add flexible grouping key
all transformers will now require a grouping key. the pipeline will take grouping keys from all transformers in it's definition. using the set of keys, the values will be pulled from the datapoint, hashed, and sent to a pipeline. if no transformers are applied, samples will be grouped by resource_id and events will be grouped by event_type. Implement blueprint distributed-coordinated-notifications Change-Id: Ief462d19655c238e5951881a58e183084d37ac13
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003047bdb5
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@ -109,8 +109,9 @@ class NotificationService(service_base.BaseService):
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if cfg.CONF.notification.workload_partitioning:
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pipe_manager = pipeline.SamplePipelineTransportManager()
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for pipe in pipeline_manager.pipelines:
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key = pipeline.get_pipeline_grouping_key(pipe)
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pipe_manager.add_transporter(
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(pipe.source.support_meter,
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(pipe.source.support_meter, key or ['resource_id'],
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self._get_notifiers(transport, pipe)))
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else:
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pipe_manager = pipeline_manager
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@ -126,7 +127,7 @@ class NotificationService(service_base.BaseService):
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event_pipe_manager = pipeline.EventPipelineTransportManager()
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for pipe in self.event_pipeline_manager.pipelines:
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event_pipe_manager.add_transporter(
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(pipe.source.support_event,
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(pipe.source.support_event, ['event_type'],
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self._get_notifiers(transport, pipe)))
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else:
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event_pipe_manager = self.event_pipeline_manager
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@ -125,12 +125,19 @@ class _PipelineTransportManager(object):
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def __init__(self):
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self.transporters = []
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@staticmethod
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def hash_grouping(datapoint, grouping_keys):
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value = ''
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for key in grouping_keys or []:
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value += datapoint.get(key) if datapoint.get(key) else ''
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return hash(value)
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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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hash_grouping = self.hash_grouping
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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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@ -144,10 +151,11 @@ class _PipelineTransportManager(object):
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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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for d_filter, grouping_keys, 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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key = (hash_grouping(serialized_data,
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grouping_keys)
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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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@ -164,10 +172,6 @@ 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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@ -178,10 +182,6 @@ 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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@ -849,3 +849,10 @@ def setup_polling():
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"""Setup polling manager according to yaml config file."""
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cfg_file = cfg.CONF.pipeline_cfg_file
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return _setup_polling_manager(cfg_file)
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def get_pipeline_grouping_key(pipe):
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keys = []
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for transformer in pipe.sink.transformers:
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keys += transformer.grouping_keys
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return list(set(keys))
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@ -425,10 +425,50 @@ class TestRealNotificationHA(BaseRealNotification):
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mock_notifier.call_args_list[2][1]['event_type'])
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self.srv.stop()
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@mock.patch('ceilometer.publisher.test.TestPublisher')
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def test_multiple_agents(self, fake_publisher_cls):
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fake_publisher_cls.return_value = self.publisher
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class TestRealNotificationMultipleAgents(tests_base.BaseTestCase):
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def setup_pipeline(self, transformers):
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pipeline = yaml.dump({
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'sources': [{
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'name': 'test_pipeline',
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'interval': 5,
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'meters': ['instance', 'memory'],
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'sinks': ['test_sink']
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}],
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'sinks': [{
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'name': 'test_sink',
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'transformers': transformers,
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'publishers': ['test://']
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}]
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})
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if six.PY3:
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pipeline = pipeline.encode('utf-8')
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pipeline_cfg_file = fileutils.write_to_tempfile(content=pipeline,
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prefix="pipeline",
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suffix="yaml")
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return pipeline_cfg_file
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def setUp(self):
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super(TestRealNotificationMultipleAgents, self).setUp()
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self.CONF = self.useFixture(fixture_config.Config()).conf
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service.prepare_service([])
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self.setup_messaging(self.CONF, 'nova')
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pipeline_cfg_file = self.setup_pipeline(['instance', 'memory'])
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self.CONF.set_override("pipeline_cfg_file", pipeline_cfg_file)
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self.CONF.set_override("store_events", False, group="notification")
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self.CONF.set_override("disable_non_metric_meters", False,
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group="notification")
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self.CONF.set_override('workload_partitioning', True,
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group='notification')
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self.publisher = test_publisher.TestPublisher("")
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self.publisher2 = test_publisher.TestPublisher("")
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def _check_notifications(self, fake_publisher_cls):
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fake_publisher_cls.side_effect = [self.publisher, self.publisher2]
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self.srv = notification.NotificationService()
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self.srv2 = notification.NotificationService()
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with mock.patch('ceilometer.coordination.PartitionCoordinator'
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'._get_members', return_value=['harry', 'lloyd']):
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@ -448,17 +488,63 @@ class TestRealNotificationHA(BaseRealNotification):
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notifier.info(context.RequestContext(), 'compute.instance.create.end',
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payload2)
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self.expected_samples = 4
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self.expected_events = 2
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start = timeutils.utcnow()
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with mock.patch('six.moves.builtins.hash', lambda x: int(x)):
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while timeutils.delta_seconds(start, timeutils.utcnow()) < 60:
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if (len(self.publisher.samples) >= self.expected_samples and
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len(self.publisher.events) >= self.expected_events):
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if (len(self.publisher.samples + self.publisher2.samples) >=
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self.expected_samples):
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break
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eventlet.sleep(0)
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self.srv.stop()
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self.srv2.stop()
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resources = set(s.resource_id for s in self.publisher.samples)
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self.assertEqual(self.expected_samples, len(self.publisher.samples))
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self.assertEqual(self.expected_events, len(self.publisher.events))
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self.assertEqual(set(['1', '0']), resources)
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self.assertEqual(2, len(self.publisher.samples))
