Java 8 streams conditional processing

Simply test each element, and act accordingly.

lines.forEach(line -> {
    if (isTypeA(line)) processTypeA(line);
    else processTypeB(line);
});

This behavior could be hidden in a helper method:

public static <T> Consumer<T> branch(Predicate<? super T> test, 
                                     Consumer<? super T> t, 
                                     Consumer<? super T> f) {
    return o -> {
        if (test.test(o)) t.accept(o);
        else f.accept(o);
    };
}

Then the usage would look like this:

lines.forEach(branch(this::isTypeA, this::processTypeA, this::processTypeB));

Tangential Note

The Files.lines() method does not close the underlying file, so you must use it like this:

try (Stream<String> lines = Files.lines(path, encoding)) {
  lines.forEach(...);
}

Variables of Stream type throw up a bit of a red flag for me, so I prefer to manage a BufferedReader directly:

try (BufferedReader lines = Files.newBufferedReader(path, encoding)) {
    lines.lines().forEach(...);
}

While side effects in behavioral parameters are discouraged, they are not forbidden, as long as there’s no interference, so the simplest, though not cleanest solution is to count right in the filter:

AtomicInteger rejected=new AtomicInteger();
Files.lines(path)
    .filter(line -> {
        boolean accepted=isTypeA(line);
        if(!accepted) rejected.incrementAndGet();
        return accepted;
})
// chain processing of matched lines

As long as you are processing all items, the result will be consistent. Only if you are using a short-circuiting terminal operation (in a parallel stream), the result will become unpredictable.

Updating an atomic variable may not be the most efficient solution, but in the context of processing lines from a file, the overhead will likely be negligible.

If you want a clean, parallel friendly solution, one general approach is to implement a Collector which can combine the processing of two collect operations based on a condition. This requires that you are able to express the downstream operation as a collector, but most stream operations can be expressed as collector (and the trend is going towards the possibility to express all operation that way, i.e. Java 9 will add the currently missing filtering and flatMapping.

You’ll need a pair type to hold two results, so assuming a sketch like

class Pair<A,B> {
    final A a;
    final B b;
    Pair(A a, B b) {
        this.a=a;
        this.b=b;
    }
}

the combining collector implementation will look like

public static <T, A1, A2, R1, R2> Collector<T, ?, Pair<R1,R2>> conditional(
        Predicate<? super T> predicate,
        Collector<T, A1, R1> whenTrue, Collector<T, A2, R2> whenFalse) {
    Supplier<A1> s1=whenTrue.supplier();
    Supplier<A2> s2=whenFalse.supplier();
    BiConsumer<A1, T> a1=whenTrue.accumulator();
    BiConsumer<A2, T> a2=whenFalse.accumulator();
    BinaryOperator<A1> c1=whenTrue.combiner();
    BinaryOperator<A2> c2=whenFalse.combiner();
    Function<A1,R1> f1=whenTrue.finisher();
    Function<A2,R2> f2=whenFalse.finisher();
    return Collector.of(
        ()->new Pair<>(s1.get(), s2.get()),
        (p,t)->{
            if(predicate.test(t)) a1.accept(p.a, t); else a2.accept(p.b, t);
        },
        (p1,p2)->new Pair<>(c1.apply(p1.a, p2.a), c2.apply(p1.b, p2.b)),
        p -> new Pair<>(f1.apply(p.a), f2.apply(p.b)));
}

and can be used, for example for collecting matching items into a list and counting the non-matching, like this:

Pair<List<String>, Long> p = Files.lines(path)
  .collect(conditional(line -> isTypeA(line), Collectors.toList(), Collectors.counting()));
List<String> matching=p.a;
long nonMatching=p.b;

The collector is parallel friendly and allows arbitrarily complex delegate collectors, but note that with the current implementation, the stream returned by Files.lines might not perform so well with parallel processing, compare to “Reader#lines() parallelizes badly due to nonconfigurable batch size policy in its spliterator”. Improvements are scheduled for the Java 9 release.

The way I'd deal with this is not to split this up at all, but rather, write

Files.lines(path)
   .map(line -> {
      if (condition(line)) {
        return doThingA(line);
      } else {
        return doThingB(line);
      }
   })...

Details vary depending on exactly what you want to do and how you plan to do it.

Here's an approach (which ignores the cautions about forcing conditional processing into a stream) that wraps a predicate and consumer into a single predicate-with-side-effect:

public static class StreamProc {

    public static <T> Predicate<T> process( Predicate<T> condition, Consumer<T> operation ) {
        Predicate<T> p = t -> { operation.accept(t); return false; };
        return (t) -> condition.test(t) ? p.test(t) : true;
    }

}

Then filter the stream:

someStream
    .filter( StreamProc.process( cond1, op1 ) )
    .filter( StreamProc.process( cond2, op2 ) )
    ...
    .collect( ... )

Elements remaining in the stream have not yet been processed.

For example, a typical filesystem traversal using external iteration looks like

File[] files = dir.listFiles();
for ( File f : files ) {
    if ( f.isDirectory() ) {
        this.processDir( f );
    } else if ( f.isFile() ) {
        this.processFile( f );
    } else {
        this.processErr( f );
    }
}

With streams and internal iteration this becomes

Arrays.stream( dir.listFiles() )
    .filter( StreamProc.process( f -> f.isDirectory(), this::processDir ) )
    .filter( StreamProc.process( f -> f.isFile(), this::processFile ) )
    .forEach( f -> this::processErr );

I would like Stream to implement the process method directly. Then we could have

Arrays.stream( dir.listFiles() )
    .process( f -> f.isDirectory(), this::processDir ) )
    .process( f -> f.isFile(), this::processFile ) )
    .forEach( f -> this::processErr );

Thoughts?

It seems that in reality you do want to process each line, but process it differently based on some condition (type).

I think this is more or less functional way to implement it would be:

public static void main(String[] args) {
    Arrays.stream(new int[] {1,2,3,4}).map(i -> processor(i).get()).forEach(System.out::println);
}

static Supplier<Integer> processor(int i) {
    return tellType(i) ? () -> processTypeA(i) : () -> processTypeB(i);
}

static boolean tellType(int i) {
    return i % 2 == 0;
}

static int processTypeA(int i) {
    return i * 100;
}

static int processTypeB(int i) {
    return i * 10;
}

Well, you can simply do

Counter counter = new Counter();
File.lines(path)
    .forEach(line -> {
        if (isTypeA(line)) {
            processTypeA(line);
        }
        else {
            counter.increment();
        }
    });

Not very functional-style, but it does it in a similar way as your example. Of course, if parallel, both Counter.increment() and processTypeA() have to be thread-safe.

@tom

What about this:

Arrays.stream( dir.listFiles() )
    .peek(  f -> { if(f.isDirectory()) { processDir(f); }} )
    .peek(  f -> { if(f.isFile())      { processFile(f);}}) )
    .forEach( f -> this::processErr );