[TEST] Increase InternalDateHistogramTests coverage (#36064)

In this test 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. 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.

server/src/main/java/org/elasticsearch/search/aggregations/bucket/histogram/InternalDateHistogram.java

@@ -219,7 +219,7 @@ public final class InternalDateHistogram extends InternalMultiBucketAggregation<
     private final boolean keyed;
     private final long minDocCount;
     private final long offset;
-    private final EmptyBucketInfo emptyBucketInfo;
+    final EmptyBucketInfo emptyBucketInfo;
 
     InternalDateHistogram(String name, List<Bucket> buckets, BucketOrder order, long minDocCount, long offset,
             EmptyBucketInfo emptyBucketInfo,

server/src/test/java/org/elasticsearch/search/aggregations/bucket/histogram/InternalDateHistogramTests.java

@@ -20,12 +20,14 @@
 package org.elasticsearch.search.aggregations.bucket.histogram;
 
 import org.elasticsearch.common.io.stream.Writeable;
+import org.elasticsearch.common.rounding.Rounding;
+import org.elasticsearch.common.unit.TimeValue;
 import org.elasticsearch.search.DocValueFormat;
 import org.elasticsearch.search.aggregations.BucketOrder;
 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 org.joda.time.DateTime;
 
 import java.util.ArrayList;
@@ -42,12 +44,38 @@ public class InternalDateHistogramTests extends InternalMultiBucketAggregationTe
 
     private boolean keyed;
     private DocValueFormat format;
+    private long intervalMillis;
+    private long baseMillis;
+    private long minDocCount;
+    private InternalDateHistogram.EmptyBucketInfo emptyBucketInfo;
 
     @Override
     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 base 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.
+        long interval = randomIntBetween(1, 3);
+        intervalMillis = randomFrom(timeValueSeconds(interval), timeValueMinutes(interval), timeValueHours(interval)).getMillis();
+        Rounding rounding = Rounding.builder(TimeValue.timeValueMillis(intervalMillis)).build();
+        baseMillis = rounding.round(System.currentTimeMillis());
+        if (randomBoolean()) {
+            minDocCount = randomIntBetween(1, 10);
+            emptyBucketInfo = null;
+        } else {
+            minDocCount = 0;
+            ExtendedBounds extendedBounds = null;
+            if (randomBoolean()) {
+                //it's ok if min and max 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
+                long min = baseMillis - intervalMillis * randomNumberOfBuckets();
+                long max = baseMillis + randomNumberOfBuckets() * intervalMillis + randomNumberOfBuckets();
+                extendedBounds = new ExtendedBounds(min, max);
+            }
+            emptyBucketInfo = new InternalDateHistogram.EmptyBucketInfo(rounding, InternalAggregations.EMPTY, extendedBounds);
+        }
     }
 
     @Override
@@ -57,29 +85,58 @@ public class InternalDateHistogramTests extends InternalMultiBucketAggregationTe
                                                        InternalAggregations aggregations) {
         int nbBuckets = randomNumberOfBuckets();
         List<InternalDateHistogram.Bucket> buckets = new ArrayList<>(nbBuckets);
-        long startingDate = System.currentTimeMillis();
-
-        long interval = randomIntBetween(1, 3);
-        long intervalMillis = randomFrom(timeValueSeconds(interval), timeValueMinutes(interval), timeValueHours(interval)).getMillis();
-
+        //avoid having different random instance start from exactly the same base
+        long startingDate = baseMillis - intervalMillis * randomIntBetween(0, 100);
         for (int i = 0; i < nbBuckets; i++) {
-            long key = startingDate + (intervalMillis * i);
-            buckets.add(i, new InternalDateHistogram.Bucket(key, randomIntBetween(1, 100), keyed, format, aggregations));
+            //rarely leave some holes to be filled up with empty buckets in case minDocCount is set to 0
+            if (frequently()) {
+                long key = startingDate + intervalMillis * i;
+                buckets.add(new InternalDateHistogram.Bucket(key, randomIntBetween(1, 100), keyed, format, aggregations));
+            }
         }
-
-        BucketOrder order = randomFrom(BucketOrder.key(true), BucketOrder.key(false));
-        return new InternalDateHistogram(name, buckets, order, 1, 0L, null, format, keyed, pipelineAggregators, metaData);
+        BucketOrder order = BucketOrder.key(randomBoolean());
+        return new InternalDateHistogram(name, buckets, order, minDocCount, 0L, emptyBucketInfo, format, keyed,
+            pipelineAggregators, metaData);
     }
 
