pipeline):
|
|
"""Represents a pipeline for Samples."""
|
|
|
|
def get_interval(self):
|
|
return self.source.interval
|
|
|
|
@property
|
|
def resources(self):
|
|
return self.source.resources
|
|
|
|
@property
|
|
def discovery(self):
|
|
return self.source.discovery
|
|
|
|
def support_meter(self, meter_name):
|
|
return self.source.support_meter(meter_name)
|
|
|
|
def publish_data(self, ctxt, samples):
|
|
if not isinstance(samples, list):
|
|
samples = [samples]
|
|
supported = [s for s in samples if self.source.support_meter(s.name)]
|
|
self.sink.publish_samples(ctxt, supported)
|
|
|
|
|
|
SAMPLE_TYPE = {'pipeline': SamplePipeline,
|
|
'source': SampleSource,
|
|
'sink': SampleSink}
|
|
|
|
EVENT_TYPE = {'pipeline': EventPipeline,
|
|
'source': EventSource,
|
|
'sink': EventSink}
|
|
|
|
|
|
class PipelineManager(object):
|
|
"""Pipeline Manager
|
|
|
|
Pipeline manager sets up pipelines according to config file
|
|
|
|
Usually only one pipeline manager exists in the system.
|
|
|
|
"""
|
|
|
|
def __init__(self, cfg, transformer_manager, p_type=SAMPLE_TYPE):
|
|
"""Setup the pipelines according to config.
|
|
|
|
The configuration is supported as follows:
|
|
|
|
Decoupled: the source and sink configuration are separately
|
|
specified before being linked together. This allows source-
|
|
specific configuration, such as resource discovery, to be
|
|
kept focused only on the fine-grained source while avoiding
|
|
the necessity for wide duplication of sink-related config.
|
|
|
|
The configuration is provided in the form of separate lists
|
|
of dictionaries defining sources and sinks, for example:
|
|
|
|
{"sources": [{"name": source_1,
|
|
"interval": interval_time,
|
|
"meters" : ["meter_1", "meter_2"],
|
|
"resources": ["resource_uri1", "resource_uri2"],
|
|
"sinks" : ["sink_1", "sink_2"]
|
|
},
|
|
{"name": source_2,
|
|
"interval": interval_time,
|
|
"meters" : ["meter_3"],
|
|
"sinks" : ["sink_2"]
|
|
},
|
|
],
|
|
"sinks": [{"name": sink_1,
|
|
"transformers": [
|
|
{"name": "Transformer_1",
|
|
"parameters": {"p1": "value"}},
|
|
|
|
{"name": "Transformer_2",
|
|
"parameters": {"p1": "value"}},
|
|
],
|
|
"publishers": ["publisher_1", "publisher_2"]
|
|
},
|
|
{"name": sink_2,
|
|
"publishers": ["publisher_3"]
|
|
},
|
|
]
|
|
}
|
|
|
|
The interval determines the cadence of sample injection into
|
|
the pipeline where samples are produced under the direct control
|
|
of an agent, i.e. via a polling cycle as opposed to incoming
|
|
notifications.
|
|
|
|
Valid meter format is '*', '!meter_name', or 'meter_name'.
|
|
'*' is wildcard symbol means any meters; '!meter_name' means
|
|
"meter_name" will be excluded; 'meter_name' means 'meter_name'
|
|
will be included.
|
|
|
|
The 'meter_name" is Sample name field. For meter names with
|
|
variable like "instance:m1.tiny", it's "instance:*".
|
|
|
|
Valid meters definition is all "included meter names", all
|
|
"excluded meter names", wildcard and "excluded meter names", or
|
|
only wildcard.
|
|
|
|
The resources is list of URI indicating the resources from where
|
|
the meters should be polled. It's optional and it's up to the
|
|
specific pollster to decide how to use it.
|
|
|
|
Transformer's name is plugin name in setup.cfg.
|
|
|
|
Publisher's name is plugin name in setup.cfg
|
|
|
|
"""
|
|
self.pipelines = []
|
|
if not ('sources' in cfg and 'sinks' in cfg):
|
|
raise PipelineException("Both sources & sinks are required",
|
|
cfg)
|
|
LOG.info(_('detected decoupled pipeline config format'))
|
|
|
|
unique_names = set()
|
|
sources = []
|
|
for s in cfg.get('sources', []):
|
|
name = s.get('name')
|
|
if name in unique_names:
|
|
raise PipelineException("Duplicated source names: %s" %
|
|
name, self)
|
|
else:
|
|
unique_names.add(name)
|
|
sources.append(p_type['source'](s))
|
|
unique_names.clear()
|
|
|
|
sinks = {}
|
|
for s in cfg.get('sinks', []):
|
|
name = s.get('name')
|
|
if name in unique_names:
|
|
raise PipelineException("Duplicated sink names: %s" %
|
|
name, self)
|
|
else:
|
|
unique_names.add(name)
|
|
sinks[s['name']] = p_type['sink'](s, transformer_manager)
|
|
unique_names.clear()
|
|
|
|
for source in sources:
|
|
source.check_sinks(sinks)
|
|
for target in source.sinks:
|
|
pipe = p_type['pipeline'](source, sinks[target])
|
|
if pipe.name in unique_names:
|
|
raise PipelineException(
|
|
"Duplicate pipeline name: %s. Ensure pipeline"
|
|
" names are unique. (name is the source and sink"
|
|
" names combined)" % pipe.name, cfg)
|
|
else:
|
|
unique_names.add(pipe.name)
|
|
self.pipelines.append(pipe)
|
|
unique_names.clear()
|
|
|
|
def publisher(self, context):
|
|
"""Build a new Publisher for these manager pipelines.
