Fix merge conflicts and update since field

Author: lenin-jaganathan

implementations/micrometer-registry-otlp/src/main/java/io/micrometer/registry/otlp/HistogramFlavour.java

@@ -22,7 +22,7 @@
  * "https://github.com/open-telemetry/opentelemetry-specification/blob/main/specification/metrics/sdk_exporters/otlp.md#additional-configuration">OTLP
  * Configuration</a>
  * @author Lenin Jaganathan
- * @since 1.12.0
+ * @since 1.14.0
  */
 public enum HistogramFlavour {
 

implementations/micrometer-registry-otlp/src/main/java/io/micrometer/registry/otlp/OtlpConfig.java

@@ -215,7 +215,7 @@ default Map<String, String> headers() {
      * </p>
      * @return - histogram flavour to be used
      *
-     * @since 1.12.0
+     * @since 1.14.0
      */
     default HistogramFlavour histogramFlavour() {
         String histogramPreference = System.getenv().get("OTEL_EXPORTER_OTLP_METRICS_DEFAULT_HISTOGRAM_AGGREGATION");
@@ -231,7 +231,7 @@ default HistogramFlavour histogramFlavour() {
      * {@link io.micrometer.registry.otlp.internal.Base2ExponentialHistogram}
      * @return maxScale
      *
-     * @since 1.12.0
+     * @since 1.14.0
      */
     default int maxScale() {
         return getInteger(this, "maxScale").orElse(20);
@@ -242,7 +242,7 @@ default int maxScale() {
      * {@link io.micrometer.registry.otlp.internal.Base2ExponentialHistogram}
      * @return - maxBuckets
      *
-     * @since 1.12.0
+     * @since 1.14.0
      */
     default int maxBucketCount() {
         return getInteger(this, "maxBucketCount").orElse(160);

implementations/micrometer-registry-otlp/src/main/java/io/micrometer/registry/otlp/OtlpMeterRegistry.java

@@ -40,7 +40,6 @@
 import io.micrometer.core.ipc.http.HttpUrlConnectionSender;
 import io.micrometer.registry.otlp.internal.CumulativeBase2ExponentialHistogram;
 import io.micrometer.registry.otlp.internal.DeltaBase2ExponentialHistogram;
-import io.micrometer.registry.otlp.internal.ExponentialHistogramSnapShot;
 import io.opentelemetry.proto.collector.metrics.v1.ExportMetricsServiceRequest;
 import io.opentelemetry.proto.common.v1.AnyValue;
 import io.opentelemetry.proto.common.v1.KeyValue;
@@ -69,11 +68,6 @@ public class OtlpMeterRegistry extends PushMeterRegistry {
 
     private static final ThreadFactory DEFAULT_THREAD_FACTORY = new NamedThreadFactory("otlp-metrics-publisher");
 
-    private static final ExponentialHistogramDataPoint.Buckets EMPTY_EXPONETIAL_HISTOGRAM_BUCKETS = ExponentialHistogramDataPoint.Buckets
-        .newBuilder()
-        .addAllBucketCounts(Collections.emptyList())
-        .build();
-
     private static final double[] EMPTY_SLO_WITH_POSITIVE_INF = new double[] { Double.POSITIVE_INFINITY };
 
     private static final String TELEMETRY_SDK_NAME = "telemetry.sdk.name";
@@ -351,125 +345,6 @@ private long getInitialDelay() {
         return stepMillis - (clock.wallTime() % stepMillis) + 1;
     }
 