     @Override
     protected void assertReduced(InternalDateHistogram reduced, List<InternalDateHistogram> inputs) {
-        Map<Long, Long> expectedCounts = new TreeMap<>();
+        TreeMap<Long, Long> expectedCounts = new TreeMap<>();
         for (Histogram histogram : inputs) {
             for (Histogram.Bucket bucket : histogram.getBuckets()) {
                 expectedCounts.compute(((DateTime) bucket.getKey()).getMillis(),
                         (key, oldValue) -> (oldValue == null ? 0 : oldValue) + bucket.getDocCount());
             }
         }
+        if (minDocCount == 0) {
+            long minBound = -1;
+            long maxBound = -1;
+            if (emptyBucketInfo.bounds != null) {
+                minBound = emptyBucketInfo.rounding.round(emptyBucketInfo.bounds.getMin());
+                maxBound = emptyBucketInfo.rounding.round(emptyBucketInfo.bounds.getMax());
+                if (expectedCounts.isEmpty() && minBound <= maxBound) {
+                    expectedCounts.put(minBound, 0L);
+                }
+            }
+            if (expectedCounts.isEmpty() == false) {
+                Long nextKey = expectedCounts.firstKey();
+                while (nextKey < expectedCounts.lastKey()) {
+                    expectedCounts.putIfAbsent(nextKey, 0L);
+                    nextKey += intervalMillis;
+                }
+                if (emptyBucketInfo.bounds != null) {
+                    while (minBound < expectedCounts.firstKey()) {
+                        expectedCounts.put(expectedCounts.firstKey() - intervalMillis, 0L);
+                    }
+                    while (expectedCounts.lastKey() < maxBound) {
+                        expectedCounts.put(expectedCounts.lastKey() + intervalMillis, 0L);
+                    }
+                }
+            }
+        } else {
+            expectedCounts.entrySet().removeIf(doubleLongEntry -> doubleLongEntry.getValue() < minDocCount);
+        }
+
         Map<Long, Long> actualCounts = new TreeMap<>();
         for (Histogram.Bucket bucket : reduced.getBuckets()) {
             actualCounts.compute(((DateTime) bucket.getKey()).getMillis(),
@@ -106,6 +163,7 @@ public class InternalDateHistogramTests extends InternalMultiBucketAggregationTe
         long minDocCount = instance.getMinDocCount();
         long offset = instance.getOffset();
         List<PipelineAggregator> pipelineAggregators = instance.pipelineAggregators();
+        InternalDateHistogram.EmptyBucketInfo emptyBucketInfo = instance.emptyBucketInfo;
         Map<String, Object> metaData = instance.getMetaData();
         switch (between(0, 5)) {
         case 0:
@@ -121,6 +179,7 @@ public class InternalDateHistogramTests extends InternalMultiBucketAggregationTe
             break;
         case 3:
             minDocCount += between(1, 10);
+            emptyBucketInfo = null;
             break;
         case 4:
             offset += between(1, 20);
@@ -136,7 +195,7 @@ public class InternalDateHistogramTests extends InternalMultiBucketAggregationTe
         default:
             throw new AssertionError("Illegal randomisation branch");
         }
-        return new InternalDateHistogram(name, buckets, order, minDocCount, offset, null, format, keyed, pipelineAggregators,
+        return new InternalDateHistogram(name, buckets, order, minDocCount, offset, emptyBucketInfo, format, keyed, pipelineAggregators,
                 metaData);
     }
 }

server/src/test/java/org/elasticsearch/search/aggregations/bucket/histogram/InternalHistogramTests.java

@@ -123,7 +123,7 @@ public class InternalHistogramTests extends InternalMultiBucketAggregationTestCa
         }
         if (minDocCount == 0) {
             double minBound = round(emptyBucketInfo.minBound);
-            if (expectedCounts.isEmpty() && emptyBucketInfo.minBound < emptyBucketInfo.maxBound) {
+            if (expectedCounts.isEmpty() && emptyBucketInfo.minBound <= emptyBucketInfo.maxBound) {
                 expectedCounts.put(minBound, 0L);
             }
             if (expectedCounts.isEmpty() == false) {