feat: Improve support for exponential histogram

examples/metrics-advanced/Cargo.toml

@@ -14,6 +14,6 @@ bench = false
 
 [dependencies]
 opentelemetry = { workspace = true, features = ["metrics"] }
-opentelemetry_sdk = { workspace = true }
+opentelemetry_sdk = { workspace = true, features = ["spec_unstable_metrics_views"] }
 opentelemetry-stdout = { workspace = true, features = ["metrics"] }
 tokio = { workspace = true, features = ["full"] }

examples/metrics-advanced/src/main.rs

@@ -1,6 +1,6 @@
 use opentelemetry::global;
 use opentelemetry::KeyValue;
-use opentelemetry_sdk::metrics::{Instrument, SdkMeterProvider, Stream, Temporality};
+use opentelemetry_sdk::metrics::{Aggregation, Instrument, SdkMeterProvider, Stream, Temporality};
 use opentelemetry_sdk::Resource;
 use std::error::Error;
 
@@ -33,6 +33,36 @@ fn init_meter_provider() -> opentelemetry_sdk::metrics::SdkMeterProvider {
         }
     };
 
+    // for example 3
+    // Unlike a regular OpenTelemetry histogram with fixed buckets, which can be
+    // specified explicitly, an exponential histogram calculates bucket widths
+    // automatically, growing them exponentially. The configuration is
+    // controlled by two parameters: max_size defines the maximum number of
+    // buckets, while max_scale adjusts the resolution, with higher values
+    // providing greater precision.
+    // If the minimum and maximum values are known in advance, a regular
+    // histogram is often the better choice. However, if the range of values is
+    // unpredictable e.g. may include extreme outliers, an exponential histogram
+    // is more suitable. A example is measuring packet round-trip time in a
+    // WLAN: while most packets return in milliseconds, some may occasionally
+    // take hundreds of milliseconds or even seconds.
+    // Details are in:
+    // https://opentelemetry.io/docs/specs/otel/metrics/data-model/#exponentialhistogram
+    let my_view_change_aggregation = |i: &Instrument| {
+        if i.name() == "my_third_histogram" {
+            Stream::builder()
+                .with_aggregation(Aggregation::Base2ExponentialHistogram {
+                    max_size: 10,
+                    max_scale: 5,
+                    record_min_max: true,
+                })
+                .build()
+                .ok()
+        } else {
+            None
+        }
+    };
+
     // Build exporter using Delta Temporality.
     let exporter = opentelemetry_stdout::MetricExporterBuilder::default()
         .with_temporality(Temporality::Delta)
@@ -47,6 +77,7 @@ fn init_meter_provider() -> opentelemetry_sdk::metrics::SdkMeterProvider {
         .with_resource(resource)
         .with_view(my_view_rename_and_unit)
         .with_view(my_view_change_cardinality)
+        .with_view(my_view_change_aggregation)
         .build();
     global::set_meter_provider(provider.clone());
     provider
@@ -112,6 +143,23 @@ async fn main() -> Result<(), Box<dyn Error + Send + Sync + 'static>> {
 
     histogram2.record(1.8, &[KeyValue::new("mykey1", "v7")]);
 
+    // Example 3 - Use exponential histogram.
+    let histogram3 = meter
+        .f64_histogram("my_third_histogram")
+        .with_description("My histogram example description")
+        .build();
+    histogram3.record(-1.3, &[KeyValue::new("mykey1", "myvalue1")]);
+    histogram3.record(-5.5, &[KeyValue::new("mykey1", "myvalue1")]);
+    // is intentionally at the boundary of bucket
+    histogram3.record(-4.0, &[KeyValue::new("mykey1", "myvalue1")]);
+    histogram3.record(7.5, &[KeyValue::new("mykey1", "myvalue1")]);
+    // Internally the exponential histogram puts values either into a list of
+    // negative buckets or a list of positive buckets. Based on the values which
+    // are added the buckets are adjusted automatically. E.g. depending if the
+    // next record is commented/uncommented, then exponential histogram will
+    // have a different scale.
+    histogram3.record(0.4, &[KeyValue::new("mykey1", "myvalue1")]);
+
     // Metrics are exported by default every 60 seconds when using stdout exporter,
     // however shutting down the MeterProvider here instantly flushes
     // the metrics, instead of waiting for the 60 sec interval.

opentelemetry-sdk/src/metrics/aggregation.rs

@@ -130,12 +130,12 @@ impl Aggregation {
             Aggregation::Base2ExponentialHistogram { max_scale, .. } => {
                 if *max_scale > EXPO_MAX_SCALE {
                     return Err(MetricError::Config(format!(
-                        "aggregation: exponential histogram: max scale ({max_scale}) is greater than 20",
+                        "aggregation: exponential histogram: max scale ({max_scale}) is greater than {}", EXPO_MAX_SCALE
                     )));
                 }
                 if *max_scale < EXPO_MIN_SCALE {
                     return Err(MetricError::Config(format!(
-                        "aggregation: exponential histogram: max scale ({max_scale}) is less than -10",
+                        "aggregation: exponential histogram: max scale ({max_scale}) is less than {}", EXPO_MIN_SCALE
                     )));
                 }
 

