How to force max to return ALL maximum values in a Java Stream?
I believe the OP is using a Comparator to partition the input into equivalence classes, and the desired result is a list of members of the equivalence class that is the maximum according to that Comparator.
Unfortunately, using int values as a sample problem is a terrible example. All equal int values are fungible, so there is no notion of preserving the ordering of equivalent values. Perhaps a better example is using string lengths, where the desired result is to return a list of strings from an input that all have the longest length within that input.
I don't know of any way to do this without storing at least partial results in a collection.
Given an input collection, say
List<String> list = ... ;
...it's simple enough to do this in two passes, the first to get the longest length, and the second to filter the strings that have that length:
int longest = list.stream()
.mapToInt(String::length)
.max()
.orElse(-1);
List<String> result = list.stream()
.filter(s -> s.length() == longest)
.collect(toList());
If the input is a stream, which cannot be traversed more than once, it is possible to compute the result in only a single pass using a collector. Writing such a collector isn't difficult, but it is a bit tedious as there are several cases to be handled. A helper function that generates such a collector, given a Comparator, is as follows:
static <T> Collector<T,?,List<T>> maxList(Comparator<? super T> comp) {
return Collector.of(
ArrayList::new,
(list, t) -> {
int c;
if (list.isEmpty() || (c = comp.compare(t, list.get(0))) == 0) {
list.add(t);
} else if (c > 0) {
list.clear();
list.add(t);
}
},
(list1, list2) -> {
if (list1.isEmpty()) {
return list2;
}
if (list2.isEmpty()) {
return list1;
}
int r = comp.compare(list1.get(0), list2.get(0));
if (r < 0) {
return list2;
} else if (r > 0) {
return list1;
} else {
list1.addAll(list2);
return list1;
}
});
}
This stores intermediate results in an ArrayList. The invariant is that all elements within any such list are equivalent in terms of the Comparator. When adding an element, if it's less than the elements in the list, it's ignored; if it's equal, it's added; and if it's greater, the list is emptied and the new element is added. Merging isn't too difficult either: the list with the greater elements is returned, but if their elements are equal the lists are appended.
Given an input stream, this is pretty easy to use:
Stream<String> input = ... ;
List<String> result = input.collect(maxList(comparing(String::length)));
I would group by value and store the values into a TreeMap in order to have my values sorted, then I would get the max value by getting the last entry as next:
Stream.of(1, 3, 5, 3, 2, 3, 5)
.collect(groupingBy(Function.identity(), TreeMap::new, toList()))
.lastEntry()
.getValue()
.forEach(System.out::println);
Output:
5
5
I implemented more generic collector solution with custom downstream collector. Probably some readers might find it useful:
public static <T, A, D> Collector<T, ?, D> maxAll(Comparator<? super T> comparator,
Collector<? super T, A, D> downstream) {
Supplier<A> downstreamSupplier = downstream.supplier();
BiConsumer<A, ? super T> downstreamAccumulator = downstream.accumulator();
BinaryOperator<A> downstreamCombiner = downstream.combiner();
class Container {
A acc;
T obj;
boolean hasAny;
Container(A acc) {
this.acc = acc;
}
}
Supplier<Container> supplier = () -> new Container(downstreamSupplier.get());
BiConsumer<Container, T> accumulator = (acc, t) -> {
if(!acc.hasAny) {
downstreamAccumulator.accept(acc.acc, t);
acc.obj = t;
acc.hasAny = true;
} else {
int cmp = comparator.compare(t, acc.obj);
if (cmp > 0) {
acc.acc = downstreamSupplier.get();
acc.obj = t;
}
if (cmp >= 0)
downstreamAccumulator.accept(acc.acc, t);
}
};
BinaryOperator<Container> combiner = (acc1, acc2) -> {
if (!acc2.hasAny) {
return acc1;
}
if (!acc1.hasAny) {
return acc2;
}
int cmp = comparator.compare(acc1.obj, acc2.obj);
if (cmp > 0) {
return acc1;
}
if (cmp < 0) {
return acc2;
}
acc1.acc = downstreamCombiner.apply(acc1.acc, acc2.acc);
return acc1;
};
Function<Container, D> finisher = acc -> downstream.finisher().apply(acc.acc);
return Collector.of(supplier, accumulator, combiner, finisher);
}
So by default it can be collected to a list using:
public static <T> Collector<T, ?, List<T>> maxAll(Comparator<? super T> comparator) {
return maxAll(comparator, Collectors.toList());
}
But you can use other downstream collectors as well:
public static String joinLongestStrings(Collection<String> input) {
return input.stream().collect(
maxAll(Comparator.comparingInt(String::length), Collectors.joining(","))));
}
If I understood well, you want the frequency of the max value in the Stream.
One way to achieve that would be to store the results in a TreeMap<Integer, List<Integer> when you collect elements from the Stream. Then you grab the last key (or first depending on the comparator you give) to get the value which will contains the list of max values.
List<Integer> maxValues = st.collect(toMap(i -> i,
Arrays::asList,
(l1, l2) -> Stream.concat(l1.stream(), l2.stream()).collect(toList()),
TreeMap::new))
.lastEntry()
.getValue();
Collecting it from the Stream(4, 5, -2, 5, 5) will give you a List [5, 5, 5].
Another approach in the same spirit would be to use a group by operation combined with the counting() collector:
Entry<Integer, Long> maxValues = st.collect(groupingBy(i -> i,
TreeMap::new,
counting())).lastEntry(); //5=3 -> 5 appears 3 times
Basically you firstly get a Map<Integer, List<Integer>>. Then the downstream counting() collector will return the number of elements in each list mapped by its key resulting in a Map. From there you grab the max entry.
The first approaches require to store all the elements from the stream. The second one is better (see Holger's comment) as the intermediate List is not built. In both approached, the result is computed in a single pass.
If you get the source from a collection, you may want to use Collections.max one time to find the maximum value followed by Collections.frequency to find how many times this value appears.
It requires two passes but uses less memory as you don't have to build the data-structure.
The stream equivalent would be coll.stream().max(...).get(...) followed by coll.stream().filter(...).count().