First create a TreeMap
, whose key is the salary. TreeMap
sorts it's entries by it's key. Then grab the first entry, which is the entry with the lowest salary and get hold of the values associated with that. This solution iterates over the list only once. Here's how it looks.
List empsWithLowestSalary = employees.stream()
.collect(Collectors.groupingBy(Employee::getSalary, TreeMap::new, Collectors.toList()))
.firstEntry()
.getValue();
TreeMap
stores map elements in a Red-Black tree. The insertion cost for one element in Red-Black tree is O(Log (n))
. Since we are inserting n
elements, the total Time complexity of this solution is O(n Log (n))
. For the firstEntry()
, it takes constant time O(1)
, since it maintains a pointer to the leftmost and rightmost leaf nodes in the tree respectively. The leftmost node represent the smallest value in the tree whereas the rightmost leaf node represents the highest value.
Just by following this great answer, I thought of writing a custom collector that serves our purpose. This collector iterates over the List only once and it's runtime complexity lies at O(n), which significantly outperforms the above approach. Furthermore it allows you to write your client code in one single statement. Here's how it looks.
static Collector> minList(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) {
/*
* We have found a smaller element than what we already have. Clear the list and
* add this smallest element to it.
*/
list.clear();
list.add(t);
}
}, (list1, list2) -> {
if (comp.compare(list1.get(0), list2.get(0)) < 0)
return list1;
else if (comp.compare(list1.get(0), list2.get(0)) > 0)
return list2;
else {
list1.addAll(list2);
return list1;
}
});
}
And here's your client code.
Collection empsWithLowestSalary = employees.stream()
.collect(minList(Comparator.comparing(Employee::getSalary)));