Collecting data with streams - Java 8 in Action: Lambdas, Streams, and Functional-Style Programming - page 166

Map<Dish.Type, Long> typesCount = menu.stream().collect(
groupingBy(Dish::getType, counting()));
The result is the following Map:
{MEAT=3, FISH=2, OTHER=4}
Also note that the regular one-argument groupingBy(f), where f is the classification function, is
in reality just shorthand for groupingBy(f, toList()).
To give another example, you could rework the collector you already used to find the
highest-calorie dish in the menu to achieve a similar result, but now classified by the type of
dish:
Map<Dish.Type, Optional<Dish>> mostCaloricByType =
menu.stream()
.collect(groupingBy(Dish::getType,
maxBy(comparingInt(Dish::getCalories))));
The result of this grouping is then clearly a Map, having as keys the available types of Dishes and
as values the Optional<Dish>, wrapping the corresponding highest-calorie Dish for a given type:
{FISH=Optional[salmon], OTHER=Optional[pizza], MEAT=Optional[pork]}
Note
The values in this Map are Optionals because this is the resulting type of the collector generated
by the maxBy factory method, but in reality if there's no Dish in the menu for a given type, that
type won't have an Optional.empty() as value; it won't be present at all as a key in the Map. The
groupingBy collector lazily adds a new key in the grouping Map only the first time it finds an
element in the stream, producing that key when applying on it the grouping criteria being used.
This means that in this case, the Optional wrapper isn't very useful, because it's not modeling a
value that could be eventually absent but is there incidentally, only because this is the type
returned by the reducing collector.