Given a stream such as { 0, 1, 2, 3, 4 },
how can I most elegantly transform it into given form:
{ new Pair(0, 1), new Pair(1, 2), new Pair(2, 3), new Pair(3, 4) }
(assuming, of course, I've defined class Pair)?
Edit: This isn't strictly about ints or primitive streams. The answer should be general for a stream of any type.
The Java 8 streams library is primarily geared toward splitting streams into smaller chunks for parallel processing, so stateful pipeline stages are quite limited, and doing things like getting the index of the current stream element and accessing adjacent stream elements are not supported.
A typical way to solve these problems, with some limitations, of course, is to drive the stream by indexes and rely on having the values being processed in some random-access data structure like an ArrayList from which the elements can be retrieved. If the values were in arrayList, one could generate the pairs as requested by doing something like this:
IntStream.range(1, arrayList.size())
.mapToObj(i -> new Pair(arrayList.get(i-1), arrayList.get(i)))
.forEach(System.out::println);
Of course the limitation is that the input cannot be an infinite stream. This pipeline can be run in parallel, though.
My StreamEx library which extends standard streams provides a pairMap method for all stream types. For primitive streams it does not change the stream type, but can be used to make some calculations. Most common usage is to calculate differences:
int[] pairwiseDiffs = IntStreamEx.of(input).pairMap((a, b) -> (b-a)).toArray();
For object stream you can create any other object type. My library does not provide any new user-visible data structures like Pair (that's the part of library concept). However if you have your own Pair class and want to use it, you can do the following:
Stream<Pair> pairs = IntStreamEx.of(input).boxed().pairMap(Pair::new);
Or if you already have some Stream:
Stream<Pair> pairs = StreamEx.of(stream).pairMap(Pair::new);
This functionality is implemented using custom spliterator. It has quite low overhead and can parallelize nicely. Of course it works with any stream source, not just random access list/array like many other solutions. In many tests it performs really well. Here's a JMH benchmark where we find all input values preceding a larger value using different approaches (see this question).
You can do this with the Stream.reduce() method (I haven't seen any other answers using this technique).
public static <T> List<Pair<T, T>> consecutive(List<T> list) {
List<Pair<T, T>> pairs = new LinkedList<>();
list.stream().reduce((a, b) -> {
pairs.add(new Pair<>(a, b));
return b;
});
return pairs;
}
This is not elegant, it's a hackish solution, but works for infinite streams
Stream<Pair> pairStream = Stream.iterate(0, (i) -> i + 1).map( // natural numbers
new Function<Integer, Pair>() {
Integer previous;
@Override
public Pair apply(Integer integer) {
Pair pair = null;
if (previous != null) pair = new Pair(previous, integer);
previous = integer;
return pair;
}
}).skip(1); // drop first null
Now you can limit your stream to the length you want
pairStream.limit(1_000_000).forEach(i -> System.out.println(i));
P.S. I hope there is better solution, something like clojure (partition 2 1 stream)
I've implemented a spliterator wrapper which takes every n elements T from the original spliterator and produces List<T>:
public class ConsecutiveSpliterator<T> implements Spliterator<List<T>> {
private final Spliterator<T> wrappedSpliterator;
private final int n;
private final Deque<T> deque;
private final Consumer<T> dequeConsumer;
public ConsecutiveSpliterator(Spliterator<T> wrappedSpliterator, int n) {
this.wrappedSpliterator = wrappedSpliterator;
this.n = n;
this.deque = new ArrayDeque<>();
this.dequeConsumer = deque::addLast;
}
@Override
public boolean tryAdvance(Consumer<? super List<T>> action) {
deque.pollFirst();
fillDeque();
if (deque.size() == n) {
List<T> list = new ArrayList<>(deque);
action.accept(list);
return true;
} else {
return false;
}
}
private void fillDeque() {
while (deque.size() < n && wrappedSpliterator.tryAdvance(dequeConsumer))
;
}
@Override
public Spliterator<List<T>> trySplit() {
return null;
}
@Override
public long estimateSize() {
return wrappedSpliterator.estimateSize();
}
@Override
public int characteristics() {
return wrappedSpliterator.characteristics();
}
}
Following method may be used to create a consecutive stream:
public <E> Stream<List<E>> consecutiveStream(Stream<E> stream, int n) {
Spliterator<E> spliterator = stream.spliterator();
Spliterator<List<E>> wrapper = new ConsecutiveSpliterator<>(spliterator, n);
return StreamSupport.stream(wrapper, false);
}
Sample usage:
consecutiveStream(Stream.of(0, 1, 2, 3, 4, 5), 2)
.map(list -> new Pair(list.get(0), list.get(1)))
.forEach(System.out::println);
You can do this in cyclops-react (I contribute to this library), using the sliding operator.
LazyFutureStream.of( 0, 1, 2, 3, 4 )
.sliding(2)
.map(Pair::new);
Or
ReactiveSeq.of( 0, 1, 2, 3, 4 )
.sliding(2)
.map(Pair::new);
Assuming the Pair constructor can accept a Collection with 2 elements.
