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# cython: language_level=3
# cython: profile=True
from __future__ import absolute_import
import time
from google.protobuf import timestamp_pb2
from apache_beam.metrics.cells import DistributionData
from apache_beam.metrics.cells import DistributionResult
from apache_beam.metrics.cells import GaugeData
from apache_beam.metrics.cells import GaugeResult
from apache_beam.portability import common_urns
from apache_beam.portability.api.beam_fn_api_pb2 import CounterData
from apache_beam.portability.api.beam_fn_api_pb2 import Metric
from apache_beam.portability.api.beam_fn_api_pb2 import MonitoringInfo
ELEMENT_COUNT_URN = common_urns.monitoring_infos.ELEMENT_COUNT.urn
START_BUNDLE_MSECS_URN = common_urns.monitoring_infos.START_BUNDLE_MSECS.urn
PROCESS_BUNDLE_MSECS_URN = common_urns.monitoring_infos.PROCESS_BUNDLE_MSECS.urn
FINISH_BUNDLE_MSECS_URN = common_urns.monitoring_infos.FINISH_BUNDLE_MSECS.urn
TOTAL_MSECS_URN = common_urns.monitoring_infos.TOTAL_MSECS.urn
USER_COUNTER_URN_PREFIX = (
common_urns.monitoring_infos.USER_COUNTER_URN_PREFIX.urn)
# TODO(ajamato): Implement the remaining types, i.e. Double types
# Extrema types, etc. See:
# https://s.apache.org/beam-fn-api-metrics
SUM_INT64_TYPE = common_urns.monitoring_info_types.SUM_INT64_TYPE.urn
DISTRIBUTION_INT64_TYPE = (
common_urns.monitoring_info_types.DISTRIBUTION_INT64_TYPE.urn)
LATEST_INT64_TYPE = common_urns.monitoring_info_types.LATEST_INT64_TYPE.urn
COUNTER_TYPES = set([SUM_INT64_TYPE])
DISTRIBUTION_TYPES = set([DISTRIBUTION_INT64_TYPE])
GAUGE_TYPES = set([LATEST_INT64_TYPE])
[docs]def to_timestamp_proto(timestamp_secs):
"""Converts seconds since epoch to a google.protobuf.Timestamp.
Args:
timestamp_secs: The timestamp in seconds since epoch.
"""
seconds = int(timestamp_secs)
nanos = int((timestamp_secs - seconds) * 10**9)
return timestamp_pb2.Timestamp(seconds=seconds, nanos=nanos)
[docs]def to_timestamp_secs(timestamp_proto):
"""Converts a google.protobuf.Timestamp to seconds since epoch.
Args:
timestamp_proto: The google.protobuf.Timestamp.
"""
return timestamp_proto.seconds + timestamp_proto.nanos * 10**-9
[docs]def create_labels(ptransform='', tag=''):
"""Create the label dictionary based on the provided tags.
Args:
ptransform: The ptransform/step name.
tag: he output tag name, used as a label.
"""
labels = {}
if tag:
labels['TAG'] = tag
if ptransform:
labels['PTRANSFORM'] = ptransform
return labels
[docs]def int64_counter(urn, metric, ptransform='', tag=''):
"""Return the counter monitoring info for the specifed URN, metric and labels.
Args:
urn: The URN of the monitoring info/metric.
metric: The metric proto field to use in the monitoring info.
Or an int value.
ptransform: The ptransform/step name used as a label.
tag: The output tag name, used as a label.
"""
labels = create_labels(ptransform=ptransform, tag=tag)
if isinstance(metric, int):
metric = Metric(
counter_data=CounterData(
int64_value=metric
)
)
return create_monitoring_info(urn, SUM_INT64_TYPE, metric, labels)
[docs]def int64_distribution(urn, metric, ptransform='', tag=''):
"""Return the distribution monitoring info for the URN, metric and labels.
Args:
urn: The URN of the monitoring info/metric.
metric: The metric proto field to use in the monitoring info.
Or an int value.
ptransform: The ptransform/step name used as a label.
tag: The output tag name, used as a label.
"""
labels = create_labels(ptransform=ptransform, tag=tag)
return create_monitoring_info(urn, DISTRIBUTION_INT64_TYPE, metric, labels)
[docs]def int64_gauge(urn, metric, ptransform='', tag=''):
"""Return the gauge monitoring info for the URN, metric and labels.
Args:
urn: The URN of the monitoring info/metric.
metric: The metric proto field to use in the monitoring info.
Or an int value.
ptransform: The ptransform/step name used as a label.
tag: The output tag name, used as a label.
"""
labels = create_labels(ptransform=ptransform, tag=tag)
return create_monitoring_info(urn, LATEST_INT64_TYPE, metric, labels)
[docs]def create_monitoring_info(urn, type_urn, metric_proto, labels=None):
"""Return the gauge monitoring info for the URN, type, metric and labels.
Args:
urn: The URN of the monitoring info/metric.
type_urn: The URN of the type of the monitoring info/metric.
i.e. beam:metrics:sum_int_64, beam:metrics:latest_int_64.
metric_proto: The metric proto field to use in the monitoring info.
Or an int value.
labels: The label dictionary to use in the MonitoringInfo.
"""
return MonitoringInfo(
urn=urn,
type=type_urn,
labels=labels or dict(),
metric=metric_proto,
timestamp=to_timestamp_proto(time.time())
)
[docs]def user_metric_urn(namespace, name):
"""Returns the metric URN for a user metric, with a proper URN prefix.
Args:
namespace: The namespace of the metric.
name: The name of the metric.
"""
return '%s%s:%s' % (USER_COUNTER_URN_PREFIX, namespace, name)
[docs]def is_counter(monitoring_info_proto):
"""Returns true if the monitoring info is a coutner metric."""
return monitoring_info_proto.type in COUNTER_TYPES
[docs]def is_distribution(monitoring_info_proto):
"""Returns true if the monitoring info is a distrbution metric."""
return monitoring_info_proto.type in DISTRIBUTION_TYPES
[docs]def is_gauge(monitoring_info_proto):
"""Returns true if the monitoring info is a gauge metric."""
return monitoring_info_proto.type in GAUGE_TYPES
[docs]def is_user_monitoring_info(monitoring_info_proto):
"""Returns true if the monitoring info is a user metric."""
return monitoring_info_proto.urn.startswith(USER_COUNTER_URN_PREFIX)
[docs]def parse_namespace_and_name(monitoring_info_proto):
"""Returns the (namespace, name) tuple of the URN in the monitoring info."""
to_split = monitoring_info_proto.urn
if is_user_monitoring_info(monitoring_info_proto):
# Remove the URN prefix which indicates that it is a user counter.
to_split = monitoring_info_proto.urn[len(USER_COUNTER_URN_PREFIX):]
# If it is not a user counter, just use the first part of the URN, i.e. 'beam'
split = to_split.split(':')
return split[0], ':'.join(split[1:])
[docs]def to_key(monitoring_info_proto):
"""Returns a key based on the URN and labels.
This is useful in maps to prevent reporting the same MonitoringInfo twice.
"""
key_items = [i for i in monitoring_info_proto.labels.items()]
key_items.append(monitoring_info_proto.urn)
return frozenset(key_items)