Only execute one final reduction in InternalAutoDateHistogram (#45359)
Because auto-date-histo can perform multiple reductions while merging buckets, we need to ensure that the intermediate reductions are done with a `finalReduce` set to false to prevent Pipeline aggs from generating their output. Once all the buckets have been merged and the output is stable, a mostly-noop reduction can be performed which will allow pipelines to generate their output.
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@ -500,15 +500,24 @@ public final class InternalAutoDateHistogram extends
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BucketReduceResult reducedBucketsResult = reduceBuckets(aggregations, reduceContext);
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if (reduceContext.isFinalReduce()) {
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// Because auto-date-histo can perform multiple reductions while merging buckets, we need to pretend this is
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// not the final reduction to prevent pipeline aggs from creating their result early. However we want
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// to reuse the multiBucketConsumer so that max_buckets breaker is correctly accounted for
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ReduceContext penultimateReduceContext = new ReduceContext(reduceContext.bigArrays(), reduceContext.scriptService(),
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reduceContext::consumeBucketsAndMaybeBreak, false);
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// adding empty buckets if needed
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reducedBucketsResult = addEmptyBuckets(reducedBucketsResult, reduceContext);
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reducedBucketsResult = addEmptyBuckets(reducedBucketsResult, penultimateReduceContext);
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// Adding empty buckets may have tipped us over the target so merge the buckets again if needed
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reducedBucketsResult = mergeBucketsIfNeeded(reducedBucketsResult.buckets, reducedBucketsResult.roundingIdx,
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reducedBucketsResult.roundingInfo, reduceContext);
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reducedBucketsResult.roundingInfo, penultimateReduceContext);
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// Now finally see if we need to merge consecutive buckets together to make a coarser interval at the same rounding
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reducedBucketsResult = maybeMergeConsecutiveBuckets(reducedBucketsResult, reduceContext);
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reducedBucketsResult = maybeMergeConsecutiveBuckets(reducedBucketsResult, penultimateReduceContext);
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// Perform the final reduction which will mostly be a no-op, except for pipeline aggs
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reducedBucketsResult = performFinalReduce(reducedBucketsResult, penultimateReduceContext);
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}
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BucketInfo bucketInfo = new BucketInfo(this.bucketInfo.roundingInfos, reducedBucketsResult.roundingIdx,
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@ -561,6 +570,28 @@ public final class InternalAutoDateHistogram extends
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return new BucketReduceResult(mergedBuckets, roundingInfo, roundingIdx, mergeInterval);
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}
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/**
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* Execute a final reduction on `reducedBuckets`. This should be called after all the buckets have been
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* merged into the appropriate roundings. After the buckets are stable, this method will perform one last
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* reduction with finalReduce: true so that Pipeline aggs can generate their output.
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*/
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private BucketReduceResult performFinalReduce(BucketReduceResult reducedBuckets, ReduceContext reduceContext) {
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// We need to create another reduce context, this time setting finalReduce: true. Unlike the prior
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// reduce context, we _do not_ want to reuse the multiBucketConsumer from the reduce context.
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// We've already generated (and accounted for) all the buckets we will return, this method just triggers
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// a final reduction on un-reduced items like pipelines. If we re-use the multiBucketConsumer we would
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// over-count the buckets
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ReduceContext finalReduceContext = new ReduceContext(reduceContext.bigArrays(), reduceContext.scriptService(), true);
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List<Bucket> finalBuckets = new ArrayList<>();
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for (int i = 0; i < reducedBuckets.buckets.size(); i++) {
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finalBuckets.add(reducedBuckets.buckets.get(i).reduce(Collections.singletonList(reducedBuckets.buckets.get(i)),
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reducedBuckets.roundingInfo.rounding, finalReduceContext));
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}
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assert reducedBuckets.buckets.size() == finalBuckets.size();
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return new BucketReduceResult(finalBuckets, reducedBuckets.roundingInfo, reducedBuckets.roundingIdx, reducedBuckets.innerInterval);
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}
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@Override
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public XContentBuilder doXContentBody(XContentBuilder builder, Params params) throws IOException {
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builder.startArray(CommonFields.BUCKETS.getPreferredName());
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@ -36,10 +36,15 @@ import org.elasticsearch.common.settings.Settings;
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import org.elasticsearch.common.time.DateFormatter;
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import org.elasticsearch.index.IndexSettings;
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import org.elasticsearch.index.mapper.DateFieldMapper;
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import org.elasticsearch.index.mapper.MappedFieldType;
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import org.elasticsearch.index.mapper.NumberFieldMapper;
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import org.elasticsearch.search.aggregations.AggregationBuilders;
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import org.elasticsearch.search.aggregations.AggregatorTestCase;
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import org.elasticsearch.search.aggregations.MultiBucketConsumerService;
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import org.elasticsearch.search.aggregations.metrics.InternalMax;
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import org.elasticsearch.search.aggregations.metrics.InternalStats;
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import org.elasticsearch.search.aggregations.pipeline.DerivativePipelineAggregationBuilder;
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import org.elasticsearch.search.aggregations.pipeline.InternalSimpleValue;
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import org.elasticsearch.search.aggregations.support.AggregationInspectionHelper;
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import org.hamcrest.Matchers;
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import org.junit.Assert;
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@ -58,9 +63,12 @@ import java.util.Map;
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import java.util.function.Consumer;
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import java.util.stream.Collectors;
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import static org.hamcrest.Matchers.equalTo;
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public class AutoDateHistogramAggregatorTests extends AggregatorTestCase {
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private static final String DATE_FIELD = "date";
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private static final String INSTANT_FIELD = "instant";
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private static final String NUMERIC_FIELD = "numeric";