-    // VisibleForTesting
-    Metric writeHistogramSupport(HistogramSupport histogramSupport) {
-        Metric.Builder metricBuilder = getMetricBuilder(histogramSupport.getId());
-        boolean isTimeBased = histogramSupport instanceof Timer || histogramSupport instanceof LongTaskTimer;
-        HistogramSnapshot histogramSnapshot = histogramSupport.takeSnapshot();
-
-        Iterable<? extends KeyValue> tags = getTagsForId(histogramSupport.getId());
-        long startTimeNanos = getStartTimeNanos(histogramSupport);
-        double total = isTimeBased ? histogramSnapshot.total(getBaseTimeUnit()) : histogramSnapshot.total();
-        long count = histogramSnapshot.count();
-
-        // if percentiles configured, use summary
-        if (histogramSnapshot.percentileValues().length != 0) {
-            SummaryDataPoint.Builder summaryData = SummaryDataPoint.newBuilder()
-                .addAllAttributes(tags)
-                .setStartTimeUnixNano(startTimeNanos)
-                .setTimeUnixNano(getTimeUnixNano())
-                .setSum(total)
-                .setCount(count);
-            for (ValueAtPercentile percentile : histogramSnapshot.percentileValues()) {
-                summaryData.addQuantileValues(SummaryDataPoint.ValueAtQuantile.newBuilder()
-                    .setQuantile(percentile.percentile())
-                    .setValue(TimeUtils.convert(percentile.value(), TimeUnit.NANOSECONDS, getBaseTimeUnit())));
-            }
-            metricBuilder.setSummary(Summary.newBuilder().addDataPoints(summaryData));
-            return metricBuilder.build();
-        }
-
-        ExponentialHistogramSnapShot exponentialHistogramSnapShot = getExponentialHistogramSnapShot(histogramSupport);
-        if (exponentialHistogramSnapShot != null) {
-            ExponentialHistogramDataPoint.Builder exponentialDataPoint = ExponentialHistogramDataPoint.newBuilder()
-                .addAllAttributes(tags)
-                .setStartTimeUnixNano(startTimeNanos)
-                .setTimeUnixNano(getTimeUnixNano())
-                .setCount(count)
-                .setSum(total)
-                .setScale(exponentialHistogramSnapShot.scale())
-                .setZeroCount(exponentialHistogramSnapShot.zeroCount())
-                .setZeroThreshold(exponentialHistogramSnapShot.zeroThreshold())
-                .setPositive(ExponentialHistogramDataPoint.Buckets.newBuilder()
-                    .addAllBucketCounts(exponentialHistogramSnapShot.bucketsCount())
-                    .setOffset(exponentialHistogramSnapShot.offset())
-                    .build())
-                // Micrometer doesn't support negative recordings.
-                .setNegative(EMPTY_EXPONETIAL_HISTOGRAM_BUCKETS);
-
-            if (isDelta()) {
-                exponentialDataPoint
-                    .setMax(isTimeBased ? histogramSnapshot.max(getBaseTimeUnit()) : histogramSnapshot.max());
-            }
-
-            return metricBuilder
-                .setExponentialHistogram(ExponentialHistogram.newBuilder()
-                    .setAggregationTemporality(otlpAggregationTemporality)
-                    .addDataPoints(exponentialDataPoint)
-                    .build())
-                .build();
-        }
-
-        HistogramDataPoint.Builder histogramDataPoint = HistogramDataPoint.newBuilder()
-            .addAllAttributes(tags)
-            .setStartTimeUnixNano(startTimeNanos)
-            .setTimeUnixNano(getTimeUnixNano())
-            .setSum(total)
-            .setCount(count);
-
-        if (isDelta()) {
-            histogramDataPoint.setMax(isTimeBased ? histogramSnapshot.max(getBaseTimeUnit()) : histogramSnapshot.max());
-        }
-        // if histogram enabled, add histogram buckets
-        if (histogramSnapshot.histogramCounts().length != 0) {
-            for (CountAtBucket countAtBucket : histogramSnapshot.histogramCounts()) {
-                if (countAtBucket.bucket() != Double.POSITIVE_INFINITY) {
-                    // OTLP expects explicit bounds to not contain POSITIVE_INFINITY but
-                    // there should be a
-                    // bucket count representing values between last bucket and
-                    // POSITIVE_INFINITY.
-                    histogramDataPoint.addExplicitBounds(
-                            isTimeBased ? countAtBucket.bucket(getBaseTimeUnit()) : countAtBucket.bucket());
-                }
-                histogramDataPoint.addBucketCounts((long) countAtBucket.count());
-            }
-            metricBuilder.setHistogram(io.opentelemetry.proto.metrics.v1.Histogram.newBuilder()
-                .setAggregationTemporality(otlpAggregationTemporality)
-                .addDataPoints(histogramDataPoint));
-            return metricBuilder.build();
-        }
-
-        return metricBuilder
-            .setHistogram(io.opentelemetry.proto.metrics.v1.Histogram.newBuilder()
-                .setAggregationTemporality(otlpAggregationTemporality)
-                .addDataPoints(histogramDataPoint))
-            .build();
-    }
-
-    @Nullable
-    private static ExponentialHistogramSnapShot getExponentialHistogramSnapShot(
-            final HistogramSupport histogramSupport) {
-        if (histogramSupport instanceof OtlpHistogramSupport) {
-            return ((OtlpHistogramSupport) histogramSupport).getExponentialHistogramSnapShot();
-        }
-
-        return null;
-    }
-
-    // VisibleForTesting
-    Metric writeFunctionTimer(FunctionTimer functionTimer) {
-        return getMetricBuilder(functionTimer.getId())
-            .setHistogram(io.opentelemetry.proto.metrics.v1.Histogram.newBuilder()
-                .addDataPoints(HistogramDataPoint.newBuilder()
-                    .addAllAttributes(getTagsForId(functionTimer.getId()))
-                    .setStartTimeUnixNano(getStartTimeNanos((functionTimer)))
-                    .setTimeUnixNano(getTimeUnixNano())
-                    .setSum(functionTimer.totalTime(getBaseTimeUnit()))
-                    .setCount((long) functionTimer.count()))
-                .setAggregationTemporality(otlpAggregationTemporality))
-            .build();
-    }
-
     private boolean isCumulative() {
         return this.aggregationTemporality == AggregationTemporality.CUMULATIVE;
     }
@@ -516,14 +391,15 @@ static Histogram getHistogram(Clock clock, DistributionStatisticConfig distribut
 
