Java 8 introduced a Stream class that resembles Scala\'s Stream, a powerful lazy construct using which it is possible to do something like this very concisely:
Even if you hadn’t the problem that you can’t split an IntStream
, you code didn’t work because you are invoking your sieve
method recursively instead of lazily. So you had an infinity recursion before you could query your resulting stream for the first value.
Splitting an IntStream s
into a head and a tail IntStream
(which has not yet consumed) is possible:
PrimitiveIterator.OfInt it = s.iterator();
int head = it.nextInt();
IntStream tail = IntStream.generate(it::next).filter(i -> i % head != 0);
At this place you need a construct of invoking sieve
on the tail lazily. Stream
does not provide that; concat
expects existing stream instances as arguments and you can’t construct a stream invoking sieve
lazily with a lambda expression as lazy creation works with mutable state only which lambda expressions do not support. If you don’t have a library implementation hiding the mutable state you have to use a mutable object. But once you accept the requirement of mutable state, the solution can be even easier than your first approach:
IntStream primes = from(2).filter(i -> p.test(i)).peek(i -> p = p.and(v -> v % i != 0));
IntPredicate p = x -> true;
IntStream from(int n)
{
return IntStream.iterate(n, m -> m + 1);
}
This will recursively create a filter but in the end it doesn’t matter whether you create a tree of IntPredicate
s or a tree of IntStream
s (like with your IntStream.concat
approach if it did work). If you don’t like the mutable instance field for the filter you can hide it in an inner class (but not in a lambda expression…).
If you don't mind using 3rd party libraries cyclops-streams, I library I wrote has a number of potential solutions.
The StreamUtils class has large number of static methods for working directly with java.util.stream.Streams
including headAndTail
.
HeadAndTail<Integer> headAndTail = StreamUtils.headAndTail(Stream.of(1,2,3,4));
int head = headAndTail.head(); //1
Stream<Integer> tail = headAndTail.tail(); //Stream[2,3,4]
The Streamable class represents a replayable Stream
and works by building a lazy, caching intermediate data-structure. Because it is caching and repayable - head and tail can be implemented directly and separately.
Streamable<Integer> replayable= Streamable.fromStream(Stream.of(1,2,3,4));
int head = repayable.head(); //1
Stream<Integer> tail = replayable.tail(); //Stream[2,3,4]
cyclops-streams also provides a sequential Stream
extension that in turn extends jOOλ and has both Tuple
based (from jOOλ) and domain object (HeadAndTail) solutions for head and tail extraction.
SequenceM.of(1,2,3,4)
.splitAtHead(); //Tuple[1,SequenceM[2,3,4]
SequenceM.of(1,2,3,4)
.headAndTail();
Update per Tagir's request -> A Java version of the Scala sieve using SequenceM
public void sieveTest(){
sieve(SequenceM.range(2, 1_000)).forEach(System.out::println);
}
SequenceM<Integer> sieve(SequenceM<Integer> s){
return s.headAndTailOptional().map(ht ->SequenceM.of(ht.head())
.appendStream(sieve(ht.tail().filter(n -> n % ht.head() != 0))))
.orElse(SequenceM.of());
}
And another version via Streamable
public void sieveTest2(){
sieve(Streamable.range(2, 1_000)).forEach(System.out::println);
}
Streamable<Integer> sieve(Streamable<Integer> s){
return s.size()==0? Streamable.of() : Streamable.of(s.head())
.appendStreamable(sieve(s.tail()
.filter(n -> n % s.head() != 0)));
}
Note - neither Streamable
of SequenceM
have an Empty implementation - hence the size check for Streamable
and the use of headAndTailOptional
.
Finally a version using plain java.util.stream.Stream
import static com.aol.cyclops.streams.StreamUtils.headAndTailOptional;
public void sieveTest(){
sieve(IntStream.range(2, 1_000).boxed()).forEach(System.out::println);
}
Stream<Integer> sieve(Stream<Integer> s){
return headAndTailOptional(s).map(ht ->Stream.concat(Stream.of(ht.head())
,sieve(ht.tail().filter(n -> n % ht.head() != 0))))
.orElse(Stream.of());
}
Another update - a lazy iterative based on @Holger's version using objects rather than primitives (note a primitive version is also possible)
final Mutable<Predicate<Integer>> predicate = Mutable.of(x->true);
SequenceM.iterate(2, n->n+1)
.filter(i->predicate.get().test(i))
.peek(i->predicate.mutate(p-> p.and(v -> v%i!=0)))
.limit(100000)
.forEach(System.out::println);
You can essentially implement it like this:
static <T> Tuple2<Optional<T>, Seq<T>> splitAtHead(Stream<T> stream) {
Iterator<T> it = stream.iterator();
return tuple(it.hasNext() ? Optional.of(it.next()) : Optional.empty(), seq(it));
}
In the above example, Tuple2
and Seq
are types borrowed from jOOλ, a library that we developed for jOOQ integration tests. If you don't want any additional dependencies, you might as well implement them yourself:
class Tuple2<T1, T2> {
final T1 v1;
final T2 v2;
Tuple2(T1 v1, T2 v2) {
this.v1 = v1;
this.v2 = v2;
}
static <T1, T2> Tuple2<T1, T2> tuple(T1 v1, T2 v2) {
return new Tuple<>(v1, v2);
}
}
static <T> Tuple2<Optional<T>, Stream<T>> splitAtHead(Stream<T> stream) {
Iterator<T> it = stream.iterator();
return tuple(
it.hasNext() ? Optional.of(it.next()) : Optional.empty,
StreamSupport.stream(Spliterators.spliteratorUnknownSize(
it, Spliterator.ORDERED
), false)
);
}
If you want to get head of a stream, just:
IntStream.range(1, 5).first();
If you want to get tail of a stream, just:
IntStream.range(1, 5).skip(1);
If you want to get both head and tail of a stream, just:
IntStream s = IntStream.range(1, 5);
int head = s.head();
IntStream tail = s.tail();
If you want to find the prime, just:
LongStream.range(2, n)
.filter(i -> LongStream.range(2, (long) Math.sqrt(i) + 1).noneMatch(j -> i % j == 0))
.forEach(N::println);
If you want to know more, go to get AbacusUtil
Declaration: I'm the developer of AbacusUtil.