If you wanted to group by 4, and increment by 2 that is also supported.
ReactiveSeq.rangeLong( 0L,Long.MAX_VALUE)
.sliding(4,2)
.forEach(System.out::println);
Equivalant static methods for creating a sliding view over java.util.stream.Stream are also provided in cyclops-streams StreamUtils class.
StreamUtils.sliding(Stream.of(1,2,3,4),2)
.map(Pair::new);
Note :- for single-threaded operation ReactiveSeq would be more appropriate. LazyFutureStream extends ReactiveSeq but is primarily geared for concurrent / parallel use (it is a Stream of Futures).
LazyFutureStream extends ReactiveSeq which extends Seq from the awesome jOOλ (which extends java.util.stream.Stream), so the solutions Lukas' presents would also work with either Stream type. For anyone interested the primary differences between the window / sliding operators are the obvious relative power / complexity trade off and suitability for use with infinite streams (sliding doesn't consume the stream, but buffers as it flows).
Streams.zip(..) is available in Guava, for those who depend on it.
Example:
Streams.zip(list.stream(),
list.stream().skip(1),
(a, b) -> System.out.printf("%s %s\n", a, b));
If you're willing to use a third party library and don't need parallelism, then jOOλ offers SQL-style window functions as follows
System.out.println(
Seq.of(0, 1, 2, 3, 4)
.window()
.filter(w -> w.lead().isPresent())
.map(w -> tuple(w.value(), w.lead().get())) // alternatively, use your new Pair() class
.toList()
);
Yielding
[(0, 1), (1, 2), (2, 3), (3, 4)]
The lead() function accesses the next value in traversal order from the window.
A question in the comments was asking for a more general solution, where not pairs but n-tuples (or possibly lists) should be collected. Here's thus an alternative approach:
int n = 3;
System.out.println(
Seq.of(0, 1, 2, 3, 4)
.window(0, n - 1)
.filter(w -> w.count() == n)
.map(w -> w.window().toList())
.toList()
);
Yielding a list of lists
[[0, 1, 2], [1, 2, 3], [2, 3, 4]]
Without the filter(w -> w.count() == n), the result would be
[[0, 1, 2], [1, 2, 3], [2, 3, 4], [3, 4], [4]]
Disclaimer: I work for the company behind jOOλ
The proton-pack library provides the windowed functionnality. Given a Pair class and a Stream, you can do it like this:
Stream<Integer> st = Stream.iterate(0 , x -> x + 1);
Stream<Pair<Integer, Integer>> pairs = StreamUtils.windowed(st, 2, 1)
.map(l -> new Pair<>(l.get(0), l.get(1)))
.moreStreamOps(...);
Now the pairs stream contains:
(0, 1)
(1, 2)
(2, 3)
(3, 4)
(4, ...) and so on
The operation is essentially stateful so not really what streams are meant to solve - see the "Stateless Behaviors" section in the javadoc:
The best approach is to avoid stateful behavioral parameters to stream operations entirely
One solution here is to introduce state in your stream through an external counter, although it will only work with a sequential stream.
public static void main(String[] args) {
Stream<String> strings = Stream.of("a", "b", "c", "c");
AtomicReference<String> previous = new AtomicReference<>();
List<Pair> collect = strings.map(n -> {
String p = previous.getAndSet(n);
return p == null ? null : new Pair(p, n);
})
.filter(p -> p != null)
.collect(toList());
System.out.println(collect);
}
static class Pair<T> {
private T left, right;
Pair(T left, T right) { this.left = left; this.right = right; }
@Override public String toString() { return "{" + left + "," + right + '}'; }
}
We can use RxJava (very powerful reactive extension library)
IntStream intStream = IntStream.iterate(1, n -> n + 1);
Observable<List<Integer>> pairObservable = Observable.from(intStream::iterator).buffer(2,1);
pairObservable.take(10).forEach(b -> {
b.forEach(n -> System.out.println(n));
System.out.println();
});
The buffer operator transforms an Observable that emits items into an Observable that emits buffered collections of those items..
In your case, I would write my custom IntFunction which keeps track of the last int passed and use that to map the original IntStream.
import java.util.function.IntFunction;
import java.util.stream.IntStream;
public class PairFunction implements IntFunction<PairFunction.Pair> {
public static class Pair {
private final int first;
private final int second;
public Pair(int first, int second) {
this.first = first;
this.second = second;
}
@Override
public String toString() {
return "[" + first + "|" + second + "]";
}
}
private int last;
private boolean first = true;
@Override
public Pair apply(int value) {
Pair pair = !first ? new Pair(last, value) : null;
last = value;
first = false;
return pair;
}
public static void main(String[] args) {
IntStream intStream = IntStream.of(0, 1, 2, 3, 4);
final PairFunction pairFunction = new PairFunction();
intStream.mapToObj(pairFunction)
.filter(p -> p != null) // filter out the null
.forEach(System.out::println); // display each Pair
}
}
An elegant solution would be to use zip. Something like:
List<Integer> input = Arrays.asList(0, 1, 2, 3, 4);
Stream<Pair> pairStream = Streams.zip(input.stream(),
input.stream().substream(1),
(a, b) -> new Pair(a, b)
);
This is pretty concise and elegant, however it uses a list as an input. An infinite stream source cannot be processed this way.
