先摘錄關於collection併發的一段話:html
One difficulty in implementing parallelism in applications that use collections is that collections are not thread-safe, which means that multiple threads cannot manipulate a collection without introducing thread interference or memory consistency errors. The Collections Framework provides synchronization wrappers, which add automatic synchronization to an arbitrary collection, making it thread-safe. However, synchronization introduces thread contention. You want to avoid thread contention because it prevents threads from running in parallel. Aggregate operations and parallel streams enable you to implement parallelism with non-thread-safe collections provided that you do not modify the collection while you are operating on it.java
這段話可以說明爲何須要parallel stream.併發
下面看看如何使用parallel stream,有兩種調用方式:oracle
1.app
double average = roster .parallelStream() .filter(p -> p.getGender() == Person.Sex.MALE) .mapToInt(Person::getAge) .average() .getAsDouble();
2.ide
double average = roster
.stream().parallel()
.filter(p -> p.getGender() == Person.Sex.MALE)
.mapToInt(Person::getAge)
.average()
.getAsDouble();
還有個關於排序的問題,下面這段代碼使用forEachOrdered是能保證順序的,用通常的forEach是沒法保證順序的:spa
listOfIntegers .parallelStream() .forEachOrdered(e -> System.out.print(e + " "));