Add probability to decision when appropriate

sdk/src/main/java/io/opentelemetry/sdk/trace/Sampler.java

@@ -92,6 +92,6 @@ interface Decision {
      *     span or when sampling decision {@link #isSampled()} changes from false to true.
      * @since 0.1.0
      */
-    Map<String, AttributeValue> attributes();
+    Map<String, AttributeValue> getAttributes();
   }
 }

sdk/src/main/java/io/opentelemetry/sdk/trace/Samplers.java

@@ -16,6 +16,9 @@
 
 package io.opentelemetry.sdk.trace;
 
+import static io.opentelemetry.common.AttributeValue.doubleAttributeValue;
+import static java.util.Collections.singletonMap;
+
 import com.google.auto.value.AutoValue;
 import com.google.common.base.Preconditions;
 import io.opentelemetry.common.AttributeValue;
@@ -25,6 +28,7 @@
 import io.opentelemetry.trace.SpanContext;
 import io.opentelemetry.trace.SpanId;
 import io.opentelemetry.trace.TraceId;
+import io.opentelemetry.trace.attributes.DoubleAttributeSetter;
 import java.util.Collections;
 import java.util.List;
 import java.util.Map;
@@ -38,6 +42,7 @@
  */
 @Immutable
 public final class Samplers {
+
   private static final Sampler ALWAYS_ON = new AlwaysOnSampler();
   private static final Sampler ALWAYS_OFF = new AlwaysOffSampler();
   private static final Decision ALWAYS_ON_DECISION = new SimpleDecision(/* decision= */ true);
@@ -162,13 +167,21 @@ static Probability create(double probability) {
       } else {
         idUpperBound = (long) (probability * Long.MAX_VALUE);
       }
-      return new AutoValue_Samplers_Probability(probability, idUpperBound);
+      return new AutoValue_Samplers_Probability(
+          probability,
+          idUpperBound,
+          ProbabilityDecision.create(/* decision= */ true, probability),
+          ProbabilityDecision.create(/* decision= */ false, probability));
     }
 
     abstract double getProbability();
 
     abstract long getIdUpperBound();
 
+    abstract Decision getPositiveDecision();
+
+    abstract Decision getNegativeDecision();
+
     @Override
     public final Decision shouldSample(
         @Nullable SpanContext parentContext,
@@ -198,8 +211,8 @@ public final Decision shouldSample(
       // This is considered a reasonable tradeoff for the simplicity/performance requirements (this
       // code is executed in-line for every Span creation).
       return Math.abs(traceId.getLowerLong()) < getIdUpperBound()
-          ? ALWAYS_ON_DECISION
-          : ALWAYS_OFF_DECISION;
+          ? getPositiveDecision()
+          : getNegativeDecision();
     }
 
     @Override
@@ -229,8 +242,44 @@ public boolean isSampled() {
     }
 
     @Override
-    public Map<String, AttributeValue> attributes() {
+    public Map<String, AttributeValue> getAttributes() {
       return Collections.emptyMap();
     }
   }
+
+  /**
+   * Probability value used by a probability-based Span sampling strategy.
+   *
+   * <p>Note: This will need to be updated if a specification for this value is merged which changes
+   * this proposed value. Also, once it's in the spec, we should move it somewhere more visible.
+   *
+   * <p>See https://github.com/open-telemetry/opentelemetry-specification/pull/570
+   */
+  static final DoubleAttributeSetter SAMPLING_PROBABILITY =
+      DoubleAttributeSetter.create("sampling.probability");
+
+  /** Probability-based sampling decision with a single attribute for the probability. */
+  @Immutable
+  @AutoValue
+  abstract static class ProbabilityDecision implements Decision {
+
+    ProbabilityDecision() {}
+
+    /**
+     * Creates sampling decision without attributes.
+     *
+     * @param decision sampling decision
+     * @param probability the probability that was used for the decision.
+     */
+    static ProbabilityDecision create(boolean decision, double probability) {
+      return new AutoValue_Samplers_ProbabilityDecision(
+          decision, singletonMap(SAMPLING_PROBABILITY.key(), doubleAttributeValue(probability)));
+    }
+
+    @Override
+    public abstract boolean isSampled();
+
+    @Override
+    public abstract Map<String, AttributeValue> getAttributes();
+  }
 }

sdk/src/main/java/io/opentelemetry/sdk/trace/SpanBuilderSdk.java

@@ -230,7 +230,7 @@ public Span startSpan() {
       return DefaultSpan.create(spanContext);
     }
 
-    attributes.putAllAttributes(samplingDecision.attributes());
+    attributes.putAllAttributes(samplingDecision.getAttributes());
 
     return RecordEventsReadableSpan.startSpan(
         spanContext,

sdk/src/test/java/io/opentelemetry/sdk/trace/SamplersTest.java

@@ -17,6 +17,7 @@
 package io.opentelemetry.sdk.trace;
 
 import static com.google.common.truth.Truth.assertThat;
+import static io.opentelemetry.common.AttributeValue.doubleAttributeValue;
 
 import com.google.common.truth.Truth;
 import io.opentelemetry.common.AttributeValue;
@@ -267,7 +268,8 @@ public void probabilitySampler_SampleBasedOnTraceId() {
             Collections.<String, AttributeValue>emptyMap(),
             Collections.<Link>emptyList());
     assertThat(decision1.isSampled()).isFalse();
-    assertThat(decision1.attributes()).isEmpty();
+    assertThat(decision1.getAttributes())
+        .containsExactly(Samplers.SAMPLING_PROBABILITY.key(), doubleAttributeValue(0.0001));
     // This traceId will be sampled by the Probability Sampler because the first 8 bytes as long
     // is less than probability * Long.MAX_VALUE;
     TraceId sampledtraceId =
@@ -301,6 +303,7 @@ public void probabilitySampler_SampleBasedOnTraceId() {
             Collections.<String, AttributeValue>emptyMap(),
             Collections.<Link>emptyList());
     assertThat(decision2.isSampled()).isTrue();
-    assertThat(decision2.attributes()).isEmpty();
+    assertThat(decision1.getAttributes())
+        .containsExactly(Samplers.SAMPLING_PROBABILITY.key(), doubleAttributeValue(0.0001));
   }
 }

sdk/src/test/java/io/opentelemetry/sdk/trace/SpanBuilderSdkTest.java

@@ -305,7 +305,7 @@ public boolean isSampled() {
                           }
 
                           @Override
-                          public Map<String, AttributeValue> attributes() {
+                          public Map<String, AttributeValue> getAttributes() {
                             Map<String, AttributeValue> attributes = new LinkedHashMap<>();
                             attributes.put(
                                 samplerAttributeName, AttributeValue.stringAttributeValue("bar"));