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Jul 4, 2025
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chore: Add Exemplar Support in Cloud Monitoring Exporter #3952

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3 changes: 2 additions & 1 deletion ...-cloud-spanner/src/main/java/com/google/cloud/spanner/SpannerCloudMonitoringExporter.java
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Original file line number Diff line number Diff line change
Expand Up @@ -141,7 +141,8 @@ private CompletableResultCode exportSpannerClientMetrics(Collection<MetricData>
List<TimeSeries> spannerTimeSeries;
try {
spannerTimeSeries =
SpannerCloudMonitoringExporterUtils.convertToSpannerTimeSeries(spannerMetricData);
SpannerCloudMonitoringExporterUtils.convertToSpannerTimeSeries(
spannerMetricData, this.spannerProjectId);
} catch (Throwable e) {
logger.log(
Level.WARNING,
Expand Down
85 changes: 78 additions & 7 deletions ...d-spanner/src/main/java/com/google/cloud/spanner/SpannerCloudMonitoringExporterUtils.java
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Original file line number Diff line number Diff line change
Expand Up @@ -36,17 +36,24 @@
import com.google.api.MetricDescriptor.MetricKind;
import com.google.api.MetricDescriptor.ValueType;
import com.google.api.MonitoredResource;
import com.google.monitoring.v3.DroppedLabels;
import com.google.monitoring.v3.Point;
import com.google.monitoring.v3.SpanContext;
import com.google.monitoring.v3.TimeInterval;
import com.google.monitoring.v3.TimeSeries;
import com.google.monitoring.v3.TypedValue;
import com.google.protobuf.Any;
import com.google.protobuf.Timestamp;
import com.google.protobuf.util.Timestamps;
import io.opentelemetry.api.common.AttributeKey;
import io.opentelemetry.api.common.Attributes;
import io.opentelemetry.sdk.metrics.data.AggregationTemporality;
import io.opentelemetry.sdk.metrics.data.DoubleExemplarData;
import io.opentelemetry.sdk.metrics.data.DoublePointData;
import io.opentelemetry.sdk.metrics.data.ExemplarData;
import io.opentelemetry.sdk.metrics.data.HistogramData;
import io.opentelemetry.sdk.metrics.data.HistogramPointData;
import io.opentelemetry.sdk.metrics.data.LongExemplarData;
import io.opentelemetry.sdk.metrics.data.LongPointData;
import io.opentelemetry.sdk.metrics.data.MetricData;
import io.opentelemetry.sdk.metrics.data.MetricDataType;
Expand All @@ -57,6 +64,7 @@
import java.util.List;
import java.util.logging.Level;
import java.util.logging.Logger;
import java.util.stream.Collectors;

class SpannerCloudMonitoringExporterUtils {

Expand All @@ -69,7 +77,8 @@ static String getProjectId(Resource resource) {
return resource.getAttributes().get(PROJECT_ID_KEY);
}

static List<TimeSeries> convertToSpannerTimeSeries(List<MetricData> collection) {
static List<TimeSeries> convertToSpannerTimeSeries(
List<MetricData> collection, String projectId) {
List<TimeSeries> allTimeSeries = new ArrayList<>();

for (MetricData metricData : collection) {
Expand All @@ -94,7 +103,8 @@ static List<TimeSeries> convertToSpannerTimeSeries(List<MetricData> collection)
metricData.getData().getPoints().stream()
.map(
pointData ->
convertPointToSpannerTimeSeries(metricData, pointData, monitoredResourceBuilder))
convertPointToSpannerTimeSeries(
metricData, pointData, monitoredResourceBuilder, projectId))
.forEach(allTimeSeries::add);
}
return allTimeSeries;
Expand All @@ -103,7 +113,8 @@ static List<TimeSeries> convertToSpannerTimeSeries(List<MetricData> collection)
private static TimeSeries convertPointToSpannerTimeSeries(
MetricData metricData,
PointData pointData,
MonitoredResource.Builder monitoredResourceBuilder) {
MonitoredResource.Builder monitoredResourceBuilder,
String projectId) {
TimeSeries.Builder builder =
TimeSeries.newBuilder()
.setMetricKind(convertMetricKind(metricData))
Expand Down Expand Up @@ -135,7 +146,7 @@ private static TimeSeries convertPointToSpannerTimeSeries(
.setEndTime(Timestamps.fromNanos(pointData.getEpochNanos()))
.build();

builder.addPoints(createPoint(metricData.getType(), pointData, timeInterval));
builder.addPoints(createPoint(metricData.getType(), pointData, timeInterval, projectId));