opentelemetry-stdout/CHANGELOG.md

@@ -2,6 +2,8 @@
 
 ## vNext
 
+- ExponentialHistogram supported in stdout
+
 ## 0.31.0
 
 Released 2025-Sep-25

opentelemetry-stdout/src/metrics/exporter.rs

@@ -6,8 +6,8 @@ use opentelemetry_sdk::{
     error::OTelSdkResult,
     metrics::{
         data::{
-            Gauge, GaugeDataPoint, Histogram, HistogramDataPoint, ResourceMetrics, ScopeMetrics,
-            Sum, SumDataPoint,
+            ExponentialHistogram, ExponentialHistogramDataPoint, Gauge, GaugeDataPoint, Histogram,
+            HistogramDataPoint, ResourceMetrics, ScopeMetrics, Sum, SumDataPoint,
         },
         exporter::PushMetricExporter,
     },
@@ -120,9 +120,9 @@ fn print_metrics<'a>(metrics: impl Iterator<Item = &'a ScopeMetrics>) {
                         println!("\t\tType         : Histogram");
                         print_histogram(hist);
                     }
-                    MetricData::ExponentialHistogram(_) => {
+                    MetricData::ExponentialHistogram(hist) => {
                         println!("\t\tType         : Exponential Histogram");
-                        // TODO: add support for ExponentialHistogram
+                        print_exponential_histogram(hist);
                     }
                 }
             }
@@ -193,6 +193,26 @@ fn print_histogram<T: Debug + Copy>(histogram: &Histogram<T>) {
     print_hist_data_points(histogram.data_points());
 }
 
+fn print_exponential_histogram<T: Debug + Copy>(histogram: &ExponentialHistogram<T>) {
+    if histogram.temporality() == Temporality::Cumulative {
+        println!("\t\tTemporality  : Cumulative");
+    } else {
+        println!("\t\tTemporality  : Delta");
+    }
+    let datetime: DateTime<Utc> = histogram.start_time().into();
+    println!(
+        "\t\tStartTime    : {}",
+        datetime.format("%Y-%m-%d %H:%M:%S%.6f")
+    );
+    let datetime: DateTime<Utc> = histogram.time().into();
+    println!(
+        "\t\tEndTime      : {}",
+        datetime.format("%Y-%m-%d %H:%M:%S%.6f")
+    );
+    println!("\t\tExponential Histogram DataPoints");
+    print_exponential_hist_data_points(histogram.data_points());
+}
+
 fn print_sum_data_points<'a, T: Debug + Copy + 'a>(
     data_points: impl Iterator<Item = &'a SumDataPoint<T>>,
 ) {
@@ -266,6 +286,70 @@ fn print_hist_data_points<'a, T: Debug + Copy + 'a>(
     }
 }
 
+fn print_exponential_hist_data_points<'a, T: Debug + Copy + 'a>(
+    data_points: impl Iterator<Item = &'a ExponentialHistogramDataPoint<T>>,
+) {
+    for (i, data_point) in data_points.enumerate() {
+        println!("\t\tDataPoint #{i}");
+        println!("\t\t\tCount          : {}", data_point.count());
+        println!("\t\t\tSum            : {:?}", data_point.sum());
+        if let Some(min) = &data_point.min() {
+            println!("\t\t\tMin            : {min:?}");
+        }
+
+        if let Some(max) = &data_point.max() {
+            println!("\t\t\tMax            : {max:?}");
+        }
+
+        let scale = data_point.scale();
+        let base = 2.0f64.powf(2.0f64.powf(-scale as f64));
+
+        println!("\t\t\tScale          : {}", scale);
+        println!("\t\t\tBase           : {:.3}", base);
+        println!("\t\t\tZeroCount      : {}", data_point.zero_count());
+        println!("\t\t\tZeroThreshold  : {}", data_point.zero_threshold());
+
+        println!("\t\t\tAttributes     :");
+        for kv in data_point.attributes() {
+            println!("\t\t\t\t ->  {}  : {}", kv.key, kv.value.as_str());
+        }
+
+        // Bucket upper-bounds are inclusive while bucket lower-bounds are
+        // exclusive. Details if a bound is including/excluding can be found in:
+        // https://opentelemetry.io/docs/specs/otel/metrics/data-model/#histogram-bucket-inclusivity
+
+        let negative_bucket = data_point.negative_bucket();
+        let negative_offset = negative_bucket.offset();
+        println!("\t\t\tNegativeOffset : {}", negative_offset);
+        for (i, count) in negative_bucket
+            .counts()
+            .collect::<Vec<_>>()
+            .into_iter()
+            .enumerate()
+            .rev()
+        {
+            let lower = -base.powf(i as f64 + negative_offset as f64 + 1.0f64);
+            let upper = -base.powf(i as f64 + negative_offset as f64);
+            println!(
+                "\t\t\t\t ->  Bucket {} ({:.3}, {:.3}] : {}",
+                i, lower, upper, count
+            );
+        }
+
+        let positive_bucket = data_point.positive_bucket();
+        let positive_offset = positive_bucket.offset();
+        println!("\t\t\tPositiveOffset : {}", positive_offset);
+        for (i, count) in positive_bucket.counts().enumerate() {
+            let lower = base.powf(i as f64 + positive_offset as f64);
+            let upper = base.powf(i as f64 + positive_offset as f64 + 1.0f64);
+            println!(
+                "\t\t\t\t ->  Bucket {} ({:.3}, {:.3}] : {}",
+                i, lower, upper, count
+            );
+        }
+    }
+}
+
 /// Configuration for the stdout metrics exporter
 #[derive(Default)]
 pub struct MetricExporterBuilder {