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self.assertEqual(2, len(self.publisher2.samples))
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self.assertEqual(1, len(set(
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s.resource_id for s in self.publisher.samples)))
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self.assertEqual(1, len(set(
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s.resource_id for s in self.publisher2.samples)))
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@mock.patch('ceilometer.publisher.test.TestPublisher')
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def test_multiple_agents_no_transform(self, fake_publisher_cls):
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pipeline_cfg_file = self.setup_pipeline([])
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self.CONF.set_override("pipeline_cfg_file", pipeline_cfg_file)
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self._check_notifications(fake_publisher_cls)
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@mock.patch('ceilometer.publisher.test.TestPublisher')
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def test_multiple_agents_transform(self, fake_publisher_cls):
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pipeline_cfg_file = self.setup_pipeline(
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[{
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'name': 'unit_conversion',
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'parameters': {
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'source': {},
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'target': {'name': 'cpu_mins',
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'unit': 'min',
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'scale': 'volume'},
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}
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}])
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self.CONF.set_override("pipeline_cfg_file", pipeline_cfg_file)
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self._check_notifications(fake_publisher_cls)
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@mock.patch('ceilometer.publisher.test.TestPublisher')
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def test_multiple_agents_multiple_transform(self, fake_publisher_cls):
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pipeline_cfg_file = self.setup_pipeline(
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[{
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'name': 'unit_conversion',
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'parameters': {
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'source': {},
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'target': {'name': 'cpu_mins',
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'unit': 'min',
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'scale': 'volume'},
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}
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}, {
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'name': 'unit_conversion',
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'parameters': {
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'source': {},
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'target': {'name': 'cpu_mins',
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'unit': 'min',
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'scale': 'volume'},
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}
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}])
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self.CONF.set_override("pipeline_cfg_file", pipeline_cfg_file)
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self._check_notifications(fake_publisher_cls)
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@ -86,6 +86,7 @@ class BasePipelineTestCase(base.BaseTestCase):
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class TransformerClass(transformer.TransformerBase):
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samples = []
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grouping_keys = ['counter_name']
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def __init__(self, append_name='_update'):
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self.__class__.samples = []
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@ -111,6 +112,7 @@ class BasePipelineTestCase(base.BaseTestCase):
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class TransformerClassDrop(transformer.TransformerBase):
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samples = []
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grouping_keys = ['resource_id']
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def __init__(self):
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self.__class__.samples = []
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@ -119,6 +121,8 @@ class BasePipelineTestCase(base.BaseTestCase):
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self.__class__.samples.append(counter)
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class TransformerClassException(object):
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grouping_keys = ['resource_id']
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@staticmethod
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def handle_sample(ctxt, counter):
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raise Exception()
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@ -1897,3 +1901,48 @@ class BasePipelineTestCase(base.BaseTestCase):
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def test_unique_pipeline_names(self):
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self._dup_pipeline_name_cfg()
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self._exception_create_pipelinemanager()
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def test_get_pipeline_grouping_key(self):
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transformer_cfg = [
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{
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'name': 'update',
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'parameters': {}
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},
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{
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'name': 'unit_conversion',
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'parameters': {
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'source': {},
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'target': {'name': 'cpu_mins',
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'unit': 'min',
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'scale': 'volume'},
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}
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},
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{
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'name': 'update',
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'parameters': {}
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},
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]
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self._set_pipeline_cfg('transformers', transformer_cfg)
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pipeline_manager = pipeline.PipelineManager(self.pipeline_cfg,
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self.transformer_manager)
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self.assertEqual(set(['resource_id', 'counter_name']),
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set(pipeline.get_pipeline_grouping_key(
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pipeline_manager.pipelines[0])))
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def test_get_pipeline_duplicate_grouping_key(self):
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transformer_cfg = [
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{
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'name': 'update',
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'parameters': {}
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},
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{
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'name': 'update',
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'parameters': {}
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},
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]
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self._set_pipeline_cfg('transformers', transformer_cfg)
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pipeline_manager = pipeline.PipelineManager(self.pipeline_cfg,
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self.transformer_manager)
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self.assertEqual(['counter_name'],
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pipeline.get_pipeline_grouping_key(
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pipeline_manager.pipelines[0]))
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:param sample: A sample.
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"""
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@abc.abstractproperty
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def grouping_keys(self):
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"""Keys used to group transformer."""
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def flush(self, context):
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"""Flush samples cached previously.
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@ -22,6 +22,8 @@ class TransformerAccumulator(transformer.TransformerBase):
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And then flushes them out into the wild.
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"""
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grouping_keys = ['resource_id']
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def __init__(self, size=1, **kwargs):
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if size >= 1:
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self.samples = []
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@ -35,6 +35,8 @@ class ArithmeticTransformer(transformer.TransformerBase):
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over one or more meters and/or their metadata.
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"""
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grouping_keys = ['resource_id']
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meter_name_re = re.compile(r'\$\(([\w\.\-]+)\)')
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def __init__(self, target=None, **kwargs):
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@ -30,6 +30,8 @@ LOG = log.getLogger(__name__)
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class ScalingTransformer(transformer.TransformerBase):
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"""Transformer to apply a scaling conversion."""
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grouping_keys = ['resource_id']
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def __init__(self, source=None, target=None, **kwargs):
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"""Initialize transformer with configured parameters.
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