### 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/main/java/org/elasticsearch/search/aggregations/bucket/range/RangeAggregator.java
FilterByFilterAggregator.AdapterBuilder<FromFilters<?>> filterByFilterBuilder = new FilterByFilterAggregator.AdapterBuilder<
            FromFilters<?>>(name, false, null, context, parent, cardinality, metadata) {
            @Override
            protected FromFilters<?> adapt(CheckedFunction<AggregatorFactories, FilterByFilterAggregator, IOException> delegate)
                throws IOException {
                return new FromFilters<>(
                    parent,
                    factories,
                    delegate,
                    valuesSourceConfig.format(),
                    ranges,
                    keyed,
                    rangeFactory,
                    averageDocsPerRange
                );
            }
        };
        for (int i = 0; i < ranges.length; i++) {
            /*
             * If the bounds on the ranges are too high then the `double`s
             * that we work with will round differently in the native range
             * aggregator than in the filters aggregator. So we can't use
             * the filters. That is, if the input data type is a `long` in
             * the first place. If it isn't then
             */
            if (wholeNumbersOnly && ranges[i].from != Double.NEGATIVE_INFINITY && Math.abs(ranges[i].from) > MAX_ACCURATE_BOUND) {
                return null;
            }
            if (wholeNumbersOnly && ranges[i].to != Double.POSITIVE_INFINITY && Math.abs(ranges[i].to) > MAX_ACCURATE_BOUND) {
                return null;