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private static final List<ZonedDateTime> DATES_WITH_TIME = Arrays.asList(
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ZonedDateTime.of(2010, 3, 12, 1, 7, 45, 0, ZoneOffset.UTC),
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@ -718,6 +726,35 @@ public class AutoDateHistogramAggregatorTests extends AggregatorTestCase {
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);
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}
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public void testWithPipelineReductions() throws IOException {
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testSearchAndReduceCase(DEFAULT_QUERY, DATES_WITH_TIME,
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aggregation -> aggregation.setNumBuckets(1).field(DATE_FIELD)
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.subAggregation(AggregationBuilders.histogram("histo").field(NUMERIC_FIELD).interval(1)
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.subAggregation(AggregationBuilders.max("max").field(NUMERIC_FIELD))
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.subAggregation(new DerivativePipelineAggregationBuilder("deriv", "max"))),
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histogram -> {
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assertTrue(AggregationInspectionHelper.hasValue(histogram));
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final List<? extends Histogram.Bucket> buckets = histogram.getBuckets();
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assertEquals(1, buckets.size());
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Histogram.Bucket bucket = buckets.get(0);
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assertEquals("2010-01-01T00:00:00.000Z", bucket.getKeyAsString());
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assertEquals(10, bucket.getDocCount());
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assertThat(bucket.getAggregations().asList().size(), equalTo(1));
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InternalHistogram histo = (InternalHistogram) bucket.getAggregations().asList().get(0);
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assertThat(histo.getBuckets().size(), equalTo(10));
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for (int i = 0; i < 10; i++) {
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assertThat(histo.getBuckets().get(i).key, equalTo((double)i));
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assertThat(((InternalMax)histo.getBuckets().get(i).aggregations.get("max")).getValue(), equalTo((double)i));
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if (i > 0) {
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assertThat(((InternalSimpleValue)histo.getBuckets().get(i).aggregations.get("deriv")).getValue(), equalTo(1.0));
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}
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}
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});
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}
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private void testSearchCase(final Query query, final List<ZonedDateTime> dataset,
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final Consumer<AutoDateHistogramAggregationBuilder> configure,
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final Consumer<InternalAutoDateHistogram> verify) throws IOException {
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@ -757,6 +794,7 @@ public class AutoDateHistogramAggregatorTests extends AggregatorTestCase {
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try (Directory directory = newDirectory()) {
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try (RandomIndexWriter indexWriter = new RandomIndexWriter(random(), directory)) {
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final Document document = new Document();
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int i = 0;
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for (final ZonedDateTime date : dataset) {
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if (frequently()) {
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indexWriter.commit();
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@ -765,8 +803,10 @@ public class AutoDateHistogramAggregatorTests extends AggregatorTestCase {
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final long instant = date.toInstant().toEpochMilli();
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document.add(new SortedNumericDocValuesField(DATE_FIELD, instant));
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document.add(new LongPoint(INSTANT_FIELD, instant));
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document.add(new SortedNumericDocValuesField(NUMERIC_FIELD, i));
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indexWriter.addDocument(document);
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document.clear();
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i += 1;
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}
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}
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@ -783,11 +823,19 @@ public class AutoDateHistogramAggregatorTests extends AggregatorTestCase {
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fieldType.setHasDocValues(true);
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fieldType.setName(aggregationBuilder.field());
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MappedFieldType instantFieldType = new NumberFieldMapper.NumberFieldType(NumberFieldMapper.NumberType.LONG);
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instantFieldType.setName(INSTANT_FIELD);
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instantFieldType.setHasDocValues(true);
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MappedFieldType numericFieldType = new NumberFieldMapper.NumberFieldType(NumberFieldMapper.NumberType.LONG);
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numericFieldType.setName(NUMERIC_FIELD);
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numericFieldType.setHasDocValues(true);
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final InternalAutoDateHistogram histogram;
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if (reduced) {
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histogram = searchAndReduce(indexSearcher, query, aggregationBuilder, fieldType);
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histogram = searchAndReduce(indexSearcher, query, aggregationBuilder, fieldType, instantFieldType, numericFieldType);
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} else {
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histogram = search(indexSearcher, query, aggregationBuilder, fieldType);
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histogram = search(indexSearcher, query, aggregationBuilder, fieldType, instantFieldType);
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}
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verify.accept(histogram);
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}
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@ -50,11 +50,15 @@ public class InternalAutoDateHistogramTests extends InternalMultiBucketAggregati
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private DocValueFormat format;
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private RoundingInfo[] roundingInfos;
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private int nbBuckets;
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@Override
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public void setUp() throws Exception {
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super.setUp();
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// these need to be the same for each new instance created so that {@link #testReduceRandom()}
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// has mergeable instances to work with
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format = randomNumericDocValueFormat();
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nbBuckets = randomNumberOfBuckets();
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}
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@Override
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@ -64,7 +68,7 @@ public class InternalAutoDateHistogramTests extends InternalMultiBucketAggregati
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InternalAggregations aggregations) {
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roundingInfos = AutoDateHistogramAggregationBuilder.buildRoundings(null, null);
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int nbBuckets = randomNumberOfBuckets();
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int targetBuckets = randomIntBetween(1, nbBuckets * 2 + 1);
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List<InternalAutoDateHistogram.Bucket> buckets = new ArrayList<>(nbBuckets);
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