flink-python/pyflink/fn_execution/metrics/process/metric_impl.py

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import json
from enum import Enum
from typing import Callable, List, Tuple

from pyflink.fn_execution.metrics.process.counter_impl import CounterImpl
from pyflink.fn_execution.metrics.process.distribution_impl import DistributionImpl
from pyflink.fn_execution.metrics.process.meter_impl import MeterImpl
from pyflink.metrics import MetricGroup, Counter, Distribution, Meter


class MetricGroupType(Enum):
    """
    Indicate the type of MetricGroup.
    """
    generic = 0
    key = 1
    value = 2


class GenericMetricGroup(MetricGroup):

    def __init__(
            self,
            parent,
            name,
            metric_group_type=MetricGroupType.generic):
        self._parent = parent
        self._sub_groups = []
        self._name = name
        self._metric_group_type = metric_group_type
        self._flink_gauge = {}
        self._beam_gauge = {}

    def add_group(self, name: str, extra: str = None) -> 'MetricGroup':
        if extra is None:
            return self._add_group(name, MetricGroupType.generic)
        else:
            return self._add_group(name, MetricGroupType.key) \
                ._add_group(extra, MetricGroupType.value)

    def counter(self, name: str) -> 'Counter':
        from apache_beam.metrics.metric import Metrics
        return CounterImpl(Metrics.counter(self._get_namespace(), name))

    def gauge(self, name: str, obj: Callable[[], int]) -> None:
        from apache_beam.metrics.metric import Metrics
        self._flink_gauge[name] = obj
        self._beam_gauge[name] = Metrics.gauge(self._get_namespace(), name)

    def meter(self, name: str, time_span_in_seconds: int = 60) -> 'Meter':
        from apache_beam.metrics.metric import Metrics
        # There is no meter type in Beam, use counter to implement meter
        return MeterImpl(Metrics.counter(self._get_namespace(time_span_in_seconds), name))

    def distribution(self, name: str) -> 'Distribution':
        from apache_beam.metrics.metric import Metrics
        return DistributionImpl(Metrics.distribution(self._get_namespace(), name))

    def _add_group(self, name: str, metric_group_type: MetricGroupType) -> 'GenericMetricGroup':
        for group in self._sub_groups:
            if name == group._name and metric_group_type == group._metric_group_type:
                # we don't create same metric group repeatedly
                return group

        sub_group = GenericMetricGroup(
            self,
            name,
            metric_group_type)
        self._sub_groups.append(sub_group)
        return sub_group

    def _get_metric_group_names_and_types(self) -> Tuple[List[str], List[str]]:
        if self._name is None:
            return [], []
        else:
            names, types = self._parent._get_metric_group_names_and_types()
            names.append(self._name)
            types.append(str(self._metric_group_type))
            return names, types

    def _get_namespace(self, time=None) -> str:
        names, metric_group_type = self._get_metric_group_names_and_types()
        names.extend(metric_group_type)
        if time is not None:
            names.append(str(time))
        return json.dumps(names)