Increase InternalHistogramTests coverage (#36004)

In `InternalHistogramTests` we were randomizing different values but `minDocCount` was hardcoded to `1`. It's important to test other values, especially `0` as it's the default. To make this possible, the test needed some adapting in the way buckets are randomly generated: all aggs need to share the same `interval`, `minDocCount` and `emptyBucketInfo`. Also assertions need to take into account that more (or less) buckets are expected depending on `minDocCount`.

This was originated by #35921 and its need to test adding empty buckets as part of the reduce phase.

Also relates to #26856 as one more key comparison needed to use `Double.compare` to properly handle `NaN` values, which was triggered by the increased test coverage.
This commit is contained in:
Luca Cavanna 2018-11-28 20:06:40 +01:00 committed by GitHub
parent 513e1ed095
commit 4b85769d24
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2 changed files with 63 additions and 12 deletions

View File

@ -213,7 +213,7 @@ public final class InternalHistogram extends InternalMultiBucketAggregation<Inte
private final DocValueFormat format;
private final boolean keyed;
private final long minDocCount;
private final EmptyBucketInfo emptyBucketInfo;
final EmptyBucketInfo emptyBucketInfo;
InternalHistogram(String name, List<Bucket> buckets, BucketOrder order, long minDocCount, EmptyBucketInfo emptyBucketInfo,
DocValueFormat formatter, boolean keyed, List<PipelineAggregator> pipelineAggregators,
@ -302,7 +302,7 @@ public final class InternalHistogram extends InternalMultiBucketAggregation<Inte
final PriorityQueue<IteratorAndCurrent> pq = new PriorityQueue<IteratorAndCurrent>(aggregations.size()) {
@Override
protected boolean lessThan(IteratorAndCurrent a, IteratorAndCurrent b) {
return a.current.key < b.current.key;
return Double.compare(a.current.key, b.current.key) < 0;
}
};
for (InternalAggregation aggregation : aggregations) {
@ -405,7 +405,7 @@ public final class InternalHistogram extends InternalMultiBucketAggregation<Inte
iter.add(new Bucket(key, 0, keyed, format, reducedEmptySubAggs));
key = nextKey(key);
}
assert key == nextBucket.key;
assert key == nextBucket.key || Double.isNaN(nextBucket.key) : "key: " + key + ", nextBucket.key: " + nextBucket.key;
}
lastBucket = iter.next();
} while (iter.hasNext());