Another (lot more troublesome) issue is that zip together with the entire Streams class has been lately removed from the API. The above code only works with b95 or older releases. So with the latest JDK I would say there is no elegant FP style solution and right now we can just hope that in some way zip will be reintroduced to the API.
For calculating successive differences in the time (x-values) of a time-series, I use the stream's collect(...) method:
final List< Long > intervals = timeSeries.data().stream()
.map( TimeSeries.Datum::x )
.collect( DifferenceCollector::new, DifferenceCollector::accept, DifferenceCollector::combine )
.intervals();
Where the DifferenceCollector is something like this:
public class DifferenceCollector implements LongConsumer
{
private final List< Long > intervals = new ArrayList<>();
private Long lastTime;
@Override
public void accept( final long time )
{
if( Objects.isNull( lastTime ) )
{
lastTime = time;
}
else
{
intervals.add( time - lastTime );
lastTime = time;
}
}
public void combine( final DifferenceCollector other )
{
intervals.addAll( other.intervals );
lastTime = other.lastTime;
}
public List< Long > intervals()
{
return intervals;
}
}
You could probably modify this to suit your needs.
I finally figured out a way of tricking the Stream.reduce to be able to neatly deal with pairs of values; there are a multitude of use cases that require this facility which does not appear naturally in JDK 8:
public static int ArithGeo(int[] arr) {
//Geometric
List<Integer> diffList = new ArrayList<>();
List<Integer> divList = new ArrayList<>();
Arrays.stream(arr).reduce((left, right) -> {
diffList.add(right-left);
divList.add(right/left);
return right;
});
//Arithmetic
if(diffList.stream().distinct().count() == 1) {
return 1;
}
//Geometric
if(divList.stream().distinct().count() == 1) {
return 2;
}
return -1;
}
The trick i use is the return right; statement.
This is an interesting problem. Is my hybrid attempt below any good?
public static void main(String[] args) {
List<Integer> list = Arrays.asList(1, 2, 3);
Iterator<Integer> first = list.iterator();
first.next();
if (first.hasNext())
list.stream()
.skip(1)
.map(v -> new Pair(first.next(), v))
.forEach(System.out::println);
}
I believe it does not lend itself to parallel processing, and hence may be disqualified.
As others have observed, there is, due to the nature of the problem, some statefulness required.
I was faced with a similar problem, in which I wanted what was essentially the Oracle SQL function LEAD. My attempt to implement that is below.
/**
* Stream that pairs each element in the stream with the next subsequent element.
* The final pair will have only the first item, the second will be null.
*/
<T> Spliterator<Pair<T>> lead(final Stream<T> stream)
{
final Iterator<T> input = stream.sequential().iterator();
final Iterable<Pair<T>> iterable = () ->
{
return new Iterator<Pair<T>>()
{
Optional<T> current = getOptionalNext(input);
@Override
public boolean hasNext()
{
return current.isPresent();
}
@Override
public Pair<T> next()
{
Optional<T> next = getOptionalNext(input);
final Pair<T> pair = next.isPresent()
? new Pair(current.get(), next.get())
: new Pair(current.get(), null);
current = next;
return pair;
}
};
};
return iterable.spliterator();
}
private <T> Optional<T> getOptionalNext(final Iterator<T> iterator)
{
return iterator.hasNext()
? Optional.of(iterator.next())
: Optional.empty();
}
You can achieve that by using a bounded queue to store elements which flows through the stream (which is basing on the idea which I described in detail here: Is it possible to get next element in the Stream?)
Belows example first defines instance of BoundedQueue class which will store elements going through the stream (if you don't like idea of extending the LinkedList, refer to link mentioned above for alternative and more generic approach). Later you just combine two subsequent elements into instance of Pair:
public class TwoSubsequentElems {
public static void main(String[] args) {
List<Integer> input = new ArrayList<Integer>(asList(0, 1, 2, 3, 4));
class BoundedQueue<T> extends LinkedList<T> {
public BoundedQueue<T> save(T curElem) {
if (size() == 2) { // we need to know only two subsequent elements
pollLast(); // remove last to keep only requested number of elements
}
offerFirst(curElem);
return this;
}
public T getPrevious() {
return (size() < 2) ? null : getLast();
}
public T getCurrent() {
return (size() == 0) ? null : getFirst();
}
}
BoundedQueue<Integer> streamHistory = new BoundedQueue<Integer>();
final List<Pair<Integer>> answer = input.stream()
.map(i -> streamHistory.save(i))
.filter(e -> e.getPrevious() != null)
.map(e -> new Pair<Integer>(e.getPrevious(), e.getCurrent()))
.collect(Collectors.toList());
answer.forEach(System.out::println);
}
}
list.stream().map(i -> new Pair(i, i+1));– aepurnietMap.Entryas a Pair class. (Granted, some might consider that a hack, but using a built-in class is handy.) – Basil Bourque