def test_export_exemplar(self):
metric = _create_metric(
metric_descriptor.MetricDescriptorType.CUMULATIVE_DISTRIBUTION,
points=[
point.Point(value=_create_distribution_value(
bounds=[1],
buckets=[
value.Bucket(count=1,
exemplar=value.Exemplar(
value=2.5,
timestamp=TEST_TIME_STR,
attachments={'key1': 'value1'})),
value.Bucket(count=0),
]),
timestamp=datetime.now())
])
handler = mock.Mock(spec=ocagent.ExportRpcHandler)
ocagent.StatsExporter(handler).export_metrics([metric])
self.assertEqual(
handler.send.call_args[0][0].metrics[0].timeseries[0].points[0].
distribution_value.buckets[0].exemplar,
metrics_pb2.DistributionValue.Exemplar(
value=2.5,
timestamp=timestamp_pb2.Timestamp(seconds=1545699723,
nanos=4000),
attachments={'key1': 'value1'}))
def test_export_double_point_value(self):
view = view_module.View('', '', [FRONTEND_KEY], VIDEO_SIZE_MEASURE,
aggregation_module.SumAggregation())
v_data = view_data_module.ViewData(view=view,
start_time=TEST_TIME_STR,
end_time=TEST_TIME_STR)
v_data.record(context=tag_map_module.TagMap(),
value=2.5,
timestamp=None)
view_data = [v_data]
view_data = [metric_utils.view_data_to_metric(view_data[0], TEST_TIME)]
handler = mock.Mock(spec=ocagent.ExportRpcHandler)
ocagent.StatsExporter(handler).export_metrics(view_data)
self.assertEqual(
handler.send.call_args[0]
[0].metrics[0].timeseries[0].points[0].double_value, 2.5)
def test_export_view_data(self):
v_data = view_data_module.ViewData(view=VIDEO_SIZE_VIEW,
start_time=TEST_TIME_STR,
end_time=TEST_TIME_STR)
v_data.record(context=tag_map_module.TagMap(), value=2, timestamp=None)
view_data = [v_data]
view_data = [metric_utils.view_data_to_metric(view_data[0], TEST_TIME)]
handler = mock.Mock(spec=ocagent.ExportRpcHandler)
ocagent.StatsExporter(handler).export_metrics(view_data)
self.assertEqual(
handler.send.call_args[0][0].metrics[0].metric_descriptor,
metrics_pb2.MetricDescriptor(
name=VIDEO_SIZE_VIEW_NAME,
description='processed video size over time',
unit='By',
type=metrics_pb2.MetricDescriptor.CUMULATIVE_DISTRIBUTION,
label_keys=[metrics_pb2.LabelKey(key=FRONTEND_KEY)]))
self.assertEqual(
handler.send.call_args[0][0].metrics[0].timeseries[0],
metrics_pb2.TimeSeries(
start_timestamp=timestamp_pb2.Timestamp(seconds=1545699723,
nanos=4000),
label_values=[metrics_pb2.LabelValue(has_value=False)],
points=[
metrics_pb2.Point(
timestamp=timestamp_pb2.Timestamp(seconds=1545699723,
nanos=4000),
distribution_value=metrics_pb2.DistributionValue(
sum=2,
count=1,
bucket_options=metrics_pb2.DistributionValue.
BucketOptions(
explicit=metrics_pb2.DistributionValue.
BucketOptions.Explicit(
bounds=[16.0 * MiB, 256.0 * MiB])),
buckets=[
metrics_pb2.DistributionValue.Bucket(count=1),
metrics_pb2.DistributionValue.Bucket(),
metrics_pb2.DistributionValue.Bucket(),
]))
]))