def PercentageDistribution(
name, num_buckets=1000, reset_after=False,
description=None, field_spec=_MISSING):
"""Returns a metric handle for a cumulative distribution for percentage.
The distribution handle returned by this method is better suited for reporting
percentage values than the default one. The bucketing is optimized for values
in [0,100].
Args:
name: The name of this metric.
num_buckets: This metric buckets the percentage values before
reporting. This argument controls the number of the bucket the range
[0,100] is divided in. The default gives you 0.1% resolution.
reset_after: Should the metric be reset after reporting.
description: A string description of the metric.
field_spec: A sequence of ts_mon.Field objects to specify the field schema.
"""
# The last bucket actually covers [100, 100 + 1.0/num_buckets), so it
# corresponds to values that exactly match 100%.
bucket_width = 100 / num_buckets
b = ts_mon.FixedWidthBucketer(bucket_width, num_buckets)
return ts_mon.CumulativeDistributionMetric(
name, bucketer=b,
description=description, field_spec=field_spec)
def _BatchAndSendSpans(project_id, client, batch_sequence):
"""Batches and sends spans to the cloud trace API.
Args:
project_id: The Google Cloud project id
client: The google python api client
batch_sequence: An iterable of Span batches represented as JSON objects.
"""
batch_size_metric = metrics.CumulativeDistribution(
_BATCH_SIZE_METRIC,
description="The size of batches emitted by export_to_cloud_trace",
bucketer=ts_mon.FixedWidthBucketer(1, MIN_BATCH_SIZE * 2),
field_spec=None)
for batch in _ImpatientlyRebatched(batch_sequence, MIN_BATCH_SIZE,
BATCH_PATIENCE):
batch_size_metric.add(len(batch))
traces = []
groups = _GroupBy(batch, key=lambda span: span.get('traceId'))
for trace_id, spans in groups:
traces.append({
'traceId': trace_id,
'projectId': project_id,
'spans': spans
})
if traces:
client.projects().patchTraces(projectId=project_id,
body={'traces': traces})
def CumulativeSmallIntegerDistribution(name, reset_after=False):
"""Returns a metric handle for a cumulative distribution named |name|.
This differs slightly from CumulativeDistribution, in that the underlying
metric uses a uniform bucketer rather than a geometric one.
This metric type is suitable for holding a distribution of numbers that are
nonnegative integers in the range of 0 to 100.
"""
return ts_mon.CumulativeDistributionMetric(
name, bucketer=ts_mon.FixedWidthBucketer(1))
ts_mon.StringField('builder'),
ts_mon.StringField('master'),
ts_mon.StringField('project_id'),
ts_mon.StringField('result'),
ts_mon.StringField('slave'),
ts_mon.StringField('step_name'),
ts_mon.StringField('subproject_tag'),
]
step_durations = ts_mon.CumulativeDistributionMetric(
'buildbot/master/builders/steps/durations',
'Time (in seconds) from step start to step end',
step_field_spec,
units=ts_mon.MetricsDataUnits.SECONDS,
# Use fixed-width bucketer up to 2.7 hours with 10-second precision.
bucketer=ts_mon.FixedWidthBucketer(10, 1000))
step_counts = ts_mon.CounterMetric(
'buildbot/master/builders/steps/count',
'Count of step results, per builder and step',
step_field_spec)
field_spec = [
ts_mon.StringField('builder'),
ts_mon.StringField('master'),
ts_mon.StringField('project_id'),
ts_mon.StringField('result'),
ts_mon.StringField('slave'),
ts_mon.StringField('subproject_id'),
]