java8新特性-引用流-reduce

reduce操作用于对数据进行聚合，比如求和等。

一、reduce(BinaryOperator accumulator)
 

例子：

List users = new ArrayList<>();
users.add(new User("张三",30));
users.add(new User("李四",39));
users.add(new User("王五",20));

Optional reduce = users.stream().map(User::getAge).reduce((a, b) -> a + b);
System.out.println(reduce.get());

输出：

 

源码分析：
ReferencePipeline#reduce(BinaryOperator<P_OUT> accumulator)

public final Optional<P_OUT> reduce(BinaryOperator<P_OUT> accumulator) {
return evaluate(ReduceOps.makeRef(accumulator));
}

进入ReduceOps.makeRef(BinaryOperator operator)方法。
 

ReduceOps#makeRef(BinaryOperator operator)

public static TerminalOp<T, Optional>
makeRef(BinaryOperator operator) {
Objects.requireNonNull(operator);
class ReducingSink
implements AccumulatingSink<T, Optional, ReducingSink> {
private boolean empty;
private T state;

public void begin(long size) {
empty = true;
state = null;
}

@Override
public void accept(T t) {
if (empty) {
empty = false;
state = t;
} else {
state = operator.apply(state, t);
}
}

@Override
public Optional get() {
return empty ? Optional.empty() : Optional.of(state);
}

@Override
public void combine(ReducingSink other) {
if (!other.empty)
accept(other.state);
}
}
return new ReduceOp<T, Optional, ReducingSink>(StreamShape.REFERENCE) {
@Override
public ReducingSink makeSink() {
return new ReducingSink();
}
};
}

ReduceOps会调用makeSink获取Sink。begin方法设置empty和state的初始值。看看ReducingSink里的accept方法。第一次进入，empty为true，将state设置t，以后将t和state运行BinaryOperator聚合数据且将结果赋给state。如果Stream中没有元素则empty为true，state为null。

 
 
 

二、 reduce(T identity, BinaryOperator accumulator)

identity是初始值，功能和reduce(BinaryOperator accumulator )类似。

 

例子：

List users = new ArrayList<>();
users.add(new User("张三",30));
users.add(new User("李四",39));
users.add(new User("王五",20));

Integer reduce = users.stream().map(User::getAge).reduce(0,(a, b) -> a + b);
System.out.println(reduce);

输出：

 

 

源码分析：
ReferencePipeline#reduce(final P_OUT identity, final BinaryOperator<P_OUT> accumulator)

public final P_OUT reduce(final P_OUT identity, final BinaryOperator<P_OUT> accumulator) {
return evaluate(ReduceOps.makeRef(identity, accumulator, accumulator));
}

进入ReduceOps.makeRef(U seed, BiFunction<U, ? super T, U> reducer, BinaryOperator<U> combiner )方法

  makeRef(U seed, BiFunction<U, ? super T, U> reducer, BinaryOperator<U> combiner) {
      Objects.requireNonNull(reducer);
      Objects.requireNonNull(combiner);
      class ReducingSink extends Box<U> implements AccumulatingSink<T, U, ReducingSink> {
          @Override
          public void begin(long size) {
              state = seed;
          }

          @Override
          public void accept(T t) {
              state = reducer.apply(state, t);
          }

          @Override
          public void combine(ReducingSink other) {
              state = combiner.apply(state, other.state);
          }
      }
      return new ReduceOp<T, U, ReducingSink>(StreamShape.REFERENCE) {
          @Override
          public ReducingSink makeSink() {
              return new ReducingSink();
          }
      };
  }

ReduceOps会调用makeSink获取Sink。ReducingSink的begin将state设置为seed，seed就是传进去的初始值。每次调用accept都会运行BiFunction将state 和 t执行聚合。

 
三、reduce(U identity, BiFunction<U, ? super T, U> accumulator, BinaryOperator<U> combiner)
第一个参数是返回值的初始值，accumulator是对Stream中每个元素执行的聚合操作，combiner是在并行流中对每个线程的执行结果进行合并。

 

例子

List users = new ArrayList<>();
users.add(new User("张三",30));
users.add(new User("李四",34));
users.add(new User("王五",20));

ArrayList reduce1 = users.stream().reduce(new ArrayList(), (list, user) -> {
if (user.getAge() >= 30){
list.add(user);
}
System.out.println("执行accumulator");
return list;
}, ((users1, users2) -> {
System.out.println("执行combiner");
users1.addAll(users2);
return users1;
}));
System.out.println(reduce1);

输出：

 
 

源码分析：
ReferencePipeline#reduce(R identity, BiFunction<R, ? super P_OUT, R> accumulator, BinaryOperator combiner)

public final R reduce(R identity, BiFunction<R, ? super P_OUT, R> accumulator, BinaryOperator combiner) {
return evaluate(ReduceOps.makeRef(identity, accumulator, combiner));
}

进入ReduceOps.makeRef。

ReduceOps#makeRef

public static <T, U> TerminalOp<T, U>
makeRef(U seed, BiFunction<U, ? super T, U> reducer, BinaryOperator combiner) {
Objects.requireNonNull(reducer);
Objects.requireNonNull(combiner);
class ReducingSink extends Box implements AccumulatingSink<T, U, ReducingSink> {
@Override
public void begin(long size) {
state = seed;
}

@Override
public void accept(T t) {
state = reducer.apply(state, t);
}

@Override
public void combine(ReducingSink other) {
state = combiner.apply(state, other.state);
}
}
return new ReduceOp<T, U, ReducingSink>(StreamShape.REFERENCE) {
@Override
public ReducingSink makeSink() {
return new ReducingSink();
}
};
}

关注ReducingSink。ReducingSink#begin将state初始化为seed，accept对Stream中的每个元素执行reducer操作。