// This Source Code Form is subject to the terms of the Mozilla Public // License, v. 2.0. If a copy of the MPL was not distributed with this // file, You can obtain one at https://mozilla.org/MPL/2.0/. use std::sync::Arc; use crate::common_metric_data::CommonMetricDataInternal; use crate::error_recording::{record_error, test_get_num_recorded_errors, ErrorType}; use crate::histogram::{Bucketing, Histogram, HistogramType}; use crate::metrics::{DistributionData, Metric, MetricType}; use crate::storage::StorageManager; use crate::CommonMetricData; use crate::Glean; /// A custom distribution metric. /// /// Memory distributions are used to accumulate and store memory sizes. #[derive(Clone, Debug)] pub struct CustomDistributionMetric { meta: Arc, range_min: u64, range_max: u64, bucket_count: u64, histogram_type: HistogramType, } /// Create a snapshot of the histogram. /// /// The snapshot can be serialized into the payload format. pub(crate) fn snapshot(hist: &Histogram) -> DistributionData { DistributionData { values: hist .snapshot_values() .into_iter() .map(|(k, v)| (k as i64, v as i64)) .collect(), sum: hist.sum() as i64, count: hist.count() as i64, } } impl MetricType for CustomDistributionMetric { fn meta(&self) -> &CommonMetricDataInternal { &self.meta } } // IMPORTANT: // // When changing this implementation, make sure all the operations are // also declared in the related trait in `../traits/`. impl CustomDistributionMetric { /// Creates a new memory distribution metric. pub fn new( meta: CommonMetricData, range_min: i64, range_max: i64, bucket_count: i64, histogram_type: HistogramType, ) -> Self { Self { meta: Arc::new(meta.into()), range_min: range_min as u64, range_max: range_max as u64, bucket_count: bucket_count as u64, histogram_type, } } /// Accumulates the provided signed samples in the metric. /// /// This is required so that the platform-specific code can provide us with /// 64 bit signed integers if no `u64` comparable type is available. This /// will take care of filtering and reporting errors for any provided negative /// sample. /// /// # Arguments /// /// - `samples` - The vector holding the samples to be recorded by the metric. /// /// ## Notes /// /// Discards any negative value in `samples` and report an [`ErrorType::InvalidValue`] /// for each of them. pub fn accumulate_samples(&self, samples: Vec) { let metric = self.clone(); crate::launch_with_glean(move |glean| metric.accumulate_samples_sync(glean, samples)) } /// Accumulates the provided sample in the metric synchronously. /// /// See [`accumulate_samples`](Self::accumulate_samples) for details. #[doc(hidden)] pub fn accumulate_samples_sync(&self, glean: &Glean, samples: Vec) { if !self.should_record(glean) { return; } let mut num_negative_samples = 0; // Generic accumulation function to handle the different histogram types and count negative // samples. fn accumulate( samples: &[i64], mut hist: Histogram, metric: F, ) -> (i32, Metric) where F: Fn(Histogram) -> Metric, { let mut num_negative_samples = 0; for &sample in samples.iter() { if sample < 0 { num_negative_samples += 1; } else { let sample = sample as u64; hist.accumulate(sample); } } (num_negative_samples, metric(hist)) } glean.storage().record_with(glean, &self.meta, |old_value| { let (num_negative, hist) = match self.histogram_type { HistogramType::Linear => { let hist = if let Some(Metric::CustomDistributionLinear(hist)) = old_value { hist } else { Histogram::linear( self.range_min, self.range_max, self.bucket_count as usize, ) }; accumulate(&samples, hist, Metric::CustomDistributionLinear) } HistogramType::Exponential => { let hist = if let Some(Metric::CustomDistributionExponential(hist)) = old_value { hist } else { Histogram::exponential( self.range_min, self.range_max, self.bucket_count as usize, ) }; accumulate(&samples, hist, Metric::CustomDistributionExponential) } }; num_negative_samples = num_negative; hist }); if num_negative_samples > 0 { let msg = format!("Accumulated {} negative samples", num_negative_samples); record_error( glean, &self.meta, ErrorType::InvalidValue, msg, num_negative_samples, ); } } /// Gets the currently stored histogram. #[doc(hidden)] pub fn get_value<'a, S: Into>>( &self, glean: &Glean, ping_name: S, ) -> Option { let queried_ping_name = ping_name .into() .unwrap_or_else(|| &self.meta().inner.send_in_pings[0]); match StorageManager.snapshot_metric_for_test( glean.storage(), queried_ping_name, &self.meta.identifier(glean), self.meta.inner.lifetime, ) { // Boxing the value, in order to return either of the possible buckets Some(Metric::CustomDistributionExponential(hist)) => Some(snapshot(&hist)), Some(Metric::CustomDistributionLinear(hist)) => Some(snapshot(&hist)), _ => None, } } /// **Test-only API (exported for FFI purposes).** /// /// Gets the currently stored value as an integer. /// /// This doesn't clear the stored value. pub fn test_get_value(&self, ping_name: Option) -> Option { crate::block_on_dispatcher(); crate::core::with_glean(|glean| self.get_value(glean, ping_name.as_deref())) } /// **Exported for test purposes.** /// /// Gets the number of recorded errors for the given metric and error type. /// /// # Arguments /// /// * `error` - The type of error /// * `ping_name` - represents the optional name of the ping to retrieve the /// metric for. inner to the first value in `send_in_pings`. /// /// # Returns /// /// The number of errors reported. pub fn test_get_num_recorded_errors(&self, error: ErrorType) -> i32 { crate::block_on_dispatcher(); crate::core::with_glean(|glean| { test_get_num_recorded_errors(glean, self.meta(), error).unwrap_or(0) }) } }