def _generate_proto():
"""Generate MetricsCollection for global_monitor.send()."""
proto = metrics_pb2.MetricsCollection()
error_count = 0
for target, metric, start_time, _, fields_values in state.store.get_all():
for fields, value in fields_values.iteritems():
if len(proto.data) >= METRICS_DATA_LENGTH_LIMIT:
yield proto
proto = metrics_pb2.MetricsCollection()
try:
metrics_pb = metrics_pb2.MetricsData()
metric.serialize_to(metrics_pb, start_time, fields, value, target)
except errors.MonitoringError:
error_count += 1
logging.exception('Failed to serialize a metric.')
continue
proto.data.add().CopyFrom(metrics_pb)
if len(proto.data) > 0:
yield proto
if error_count:
raise errors.MonitoringFailedToFlushAllMetricsError(error_count)
def _generate_proto():
"""Generate MetricsCollection for global_monitor.send()."""
proto = metrics_pb2.MetricsCollection()
for target, metric, start_time, _, fields_values in state.store.get_all():
for fields, value in fields_values.iteritems():
if len(proto.data) >= METRICS_DATA_LENGTH_LIMIT:
yield proto
proto = metrics_pb2.MetricsCollection()
metric.serialize_to(proto, start_time, fields, value, target)
if len(proto.data) > 0:
yield proto
def _wrap_proto(data):
"""Normalize MetricsData, list(MetricsData), and MetricsCollection.
Args:
input: A MetricsData, list of MetricsData, or a MetricsCollection.
Returns:
A MetricsCollection with the appropriate data attribute set.
"""
if isinstance(data, metrics_pb2.MetricsCollection):
ret = data
elif isinstance(data, list):
ret = metrics_pb2.MetricsCollection(data=data)
else:
ret = metrics_pb2.MetricsCollection(data=[data])
return ret
