fix stats aggregator tests

With #60683 we stopped forcing aggregating all docs using a single
Aggregator which made some of our accuracy assumptions about the stats
aggregator incorrect. This adds a test that does the forcing and asserts
the old accuracy and adds a test without the forcing with much looser
accuracy guarantees.

Closes #61132

Author: nik9000

server/src/test/java/org/elasticsearch/search/aggregations/metrics/StatsAggregatorTests.java

@@ -61,6 +61,7 @@
 import static java.util.Collections.emptyMap;
 import static java.util.Collections.emptySet;
 import static java.util.Collections.singleton;
+import static java.util.Collections.singletonList;
 import static java.util.Collections.singletonMap;
 import static java.util.stream.Collectors.toList;
 import static java.util.stream.Collectors.toSet;
@@ -140,7 +141,7 @@ public void testRandomLongs() throws IOException {
     public void testSummationAccuracy() throws IOException {
         // Summing up a normal array and expect an accurate value
         double[] values = new double[]{0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7};
-        verifySummationOfDoubles(values, 15.3, 0.9, 0d);
+        verifySummationOfDoubles(values, 15.3, 0.9, 0d, values.length * TOLERANCE);
 
         // Summing up an array which contains NaN and infinities and expect a result same as naive summation
         int n = randomIntBetween(5, 10);
@@ -152,24 +153,29 @@ public void testSummationAccuracy() throws IOException {
                 : randomDoubleBetween(Double.MIN_VALUE, Double.MAX_VALUE, true);
             sum += values[i];
         }
-        verifySummationOfDoubles(values, sum, sum / n, TOLERANCE);
+        verifySummationOfDoubles(values, sum, sum / n, TOLERANCE, n * TOLERANCE);
 
         // Summing up some big double values and expect infinity result
         n = randomIntBetween(5, 10);
         double[] largeValues = new double[n];
         for (int i = 0; i < n; i++) {
             largeValues[i] = Double.MAX_VALUE;
         }
-        verifySummationOfDoubles(largeValues, Double.POSITIVE_INFINITY, Double.POSITIVE_INFINITY, 0d);
+        verifySummationOfDoubles(largeValues, Double.POSITIVE_INFINITY, Double.POSITIVE_INFINITY, 0d, 0d);
 
         for (int i = 0; i < n; i++) {
             largeValues[i] = -Double.MAX_VALUE;
         }
-        verifySummationOfDoubles(largeValues, Double.NEGATIVE_INFINITY, Double.NEGATIVE_INFINITY, 0d);
+        verifySummationOfDoubles(largeValues, Double.NEGATIVE_INFINITY, Double.NEGATIVE_INFINITY, 0d, 0d);
     }
 
-    private void verifySummationOfDoubles(double[] values, double expectedSum,
-                                          double expectedAvg, double delta) throws IOException {
+    private void verifySummationOfDoubles(
+        double[] values,
+        double expectedSum,
+        double expectedAvg,
+        double singleSegmentDelta,
+        double manySegmentDelta
+    ) throws IOException {
         MappedFieldType ft = new NumberFieldMapper.NumberFieldType("field", NumberType.DOUBLE);
 
         double max = Double.NEGATIVE_INFINITY;
@@ -183,14 +189,33 @@ private void verifySummationOfDoubles(double[] values, double expectedSum,
         testCase(
             stats("_name").field(ft.name()),
             iw -> {
+                List<List<NumericDocValuesField>> docs = new ArrayList<>();
                 for (double value : values) {
-                    iw.addDocument(singleton(new NumericDocValuesField(ft.name(), NumericUtils.doubleToSortableLong(value))));
+                    docs.add(singletonList(new NumericDocValuesField(ft.name(), NumericUtils.doubleToSortableLong(value))));
                 }
+                iw.addDocuments(docs);
             },
             stats -> {
                 assertEquals(values.length, stats.getCount());
-                assertEquals(expectedAvg, stats.getAvg(), delta);
-                assertEquals(expectedSum, stats.getSum(), delta);
+                assertEquals(expectedAvg, stats.getAvg(), singleSegmentDelta);
+                assertEquals(expectedSum, stats.getSum(), singleSegmentDelta);
+                assertEquals(expectedMax, stats.getMax(), 0d);
+                assertEquals(expectedMin, stats.getMin(), 0d);
+                assertTrue(AggregationInspectionHelper.hasValue(stats));
+            },
+            singleton(ft)
+        );
+        testCase(
+            stats("_name").field(ft.name()),
+            iw -> {
+                for (double value : values) {
+                    iw.addDocument(singletonList(new NumericDocValuesField(ft.name(), NumericUtils.doubleToSortableLong(value))));
+                }
+            },
+            stats -> {
+                assertEquals(values.length, stats.getCount());
+                assertEquals(expectedAvg, stats.getAvg(), manySegmentDelta);
+                assertEquals(expectedSum, stats.getSum(), manySegmentDelta);
                 assertEquals(expectedMax, stats.getMax(), 0d);
                 assertEquals(expectedMin, stats.getMin(), 0d);
                 assertTrue(AggregationInspectionHelper.hasValue(stats));