Clojure transducers与Java中流上的中间操作是相同的概念吗？

主要区别在于，动词集（操作）以某种方式对流关闭，而对传感器开放：例如，尝试在流上实现，感觉有点二等：partition

import java.util.function.Function;
import java.util.function.Supplier;
import java.util.stream.Stream;
import java.util.stream.Stream.Builder;

public class StreamUtils {
    static <T> Stream<T> delay(final Supplier<Stream<T>> thunk) {
        return Stream.of((Object) null).flatMap(x -> thunk.get());
    }

    static class Partitioner<T> implements Function<T, Stream<Stream<T>>> {
        final Function<T, ?> f;

        Object prev;
        Builder<T> sb;

        public Partitioner(Function<T, ?> f) {
            this.f = f;
        }

        public Stream<Stream<T>> apply(T t) {
            Object tag = f.apply(t);
            if (sb != null && prev.equals(tag)) {
                sb.accept(t);
                return Stream.empty();
            }
            Stream<Stream<T>> partition = sb == null ? Stream.empty() : Stream.of(sb.build());
            sb = Stream.builder();
            sb.accept(t);
            prev = tag;
            return partition;
        }

        Stream<Stream<T>> flush() {
            return sb == null ? Stream.empty() : Stream.of(sb.build());
        }
    }

    static <T> Stream<Stream<T>> partitionBy(Stream<T> in, Function<T, ?> f) {
        Partitioner<T> partitioner = new Partitioner<>(f);
        return Stream.concat(in.flatMap(partitioner), delay(() -> partitioner.flush()));
    }
}

同样像序列和化简器一样，当你转换时，你不会创建一个“更大”的计算，而是创建一个“更大”的源。

为了能够传递计算，您引入了一个从 Stream 到 Stream 的函数，用于将操作从方法提升到一等实体（以便将它们从源中解绑）。通过这样做，您已经创建了一个传感器，尽管接口太大。xf

以下是上述代码的更通用版本，用于将任何（clojure）传感器应用于Stream：

import java.util.function.Function;
import java.util.function.Supplier;
import java.util.stream.Stream;
import java.util.stream.Stream.Builder;

import clojure.lang.AFn;
import clojure.lang.IFn;
import clojure.lang.Reduced;

public class StreamUtils {
    static <T> Stream<T> delay(final Supplier<Stream<T>> thunk) {
        return Stream.of((Object) null).flatMap(x -> thunk.get());
    }

    static class Transducer implements Function {
        IFn rf;

        public Transducer(IFn xf) {
            rf = (IFn) xf.invoke(new AFn() {
                public Object invoke(Object acc) {
                    return acc;
                }

                public Object invoke(Object acc, Object item) {
                    ((Builder<Object>) acc).accept(item);
                    return acc;
                }
            });
        }

        public Stream<?> apply(Object t) {
            if (rf == null) return Stream.empty();
            Object ret = rf.invoke(Stream.builder(), t);
            if (ret instanceof Reduced) {
                Reduced red = (Reduced) ret;
                Builder<?> sb = (Builder<?>) red.deref();
                return Stream.concat(sb.build(), flush());
            }
            return ((Builder<?>) ret).build();
        }

        Stream<?> flush() {
            if (rf == null) return Stream.empty();
            Builder<?> sb = (Builder<?>) rf.invoke(Stream.builder());
            rf = null;
            return sb.build();
        }
    }

    static <T> Stream<?> withTransducer(Stream<T> in, IFn xf) {
        Transducer transducer = new Transducer(xf);
        return Stream.concat(in.flatMap(transducer), delay(() -> transducer.flush()));
    }
}

我看到的另一个重要区别是Clojure Transducers是可组合的。我经常遇到这样的情况，我的流管道比您的示例中要长一些，其中只有一些中间步骤可以在其他地方重复使用，例如：

someStream
   .map(...)
   .filter(...)
   .map(...)      // <- gee, there are at least two other
   .filter(...)   // <- pipelines where I could use the functionality
   .map(...)      // <- of just these three steps!
   .filter(...)
   .collect(...)

我还没有找到一种理智的方法来实现这一目标。我希望我有这样的东西：

Transducer<Integer,String> smallTransducer = s -> s.map(...); // usable in a stream Integer -> String
Transducer<String,MyClass> otherTransducer = s -> s.filter(...).map(...); // stream String -> MyClass
Transducer<Integer,MyClass> combinedTransducer = smallTransducer.then(otherTransducer); // compose transducers, to get an Integer -> MyClass transducer

然后像这样使用它：

someStream
   .map(...)
   .filter(...)
   .transduce(smallTransducer)
   .transduce(otherTransducer)
   .filter(...)
   .collect(...)

// or

someStream
   .map(...)
   .filter(...)
   .transduce(combinedTransducer)
   .filter(...)
   .collect(...)