opentelemetry_sdk/metrics/internal/
sum.rs

use crate::metrics::data::{self, Aggregation, SumDataPoint};
use crate::metrics::Temporality;
use opentelemetry::KeyValue;

use super::aggregate::{AggregateTimeInitiator, AttributeSetFilter};
use super::{Aggregator, AtomicTracker, ComputeAggregation, Measure, Number};
use super::{AtomicallyUpdate, ValueMap};

struct Increment<T>
where
    T: AtomicallyUpdate<T>,
{
    value: T::AtomicTracker,
}

impl<T> Aggregator for Increment<T>
where
    T: Number,
{
    type InitConfig = ();
    type PreComputedValue = T;

    fn create(_init: &()) -> Self {
        Self {
            value: T::new_atomic_tracker(T::default()),
        }
    }

    fn update(&self, value: T) {
        self.value.add(value)
    }

    fn clone_and_reset(&self, _: &()) -> Self {
        Self {
            value: T::new_atomic_tracker(self.value.get_and_reset_value()),
        }
    }
}

/// Summarizes a set of measurements made as their arithmetic sum.
pub(crate) struct Sum<T: Number> {
    value_map: ValueMap<Increment<T>>,
    init_time: AggregateTimeInitiator,
    temporality: Temporality,
    filter: AttributeSetFilter,
    monotonic: bool,
}

impl<T: Number> Sum<T> {
    /// Returns an aggregator that summarizes a set of measurements as their
    /// arithmetic sum.
    ///
    /// Each sum is scoped by attributes and the aggregation cycle the measurements
    /// were made in.
    pub(crate) fn new(
        temporality: Temporality,
        filter: AttributeSetFilter,
        monotonic: bool,
    ) -> Self {
        Sum {
            value_map: ValueMap::new(()),
            init_time: AggregateTimeInitiator::default(),
            temporality,
            filter,
            monotonic,
        }
    }

    pub(crate) fn delta(
        &self,
        dest: Option<&mut dyn Aggregation>,
    ) -> (usize, Option<Box<dyn Aggregation>>) {
        let time = self.init_time.delta();
        let s_data = dest.and_then(|d| d.as_mut().downcast_mut::<data::Sum<T>>());
        let mut new_agg = if s_data.is_none() {
            Some(data::Sum {
                data_points: vec![],
                start_time: time.start,
                time: time.current,
                temporality: Temporality::Delta,
                is_monotonic: self.monotonic,
            })
        } else {
            None
        };
        let s_data = s_data.unwrap_or_else(|| new_agg.as_mut().expect("present if s_data is none"));
        s_data.start_time = time.start;
        s_data.time = time.current;
        s_data.temporality = Temporality::Delta;
        s_data.is_monotonic = self.monotonic;

        self.value_map
            .collect_and_reset(&mut s_data.data_points, |attributes, aggr| SumDataPoint {
                attributes,
                value: aggr.value.get_value(),
                exemplars: vec![],
            });

        (
            s_data.data_points.len(),
            new_agg.map(|a| Box::new(a) as Box<_>),
        )
    }

    pub(crate) fn cumulative(
        &self,
        dest: Option<&mut dyn Aggregation>,
    ) -> (usize, Option<Box<dyn Aggregation>>) {
        let time = self.init_time.cumulative();
        let s_data = dest.and_then(|d| d.as_mut().downcast_mut::<data::Sum<T>>());
        let mut new_agg = if s_data.is_none() {
            Some(data::Sum {
                data_points: vec![],
                start_time: time.start,
                time: time.current,
                temporality: Temporality::Cumulative,
                is_monotonic: self.monotonic,
            })
        } else {
            None
        };
        let s_data = s_data.unwrap_or_else(|| new_agg.as_mut().expect("present if s_data is none"));

        s_data.start_time = time.start;
        s_data.time = time.current;
        s_data.temporality = Temporality::Cumulative;
        s_data.is_monotonic = self.monotonic;

        self.value_map
            .collect_readonly(&mut s_data.data_points, |attributes, aggr| SumDataPoint {
                attributes,
                value: aggr.value.get_value(),
                exemplars: vec![],
            });

        (
            s_data.data_points.len(),
            new_agg.map(|a| Box::new(a) as Box<_>),
        )
    }
}

impl<T> Measure<T> for Sum<T>
where
    T: Number,
{
    fn call(&self, measurement: T, attrs: &[KeyValue]) {
        self.filter.apply(attrs, |filtered| {
            self.value_map.measure(measurement, filtered);
        })
    }
}

impl<T> ComputeAggregation for Sum<T>
where
    T: Number,
{
    fn call(&self, dest: Option<&mut dyn Aggregation>) -> (usize, Option<Box<dyn Aggregation>>) {
        match self.temporality {
            Temporality::Delta => self.delta(dest),
            _ => self.cumulative(dest),
        }
    }
}
opentelemetry_sdk/metrics/internal/sum.rs

opentelemetry_sdk/metrics/internal/
sum.rs