     static Histogram getHistogram(final Clock clock, final DistributionStatisticConfig distributionStatisticConfig,
             final OtlpConfig otlpConfig, @Nullable final TimeUnit baseTimeUnit) {
-        // While publishing to OTLP, we export either Histogram datapoint (Explicit Bucket
+        // While publishing to OTLP, we export either Histogram datapoint (Explicit
+        // ExponentialBucket
         // or Exponential) / Summary
         // datapoint. So, we will make the histogram either of them and not both.
         // Though AbstractTimer/Distribution Summary prefers publishing percentiles,
         // exporting of histograms over percentiles is preferred in OTLP.
         if (distributionStatisticConfig.isPublishingHistogram()) {
-            if (histogramFlavour(otlpConfig.histogramFlavour(),
-                    distributionStatisticConfig) == HistogramFlavour.BASE2_EXPONENTIAL_BUCKET_HISTOGRAM) {
+            if (HistogramFlavour.BASE2_EXPONENTIAL_BUCKET_HISTOGRAM
+                .equals(histogramFlavour(otlpConfig.histogramFlavour(), distributionStatisticConfig))) {
                 Double minimumExpectedValue = distributionStatisticConfig.getMinimumExpectedValueAsDouble();
                 if (minimumExpectedValue == null) {
                     minimumExpectedValue = 0.0;

implementations/micrometer-registry-otlp/src/main/java/io/micrometer/registry/otlp/OtlpMetricConverter.java

@@ -24,6 +24,7 @@
 import io.micrometer.core.instrument.distribution.HistogramSupport;
 import io.micrometer.core.instrument.distribution.ValueAtPercentile;
 import io.micrometer.core.instrument.util.TimeUtils;
+import io.micrometer.registry.otlp.internal.ExponentialHistogramSnapShot;
 import io.opentelemetry.proto.common.v1.AnyValue;
 import io.opentelemetry.proto.common.v1.KeyValue;
 import io.opentelemetry.proto.metrics.v1.*;
@@ -122,16 +123,35 @@ private void writeHistogramSupport(HistogramSupport histogramSupport) {
         Iterable<KeyValue> tags = getKeyValuesForId(id);
         long startTimeNanos = getStartTimeNanos(histogramSupport);
         double total = isTimeBased ? histogramSnapshot.total(baseTimeUnit) : histogramSnapshot.total();
+        double max = isTimeBased ? histogramSnapshot.max(baseTimeUnit) : histogramSnapshot.max();
         long count = histogramSnapshot.count();
 
