### Description

Our most common aggregations should be optimized for single-valued fields. In general, our aggregations look like this:

```java
    @Override
    public LeafBucketCollector getLeafCollector(LeafReaderContext ctx, LeafBucketCollector sub) throws IOException {
        if (valuesSource == null) {
            return LeafBucketCollector.NO_OP_COLLECTOR;
        }
        SortedNumericDocValues values = valuesSource.longValues(ctx);
        return new LeafBucketCollectorBase(sub, values) {
            @Override
            public void collect(int doc, long owningBucketOrd) throws IOException {
                if (values.advanceExact(doc)) {
                    int valuesCount = values.docValueCount();
                    for (int i = 0; i < valuesCount; ++i) {
                        long value = values.nextValue();
                        // do something with value
                    }
                }
            }
        };
    }
```

The idea consists of optimizing for single-valued fields by unwrapping the single-valued doc-value iterator:

```java
    @Override
    public LeafBucketCollector getLeafCollector(LeafReaderContext ctx, LeafBucketCollector sub) throws IOException {
        if (valuesSource == null) {
            return LeafBucketCollector.NO_OP_COLLECTOR;
        }
        SortedNumericDocValues values = valuesSource.longValues(ctx);
        NumericDocValues singleValues = DocValues.unwrapSingleton(values); // or FieldData.unwrapSingleton for doubles
        if (singleValues != null) {
            return new LeafBucketCollectorBase(sub, values) {
                @Override
                public void collect(int doc, long owningBucketOrd) throws IOException {
                    if (singleValues.advanceExact(doc)) {
                        long value = singleValues.longValue();
                        // do something with value
                    }
                }
            };
        } else {
            return new LeafBucketCollectorBase(sub, values) {
                @Override
                public void collect(int doc, long owningBucketOrd) throws IOException {
                    if (values.advanceExact(doc)) {
                        int valuesCount = values.docValueCount();
                        for (int i = 0; i < valuesCount; ++i) {
                            long value = values.nextValue();
                            // do something with value
                        }
                    }
                }
            };
        }
    }
```

The `terms` aggregation already does this, and e.g. `min` and `max` aggregations use similar tricks that also help optimize the single-valued case. But `date_histogram`, which is one of our most common aggregations, doesn't. Let's specialize the single-value case for date histograms too?
server/src/test/java/org/elasticsearch/search/aggregations/bucket/histogram/DateHistogramAggregatorTests.java
}
        };
        DateFieldMapper.DateFieldType ft = new DateFieldMapper.DateFieldType("f");
        
        FieldNamesFieldMapper.FieldNamesFieldType fnft = FieldNamesFieldMapper.FieldNamesFieldType.get(true);
        debugTestCase(
            builder,
            new MatchAllDocsQuery(),
            buildIndex,
            (InternalDateHistogram result, Class<? extends Aggregator> impl, Map<String, Map<String, Object>> debug) -> {
                assertThat(result.getBuckets(), hasSize(2));
                assertThat(result.getBuckets().get(0).getKeyAsString(), equalTo("2020-01-01T00:00:00.000Z"));
                assertThat(result.getBuckets().get(0).getDocCount(), equalTo(10010L));
                assertThat(result.getBuckets().get(1).getKeyAsString(), equalTo("2020-01-02T00:00:00.000Z"));
                assertThat(result.getBuckets().get(1).getDocCount(), equalTo(10010L));
                assertThat(impl, equalTo(DateHistogramAggregator.FromDateRange.class));
                assertMap(
                    debug,
                    matchesMap().entry(
                        "d",
                        matchesMap().entry("delegate", "RangeAggregator.NoOverlap")
                            .entry("delegate_debug", matchesMap().entry("ranges", 2).entry("average_docs_per_range", 5005.0))
                    )
                );
            },
            ft,
            fnft
        );
    }
    private void aggregationImplementationChoiceTestCase(