|
|
|
|
:param context: The context.
|
|
"""
|
|
return PublishContext(context, self.pipelines)
|
|
|
|
|
|
class PollingManager(object):
|
|
"""Polling Manager
|
|
|
|
Polling manager sets up polling according to config file.
|
|
"""
|
|
|
|
def __init__(self, cfg):
|
|
"""Setup the polling according to config.
|
|
|
|
The configuration is the sources half of the Pipeline Config.
|
|
"""
|
|
self.sources = []
|
|
if not ('sources' in cfg and 'sinks' in cfg):
|
|
raise PipelineException("Both sources & sinks are required",
|
|
cfg)
|
|
LOG.info(_('detected decoupled pipeline config format'))
|
|
|
|
unique_names = set()
|
|
for s in cfg.get('sources', []):
|
|
name = s.get('name')
|
|
if name in unique_names:
|
|
raise PipelineException("Duplicated source names: %s" %
|
|
name, self)
|
|
else:
|
|
unique_names.add(name)
|
|
self.sources.append(SampleSource(s))
|
|
unique_names.clear()
|
|
|
|
|
|
def _setup_pipeline_manager(cfg_file, transformer_manager, p_type=SAMPLE_TYPE):
|
|
if not os.path.exists(cfg_file):
|
|
cfg_file = cfg.CONF.find_file(cfg_file)
|
|
|
|
LOG.debug(_("Pipeline config file: %s"), cfg_file)
|
|
|
|
with open(cfg_file) as fap:
|
|
data = fap.read()
|
|
|
|
pipeline_cfg = yaml.safe_load(data)
|
|
LOG.info(_("Pipeline config: %s"), pipeline_cfg)
|
|
|
|
return PipelineManager(pipeline_cfg,
|
|
transformer_manager or
|
|
extension.ExtensionManager(
|
|
'ceilometer.transformer',
|
|
), p_type)
|
|
|
|
|
|
def _setup_polling_manager(cfg_file):
|
|
if not os.path.exists(cfg_file):
|
|
cfg_file = cfg.CONF.find_file(cfg_file)
|
|
|
|
LOG.debug(_("Polling config file: %s"), cfg_file)
|
|
|
|
with open(cfg_file) as fap:
|
|
data = fap.read()
|
|
|
|
pipeline_cfg = yaml.safe_load(data)
|
|
LOG.info(_("Pipeline config: %s"), pipeline_cfg)
|
|
|
|
return PollingManager(pipeline_cfg)
|
|
|
|
|
|
def setup_event_pipeline(transformer_manager=None):
|
|
"""Setup event pipeline manager according to yaml config file."""
|
|
cfg_file = cfg.CONF.event_pipeline_cfg_file
|
|
return _setup_pipeline_manager(cfg_file, transformer_manager, EVENT_TYPE)
|
|
|
|
|
|
def setup_pipeline(transformer_manager=None):
|
|
"""Setup pipeline manager according to yaml config file."""
|
|
cfg_file = cfg.CONF.pipeline_cfg_file
|
|
return _setup_pipeline_manager(cfg_file, transformer_manager)
|
|
|
|
|
|
def _get_pipeline_cfg_file(p_type=SAMPLE_TYPE):
|
|
if p_type == EVENT_TYPE:
|
|
cfg_file = cfg.CONF.event_pipeline_cfg_file
|
|
else:
|
|
cfg_file = cfg.CONF.pipeline_cfg_file
|
|
|
|
if not os.path.exists(cfg_file):
|
|
cfg_file = cfg.CONF.find_file(cfg_file)
|
|
|
|
return cfg_file
|
|
|
|
|
|
def get_pipeline_mtime(p_type=SAMPLE_TYPE):
|
|
cfg_file = _get_pipeline_cfg_file(p_type)
|
|
return os.path.getmtime(cfg_file)
|
|
|
|
|
|
def get_pipeline_hash(p_type=SAMPLE_TYPE):
|
|
|
|
cfg_file = _get_pipeline_cfg_file(p_type)
|
|
with open(cfg_file) as fap:
|
|
data = fap.read()
|
|
if six.PY3:
|
|
data = data.encode('utf-8')
|
|
|
|
file_hash = hashlib.md5(data).hexdigest()
|
|
return file_hash
|
|
|
|
|
|
def setup_polling():
|
|
"""Setup polling manager according to yaml config file."""
|
|
cfg_file = cfg.CONF.pipeline_cfg_file
|
|
return _setup_polling_manager(cfg_file)
|