         // if percentiles configured, use summary
         if (histogramSnapshot.percentileValues().length != 0) {
             buildSummaryDataPoint(histogramSupport, tags, startTimeNanos, total, count, isTimeBased, histogramSnapshot);
+            return;
+        }
+
+        Optional<ExponentialHistogramSnapShot> exponentialHistogramSnapShot = getExponentialHistogramSnapShot(
+                histogramSupport);
+        if (exponentialHistogramSnapShot.isPresent()) {
+            buildExponentialHistogramDataPoint(histogramSupport, tags, startTimeNanos, total, max, count,
+                    exponentialHistogramSnapShot.get());
         }
         else {
-            buildHistogramDataPoint(histogramSupport, tags, startTimeNanos, total, count, isTimeBased,
+            buildHistogramDataPoint(histogramSupport, tags, startTimeNanos, total, max, count, isTimeBased,
                     histogramSnapshot);
         }
+
+    }
+
+    private static Optional<ExponentialHistogramSnapShot> getExponentialHistogramSnapShot(
+            final HistogramSupport histogramSupport) {
+        if (histogramSupport instanceof OtlpHistogramSupport) {
+            return Optional.ofNullable(((OtlpHistogramSupport) histogramSupport).getExponentialHistogramSnapShot());
+        }
+
+        return Optional.empty();
     }
 
     private void writeFunctionTimer(FunctionTimer functionTimer) {
@@ -151,7 +171,8 @@ private boolean isTimeBasedMeter(Meter.Id id) {
     }
 
     private void buildHistogramDataPoint(HistogramSupport histogramSupport, Iterable<KeyValue> tags,
-            long startTimeNanos, double total, long count, boolean isTimeBased, HistogramSnapshot histogramSnapshot) {
+            long startTimeNanos, double total, double max, long count, boolean isTimeBased,
+            HistogramSnapshot histogramSnapshot) {
         Metric.Builder metricBuilder = getOrCreateMetricBuilder(histogramSupport.getId(), DataCase.HISTOGRAM);
         HistogramDataPoint.Builder histogramDataPoint = HistogramDataPoint.newBuilder()
             .addAllAttributes(tags)
@@ -161,7 +182,7 @@ private void buildHistogramDataPoint(HistogramSupport histogramSupport, Iterable
             .setCount(count);
 
         if (isDelta()) {
-            histogramDataPoint.setMax(isTimeBased ? histogramSnapshot.max(baseTimeUnit) : histogramSnapshot.max());
+            histogramDataPoint.setMax(max);
         }
 
         // if histogram enabled, add histogram buckets
@@ -180,6 +201,37 @@ private void buildHistogramDataPoint(HistogramSupport histogramSupport, Iterable
         setHistogramDataPoint(metricBuilder, histogramDataPoint.build());
     }
 
+    private void buildExponentialHistogramDataPoint(HistogramSupport histogramSupport, Iterable<KeyValue> tags,
+            long startTimeNanos, double total, double max, long count,
+            ExponentialHistogramSnapShot exponentialHistogramSnapShot) {
+        Metric.Builder metricBuilder = getOrCreateMetricBuilder(histogramSupport.getId(),
+                DataCase.EXPONENTIAL_HISTOGRAM);
+        ExponentialHistogramDataPoint.Builder exponentialDataPoint = ExponentialHistogramDataPoint.newBuilder()
+            .addAllAttributes(tags)
+            .setStartTimeUnixNano(startTimeNanos)
+            .setTimeUnixNano(getTimeUnixNano())
+            .setCount(count)
+            .setSum(total)
+            .setScale(exponentialHistogramSnapShot.scale())
+            .setZeroCount(exponentialHistogramSnapShot.zeroCount())
+            .setZeroThreshold(exponentialHistogramSnapShot.zeroThreshold());
+
+        // Currently, micrometer doesn't support negative recordings hence we will only
+        // add positive buckets.
+        if (!exponentialHistogramSnapShot.positive().isEmpty()) {
+            exponentialDataPoint.setPositive(ExponentialHistogramDataPoint.Buckets.newBuilder()
+                .addAllBucketCounts(exponentialHistogramSnapShot.positive().bucketCounts())
+                .setOffset(exponentialHistogramSnapShot.positive().offset())
+                .build());
+        }
+
+        if (isDelta()) {
+            exponentialDataPoint.setMax(max);
+        }
+
+        setExponentialHistogramDataPoint(metricBuilder, exponentialDataPoint.build());
+    }
+
     private void buildSummaryDataPoint(HistogramSupport histogramSupport, Iterable<KeyValue> tags, long startTimeNanos,
             double total, long count, boolean isTimeBased, HistogramSnapshot histogramSnapshot) {
         Metric.Builder metricBuilder = getOrCreateMetricBuilder(histogramSupport.getId(), DataCase.SUMMARY);
@@ -220,6 +272,15 @@ private void setHistogramDataPoint(Metric.Builder builder, HistogramDataPoint hi
         builder.getHistogramBuilder().addDataPoints(histogramDataPoint);
     }
 
