### 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
.minDocCount(0),
            true
        );
    }
    public void testHardBoundsUsesFromRange() throws IOException {
        aggregationImplementationChoiceTestCase(
            aggregableDateFieldType(false, true, DateFormatter.forPattern("yyyy")),
            List.of("2016", "2017", "2018", "2019"),
            List.of("2017", "2018"),
            new DateHistogramAggregationBuilder("test").field(AGGREGABLE_DATE)
                .calendarInterval(DateHistogramInterval.YEAR)
                .hardBounds(new LongBounds("2017", "2019")),
            true
        );
    }
    public void testOneBucketOptimized() throws IOException {
        AggregationBuilder builder = new DateHistogramAggregationBuilder("d").field("f").calendarInterval(DateHistogramInterval.DAY);
        CheckedConsumer<RandomIndexWriter, IOException> buildIndex = iw -> {
            long start = DateFieldMapper.DEFAULT_DATE_TIME_FORMATTER.parseMillis("2020-01-01T00:00:01");
            for (int i = 0; i < RangeAggregator.DOCS_PER_RANGE_TO_USE_FILTERS; i++) {
                long date = start + i;
                iw.addDocument(List.of(new LongPoint("f", date), new NumericDocValuesField("f", date)));
            }
            for (int i = 0; i < 10; i++) {
                iw.addDocument(List.of());
            }
        };
        DateFieldMapper.DateFieldType ft = new DateFieldMapper.DateFieldType("f");
        
        FieldNamesFieldMapper.FieldNamesFieldType fnft = FieldNamesFieldMapper.FieldNamesFieldType.get(true);