View File

@ -25,9 +25,9 @@ import org.elasticsearch.search.DocValueFormat;
import org.elasticsearch.search.aggregations.BucketOrder;
import org.elasticsearch.search.aggregations.InternalAggregation;
import org.elasticsearch.search.aggregations.InternalAggregations;
import org.elasticsearch.test.InternalMultiBucketAggregationTestCase;
import org.elasticsearch.search.aggregations.ParsedMultiBucketAggregation;
import org.elasticsearch.search.aggregations.pipeline.PipelineAggregator;
import org.elasticsearch.test.InternalMultiBucketAggregationTestCase;
import java.util.ArrayList;
import java.util.Arrays;
@ -40,12 +40,36 @@ public class InternalHistogramTests extends InternalMultiBucketAggregationTestCa
private boolean keyed;
private DocValueFormat format;
private int interval;
private int minDocCount;
private InternalHistogram.EmptyBucketInfo emptyBucketInfo;
private int offset;
@Override
public void setUp() throws Exception{
public void setUp() throws Exception {
super.setUp();
keyed = randomBoolean();
format = randomNumericDocValueFormat();
//in order for reduction to work properly (and be realistic) we need to use the same interval, minDocCount, emptyBucketInfo
//and offset in all randomly created aggs as part of the same test run. This is particularly important when minDocCount is
//set to 0 as empty buckets need to be added to fill the holes.
interval = randomIntBetween(1, 3);
offset = randomIntBetween(0, 3);
if (randomBoolean()) {
minDocCount = randomIntBetween(1, 10);
emptyBucketInfo = null;
} else {
minDocCount = 0;
//it's ok if minBound and maxBound are outside the range of the generated buckets, that will just mean that
//empty buckets won't be added before the first bucket and/or after the last one
int minBound = randomInt(50) - 30;
int maxBound = randomNumberOfBuckets() * interval + randomIntBetween(0, 10);
emptyBucketInfo = new InternalHistogram.EmptyBucketInfo(interval, offset, minBound, maxBound, InternalAggregations.EMPTY);
}
}
private double round(double key) {
return Math.floor((key - offset) / interval) * interval + offset;
}
@Override
@ -53,16 +77,18 @@ public class InternalHistogramTests extends InternalMultiBucketAggregationTestCa
List<PipelineAggregator> pipelineAggregators,
Map<String, Object> metaData,
InternalAggregations aggregations) {
final int base = randomInt(50) - 30;
final double base = round(randomInt(50) - 30);
final int numBuckets = randomNumberOfBuckets();
final int interval = randomIntBetween(1, 3);
List<InternalHistogram.Bucket> buckets = new ArrayList<>();
for (int i = 0; i < numBuckets; ++i) {
//rarely leave some holes to be filled up with empty buckets in case minDocCount is set to 0
if (frequently()) {
final int docCount = TestUtil.nextInt(random(), 1, 50);
buckets.add(new InternalHistogram.Bucket(base + i * interval, docCount, keyed, format, aggregations));
}
}
BucketOrder order = BucketOrder.key(randomBoolean());
return new InternalHistogram(name, buckets, order, 1, null, format, keyed, pipelineAggregators, metaData);
return new InternalHistogram(name, buckets, order, minDocCount, emptyBucketInfo, format, keyed, pipelineAggregators, metaData);
}
// issue 26787
@ -88,13 +114,36 @@ public class InternalHistogramTests extends InternalMultiBucketAggregationTestCa
@Override
protected void assertReduced(InternalHistogram reduced, List<InternalHistogram> inputs) {
Map<Double, Long> expectedCounts = new TreeMap<>();
TreeMap<Double, Long> expectedCounts = new TreeMap<>();
for (Histogram histogram : inputs) {
for (Histogram.Bucket bucket : histogram.getBuckets()) {
expectedCounts.compute((Double) bucket.getKey(),
(key, oldValue) -> (oldValue == null ? 0 : oldValue) + bucket.getDocCount());
}
}
if (minDocCount == 0) {
double minBound = round(emptyBucketInfo.minBound);
if (expectedCounts.isEmpty() && emptyBucketInfo.minBound < emptyBucketInfo.maxBound) {
expectedCounts.put(minBound, 0L);
}
if (expectedCounts.isEmpty() == false) {
Double nextKey = expectedCounts.firstKey();
while (nextKey < expectedCounts.lastKey()) {
expectedCounts.putIfAbsent(nextKey, 0L);
nextKey += interval;
}
while (minBound < expectedCounts.firstKey()) {
expectedCounts.put(expectedCounts.firstKey() - interval, 0L);
}
double maxBound = round(emptyBucketInfo.maxBound);
while (expectedCounts.lastKey() < maxBound) {
expectedCounts.put(expectedCounts.lastKey() + interval, 0L);
}
}
} else {
expectedCounts.entrySet().removeIf(doubleLongEntry -> doubleLongEntry.getValue() < minDocCount);
}
Map<Double, Long> actualCounts = new TreeMap<>();
for (Histogram.Bucket bucket : reduced.getBuckets()) {
actualCounts.compute((Double) bucket.getKey(),
@ -121,6 +170,7 @@ public class InternalHistogramTests extends InternalMultiBucketAggregationTestCa
long minDocCount = instance.getMinDocCount();
List<PipelineAggregator> pipelineAggregators = instance.pipelineAggregators();
Map<String, Object> metaData = instance.getMetaData();
InternalHistogram.EmptyBucketInfo emptyBucketInfo = instance.emptyBucketInfo;
switch (between(0, 4)) {
case 0:
name += randomAlphaOfLength(5);
@ -135,6 +185,7 @@ public class InternalHistogramTests extends InternalMultiBucketAggregationTestCa
break;
case 3:
minDocCount += between(1, 10);
emptyBucketInfo = null;
break;
case 4:
if (metaData == null) {
@ -147,6 +198,6 @@ public class InternalHistogramTests extends InternalMultiBucketAggregationTestCa
default:
throw new AssertionError("Illegal randomisation branch");
}
return new InternalHistogram(name, buckets, order, minDocCount, null, format, keyed, pipelineAggregators, metaData);
return new InternalHistogram(name, buckets, order, minDocCount, emptyBucketInfo, format, keyed, pipelineAggregators, metaData);
}
}