+    private void setExponentialHistogramDataPoint(Metric.Builder builder,
+            ExponentialHistogramDataPoint exponentialHistogramDataPoint) {
+        if (!builder.hasExponentialHistogram()) {
+            builder.setExponentialHistogram(
+                    ExponentialHistogram.newBuilder().setAggregationTemporality(otlpAggregationTemporality));
+        }
+        builder.getExponentialHistogramBuilder().addDataPoints(exponentialHistogramDataPoint);
+    }
+
     private void setSummaryDataPoint(Metric.Builder builder, SummaryDataPoint.Builder summaryDataPoint) {
         if (!builder.hasSummary()) {
             builder.setSummary(Summary.newBuilder());

implementations/micrometer-registry-otlp/src/main/java/io/micrometer/registry/otlp/internal/Base2ExponentialHistogram.java

@@ -15,6 +15,8 @@
  */
 package io.micrometer.registry.otlp.internal;
 
+import static io.micrometer.registry.otlp.internal.ExponentialHistogramSnapShot.ExponentialBucket.EMPTY_EXPONENTIAL_BUCKET;
+
 import java.util.Arrays;
 import java.util.Collections;
 import java.util.List;
@@ -26,17 +28,24 @@
 import io.micrometer.core.instrument.distribution.Histogram;
 import io.micrometer.core.instrument.distribution.HistogramSnapshot;
 import io.micrometer.core.instrument.util.TimeUtils;
+import io.micrometer.registry.otlp.internal.ExponentialHistogramSnapShot.ExponentialBucket;
 
 /**
  * A ExponentialHistogram implementation that compresses bucket boundaries using an
  * exponential formula (Base2 exponent), making it suitable for conveying high dynamic
  * range data with small relative error. This is an implementation of the <a href=
  * "https://github.com/open-telemetry/opentelemetry-specification/blob/main/specification/metrics/data-model.md#exponentialhistogram">Exponential
  * Histogram</a> as per the OTLP specification. The internal implementations uses the
- * techniques outlined in the OTLP specification mentioned above.
+ * techniques outlined in the OTLP specification mentioned above. This implementation
+ * supports only recording positive values (enforced by
+ * {@link io.micrometer.core.instrument.AbstractTimer#record(long, TimeUnit)}).
+ * <p>
+ * <strong> This is an internal class and might have breaking changes, external
+ * implementations SHOULD NOT rely on this implementation. </strong>
+ * </p>
  *
  * @author Lenin Jaganathan
- * @since 1.12.0
+ * @since 1.14.0
  */
 public abstract class Base2ExponentialHistogram implements Histogram {
 
@@ -115,8 +124,8 @@ public HistogramSnapshot takeSnapshot(final long count, final double total, fina
     ExponentialHistogramSnapShot getCurrentValuesSnapshot() {
         return (circularCountHolder.isEmpty() && zeroCount.longValue() == 0)
                 ? DefaultExponentialHistogramSnapShot.getEmptySnapshotForScale(scale)
-                : new DefaultExponentialHistogramSnapShot(scale, getOffset(), zeroCount.longValue(), zeroThreshold,
-                        getBucketCounts());
+                : new DefaultExponentialHistogramSnapShot(scale, zeroCount.longValue(), zeroThreshold,
+                        new ExponentialBucket(getOffset(), getBucketCounts()), EMPTY_EXPONENTIAL_BUCKET);
     }
 
     /**

implementations/micrometer-registry-otlp/src/main/java/io/micrometer/registry/otlp/internal/CumulativeBase2ExponentialHistogram.java

@@ -21,10 +21,14 @@
 
 /**
  * A {@link Base2ExponentialHistogram} that tracks values cumulatively from first recorded
- * value.
+ * value. *
+ * <p>
+ * * <strong> This is an internal class and might have breaking changes, external *
+ * implementations SHOULD NOT rely on this implementation. </strong> *
+ * </p>
  *
  * @author Lenin Jaganathan
- * @since 1.12.0
+ * @since 1.14.0
  */
 public class CumulativeBase2ExponentialHistogram extends Base2ExponentialHistogram {