return builder.build();
}
Expand Down Expand Up @@ -191,15 +202,16 @@ private static ValueType convertValueType(MetricDataType metricDataType) {
}

private static Point createPoint(
MetricDataType type, PointData pointData, TimeInterval timeInterval) {
MetricDataType type, PointData pointData, TimeInterval timeInterval, String projectId) {
Point.Builder builder = Point.newBuilder().setInterval(timeInterval);
switch (type) {
case HISTOGRAM:
case EXPONENTIAL_HISTOGRAM:
return builder
.setValue(
TypedValue.newBuilder()
.setDistributionValue(convertHistogramData((HistogramPointData) pointData))
.setDistributionValue(
convertHistogramData((HistogramPointData) pointData, projectId))
.build())
.build();
case DOUBLE_GAUGE:
Expand All @@ -221,14 +233,73 @@ private static Point createPoint(
}
}

private static Distribution convertHistogramData(HistogramPointData pointData) {
private static Distribution convertHistogramData(HistogramPointData pointData, String projectId) {
return Distribution.newBuilder()
.setCount(pointData.getCount())
.setMean(pointData.getCount() == 0L ? 0.0D : pointData.getSum() / pointData.getCount())
.setBucketOptions(
BucketOptions.newBuilder()
.setExplicitBuckets(Explicit.newBuilder().addAllBounds(pointData.getBoundaries())))
.addAllBucketCounts(pointData.getCounts())
.addAllExemplars(
pointData.getExemplars().stream()
.map(e -> mapExemplar(e, projectId))
.collect(Collectors.toList()))
.build();
}

private static Distribution.Exemplar mapExemplar(ExemplarData exemplar, String projectId) {
double value = 0;
if (exemplar instanceof DoubleExemplarData) {
value = ((DoubleExemplarData) exemplar).getValue();
} else if (exemplar instanceof LongExemplarData) {
value = ((LongExemplarData) exemplar).getValue();
}

Distribution.Exemplar.Builder exemplarBuilder =
Distribution.Exemplar.newBuilder()
.setValue(value)
.setTimestamp(mapTimestamp(exemplar.getEpochNanos()));
if (exemplar.getSpanContext().isValid()) {
exemplarBuilder.addAttachments(
Any.pack(
SpanContext.newBuilder()
.setSpanName(
makeSpanName(
projectId,
exemplar.getSpanContext().getTraceId(),
exemplar.getSpanContext().getSpanId()))
.build()));
}
if (!exemplar.getFilteredAttributes().isEmpty()) {
exemplarBuilder.addAttachments(
Any.pack(mapFilteredAttributes(exemplar.getFilteredAttributes())));
}
return exemplarBuilder.build();
}

static final long NANO_PER_SECOND = (long) 1e9;

private static Timestamp mapTimestamp(long epochNanos) {
return Timestamp.newBuilder()
.setSeconds(epochNanos / NANO_PER_SECOND)
.setNanos((int) (epochNanos % NANO_PER_SECOND))
.build();
}

private static String makeSpanName(String projectId, String traceId, String spanId) {
return String.format("projects/%s/traces/%s/spans/%s", projectId, traceId, spanId);
}

private static DroppedLabels mapFilteredAttributes(Attributes attributes) {
DroppedLabels.Builder labels = DroppedLabels.newBuilder();
attributes.forEach((k, v) -> labels.putLabel(cleanAttributeKey(k.getKey()), v.toString()));
return labels.build();
}