My StreamEx library has now headTail() operation which solves the problem:
public static StreamEx<Integer> sieve(StreamEx<Integer> input) {
return input.headTail((head, tail) ->
sieve(tail.filter(n -> n % head != 0)).prepend(head));
}
The headTail
method takes a BiFunction
which will be executed at most once during the stream terminal operation execution. So this implementation is lazy: it does not compute anything until traversal starts and computes only as much prime numbers as requested. The BiFunction
receives a first stream element head
and the stream of the rest elements tail
and can modify the tail
in any way it wants. You may use it with predefined input:
sieve(IntStreamEx.range(2, 1000).boxed()).forEach(System.out::println);
But infinite stream work as well
sieve(StreamEx.iterate(2, x -> x+1)).takeWhile(x -> x < 1000)
.forEach(System.out::println);
// Not the primes till 1000, but 1000 first primes
sieve(StreamEx.iterate(2, x -> x+1)).limit(1000).forEach(System.out::println);
There's also alternative solution using headTail
and predicate concatenation:
public static StreamEx<Integer> sieve(StreamEx<Integer> input, IntPredicate isPrime) {
return input.headTail((head, tail) -> isPrime.test(head)
? sieve(tail, isPrime.and(n -> n % head != 0)).prepend(head)
: sieve(tail, isPrime));
}
sieve(StreamEx.iterate(2, x -> x+1), i -> true).limit(1000).forEach(System.out::println);
It interesting to compare recursive solutions: how many primes they capable to generate.
@John McClean solution (StreamUtils
)
John McClean solutions are not lazy: you cannot feed them with infinite stream. So I just found by trial-and-error the maximal allowed upper bound (17793
) (after that StackOverflowError occurs):
public void sieveTest(){
sieve(IntStream.range(2, 17793).boxed()).forEach(System.out::println);
}
@John McClean solution (Streamable
)
public void sieveTest2(){
sieve(Streamable.range(2, 39990)).forEach(System.out::println);
}
Increasing upper limit above 39990
results in StackOverflowError.
@frhack solution (LazySeq
)
LazySeq<Integer> ints = integers(2);
LazySeq primes = sieve(ints); // sieve method from @frhack answer
primes.forEach(p -> System.out.println(p));
Result: stuck after prime number = 53327
with enormous heap allocation and garbage collection taking more than 90%. It took several minutes to advance from 53323 to 53327, so waiting more seems impractical.
@vidi solution
Prime.stream().forEach(System.out::println);
Result: StackOverflowError after prime number = 134417
.
My solution (StreamEx)
sieve(StreamEx.iterate(2, x -> x+1)).forEach(System.out::println);
Result: StackOverflowError after prime number = 236167
.
@frhack solution (rxjava
)
Observable<Integer> primes = Observable.from(()->primesStream.iterator());
primes.forEach((x) -> System.out.println(x.toString()));
Result: StackOverflowError after prime number = 367663
.
@Holger solution
IntStream primes=from(2).filter(i->p.test(i)).peek(i->p=p.and(v->v%i!=0));
primes.forEach(System.out::println);
Result: StackOverflowError after prime number = 368089
.
My solution (StreamEx with predicate concatenation)
sieve(StreamEx.iterate(2, x -> x+1), i -> true).forEach(System.out::println);
Result: StackOverflowError after prime number = 368287
.
So three solutions involving predicate concatenation win, because each new condition adds only 2 more stack frames. I think, the difference between them is marginal and should not be considered to define a winner. However I like my first StreamEx solution more as it more similar to Scala code.
Here is another recipe using the way suggested by Holger. It use RxJava just to add the possibility to use the take(int) method and many others.
package com.company;
import rx.Observable;
import java.util.function.IntPredicate;
import java.util.stream.IntStream;
public class Main {
public static void main(String[] args) {
final IntPredicate[] p={(x)->true};
IntStream primesStream=IntStream.iterate(2,n->n+1).filter(i -> p[0].test(i)).peek(i->p[0]=p[0].and(v->v%i!=0) );
Observable primes = Observable.from(()->primesStream.iterator());
primes.take(10).forEach((x) -> System.out.println(x.toString()));
}
}