Clamp exponential histogram percentiles to min/max

Author: JonasKunz

libs/exponential-histogram/src/main/java/org/elasticsearch/exponentialhistogram/ExponentialHistogramQuantile.java

@@ -34,6 +34,7 @@ public class ExponentialHistogramQuantile {
      * It returns the value of the element at rank {@code max(0, min(n - 1, (quantile * (n + 1)) - 1))}, where n is the total number of
      * values and rank starts at 0. If the rank is fractional, the result is linearly interpolated from the values of the two
      * neighboring ranks.
+     * The result is clamped to the histogram's minimum and maximum values.
      *
      * @param histo    the histogram representing the distribution
      * @param quantile the quantile to query, in the range [0, 1]
@@ -67,7 +68,7 @@ public static double getQuantile(ExponentialHistogram histo, double quantile) {
         } else {
             result = values.valueAtPreviousRank() * (1 - upperFactor) + values.valueAtRank() * upperFactor;
         }
-        return removeNegativeZero(result);
+        return removeNegativeZero(Math.clamp(result, histo.min(), histo.max()));
     }
 
     private static double removeNegativeZero(double result) {

libs/exponential-histogram/src/test/java/org/elasticsearch/exponentialhistogram/QuantileAccuracyTests.java

@@ -63,6 +63,21 @@ public void testNoNegativeZeroReturned() {
         assertThat(median, equalTo(0.0));
     }
 
+    public void testPercentilesClampedToMinMax() {
+        ExponentialHistogram histogram = createAutoReleasedHistogram(
+            b -> b
+                .scale(0)
+                .setNegativeBucket(1, 1)
+                .setPositiveBucket(1, 1)
+                .max(0.00001)
+                .min(-0.00002)
+        );
+        double p01 = ExponentialHistogramQuantile.getQuantile(histogram, 0.01);
+        double p99 = ExponentialHistogramQuantile.getQuantile(histogram, 0.99);
+        assertThat(p01, equalTo(-0.00002));
+        assertThat(p99, equalTo(0.00001));
+    }
+
     public void testUniformDistribution() {
         testDistributionQuantileAccuracy(new UniformRealDistribution(new Well19937c(randomInt()), 0, 100));
     }