private static String cleanAttributeKey(String key) {
// . is commonly used in OTel but disallowed in GCM label names,
// https://cloud.google.com/monitoring/api/ref_v3/rest/v3/LabelDescriptor#:~:text=Matches%20the%20following%20regular%20expression%3A
return key.replace('.', '_');
}
}
86 changes: 86 additions & 0 deletions ...ud-spanner/src/test/java/com/google/cloud/spanner/SpannerCloudMonitoringExporterTest.java
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Original file line number Diff line number Diff line change
Expand Up @@ -42,15 +42,21 @@
import com.google.cloud.monitoring.v3.stub.MetricServiceStub;
import com.google.common.collect.ImmutableList;
import com.google.monitoring.v3.CreateTimeSeriesRequest;
import com.google.monitoring.v3.DroppedLabels;
import com.google.monitoring.v3.TimeSeries;
import com.google.protobuf.Empty;
import io.opentelemetry.api.common.Attributes;
import io.opentelemetry.api.trace.SpanContext;
import io.opentelemetry.api.trace.TraceFlags;
import io.opentelemetry.api.trace.TraceState;
import io.opentelemetry.sdk.common.InstrumentationScopeInfo;
import io.opentelemetry.sdk.metrics.InstrumentType;
import io.opentelemetry.sdk.metrics.data.AggregationTemporality;
import io.opentelemetry.sdk.metrics.data.DoubleExemplarData;
import io.opentelemetry.sdk.metrics.data.HistogramPointData;
import io.opentelemetry.sdk.metrics.data.LongPointData;
import io.opentelemetry.sdk.metrics.data.MetricData;
import io.opentelemetry.sdk.metrics.internal.data.ImmutableDoubleExemplarData;
import io.opentelemetry.sdk.metrics.internal.data.ImmutableHistogramData;
import io.opentelemetry.sdk.metrics.internal.data.ImmutableHistogramPointData;
import io.opentelemetry.sdk.metrics.internal.data.ImmutableLongPointData;
Expand Down Expand Up @@ -347,6 +353,86 @@ public void testExportingSumDataInBatches() {
}
}

@Test
public void testExportingHistogramDataWithExemplars() {
ArgumentCaptor<CreateTimeSeriesRequest> argumentCaptor =
ArgumentCaptor.forClass(CreateTimeSeriesRequest.class);

UnaryCallable<CreateTimeSeriesRequest, Empty> mockCallable = mock(UnaryCallable.class);
when(mockMetricServiceStub.createServiceTimeSeriesCallable()).thenReturn(mockCallable);
ApiFuture<Empty> future = ApiFutures.immediateFuture(Empty.getDefaultInstance());
when(mockCallable.futureCall(argumentCaptor.capture())).thenReturn(future);

long startEpoch = 10 * 1_000_000_000L;
long endEpoch = 15 * 1_000_000_000L;
long recordTimeEpoch = 12_123_456_789L;

DoubleExemplarData exemplar =
ImmutableDoubleExemplarData.create(
Attributes.builder().put("request_id", "test").build(),
recordTimeEpoch,
SpanContext.create(
"0123456789abcdef0123456789abcdef",
"0123456789abcdef",
TraceFlags.getSampled(),
TraceState.getDefault()),
1.5);

HistogramPointData histogramPointData =
ImmutableHistogramPointData.create(
startEpoch,
endEpoch,
attributes,
3d,
true,
1d,
true,
2d,
Collections.singletonList(1.0),
Arrays.asList(1L, 2L),
Collections.singletonList(exemplar) // ← add exemplar
);

MetricData histogramData =
ImmutableMetricData.createDoubleHistogram(
resource,
scope,
"spanner.googleapis.com/internal/client/" + OPERATION_LATENCIES_NAME,
"description",
"ms",
ImmutableHistogramData.create(
AggregationTemporality.CUMULATIVE, ImmutableList.of(histogramPointData)));

exporter.export(Collections.singletonList(histogramData));
assertFalse(exporter.lastExportSkippedData());

CreateTimeSeriesRequest request = argumentCaptor.getValue();
TimeSeries timeSeries = request.getTimeSeriesList().get(0);
Distribution distribution = timeSeries.getPoints(0).getValue().getDistributionValue();

// Assert exemplar exists and has expected value
assertThat(distribution.getExemplarsCount()).isEqualTo(1);
Distribution.Exemplar exportedExemplar = distribution.getExemplars(0);
assertThat(exportedExemplar.getValue()).isEqualTo(1.5);

// Assert timestamp mapping
assertThat(exportedExemplar.getTimestamp().getSeconds())
.isEqualTo(recordTimeEpoch / 1_000_000_000L);
assertThat(exportedExemplar.getTimestamp().getNanos())
.isEqualTo((int) (recordTimeEpoch % 1_000_000_000L));

// Assert attachments: SpanContext
boolean hasSpanAttachment =
exportedExemplar.getAttachmentsList().stream()
.anyMatch(any -> any.is(com.google.monitoring.v3.SpanContext.class));
assertThat(hasSpanAttachment).isTrue();

// Assert attachments: DroppedLabels (filtered attributes)
boolean hasFilteredAttrs =
exportedExemplar.getAttachmentsList().stream().anyMatch(any -> any.is(DroppedLabels.class));
assertThat(hasFilteredAttrs).isTrue();
}

@Test
public void getAggregationTemporality() throws IOException {
SpannerCloudMonitoringExporter actualExporter =
Expand Down