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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
This commit is contained in:
Nik Everett 2020-08-18 17:49:18 -04:00
parent b1aa0d8731
commit 70128e022b
1 changed files with 34 additions and 9 deletions
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43
server/src/test/java/org/elasticsearch/search/aggregations/metrics/StatsAggregatorTests.java
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@ -61,6 +61,7 @@ import java.util.function.Function;
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 class StatsAggregatorTests extends AggregatorTestCase {
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);
@ -152,7 +153,7 @@ public class StatsAggregatorTests extends AggregatorTestCase {
: 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);
@ -160,16 +161,21 @@ public class StatsAggregatorTests extends AggregatorTestCase {
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 @@ public class StatsAggregatorTests extends AggregatorTestCase {
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(), 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(), delta);
assertEquals(expectedSum, stats.getSum(), delta);
assertEquals(expectedAvg, stats.getAvg(), manySegmentDelta);
assertEquals(expectedSum, stats.getSum(), manySegmentDelta);
assertEquals(expectedMax, stats.getMax(), 0d);
assertEquals(expectedMin, stats.getMin(), 0d);
assertTrue(AggregationInspectionHelper.hasValue(stats));