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Releases: ReactiveX/RxJava

1.0.0-RC1

30 Aug 06:22
@benjchristensen benjchristensen
v1.0.0-rc.1
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1.0.0-RC1 Pre-release
Pre-release

The first release candidate for 1.0.0.

This is the same code as version 0.20.2 except:

  • all deprecated methods and types are deleted
  • now published to groupId io.reactivex instead of com.netflix.rxjava
  • artifactId is now rxjava instead of rxjava-core
io.reactivex:rxjava:1.0.0-rc.1
  • all sub-projects are separated into their own projects and no longer released along with RxJava

The artifacts can be found on maven Central at: http://repo1.maven.org/maven2/io/reactivex/rxjava/1.0.0-rc.1/

Artifacts: Maven Central

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0.20.2

28 Aug 00:07
@benjchristensen benjchristensen
0.20.2
76d0918
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0.20.2
  • Pull 1637 Optimize single BlockingObservable operations

Artifacts: Maven Central

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0.20.1

27 Aug 17:30
@benjchristensen benjchristensen
0.20.1
2052c25
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0.20.1
  • Pull 1631 Handle Fatal Exceptions in doOn* operators
  • Pull 1625 RxScala: Mark superfluous from/empty methods with scheduler parameter as deprecated
  • Pull 1623 RxScala: Add more operators to match RxJava
  • Pull 1632 Composite Exception - Circular Reference Handling

Artifacts: Maven Central

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0.20.0

19 Aug 06:56
@benjchristensen benjchristensen
0.20.0
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0.20.0

RxJava 0.20.0 is a major release that adds "reactive pull" support for backpressure along with several other enhancements leading into the 1.0 release.

Reactive Pull for Backpressure

Solutions for backpressure was the major focus of this release. A "reactive pull" implementation was implemented. Documentation on this and other options for backpressure are found in the wiki: https://github.com/ReactiveX/RxJava/wiki/Backpressure

The reactive pull solution evolved out of several prototypes and interaction with many people over the months.

Signature Changes

A new type Producer has been added:

public interface Producer {
    public void request(long n);
}

The Subscriber type now has these methods added:

public abstract class Subscriber<T> implements Observer<T>, Subscription {
    public void onStart();
    protected final void request(long n);
    public final void setProducer(Producer producer);
}

Examples

This trivial example shows requesting values one at a time:

Observable.from(1, 2, 3, 4).subscribe(new Subscriber<Integer>() {

    @Override
    public void onStart() {
        // on start this tells it to request 1
        // otherwise it defaults to request(Long.MAX_VALUE)
        request(1);
    }

    @Override
    public void onCompleted() {
    }

    @Override
    public void onError(Throwable e) {
    }

    @Override
    public void onNext(Integer t) {
        System.out.println(t);
        // as each onNext is consumed, request another 
        // otherwise the Producer will not send more
        request(1);
    }

});

The OnSubscribeFromIterable operator shows how an Iterable is consumed with backpressure.

Some hi-lights (modified for simplicity rather than performance and completeness):

public final class OnSubscribeFromIterable<T> implements OnSubscribe<T> {

    @Override
    public void call(final Subscriber<? super T> o) {
        final Iterator<? extends T> it = is.iterator();
        // instead of emitting directly to the Subscriber, it emits a Producer
        o.setProducer(new IterableProducer<T>(o, it));
    }

    private static final class IterableProducer<T> implements Producer {

        public void request(long n) {
            int _c = requested.getAndAdd(n);
            if (_c == 0) {
                while (it.hasNext()) {
                    if (o.isUnsubscribed()) {
                        return;
                    }
                    T t = it.next();
                    o.onNext(t);
                    if (requested.decrementAndGet() == 0) {
                        // we're done emitting the number requested so return
                        return;
                    }
                }

                o.onCompleted();
            }

        }
    }
}

The observeOn operator is a sterotypical example of queuing on one side of a thread and draining on the other, now with backpressure.

private static final class ObserveOnSubscriber<T> extends Subscriber<T> {
        @Override
        public void onStart() {
            // signal that this is an async operator capable of receiving this many
            request(RxRingBuffer.SIZE);
        }

        @Override
        public void onNext(final T t) {
            try {
                // enqueue
                queue.onNext(t);
            } catch (MissingBackpressureException e) {
                // fail if the upstream has not obeyed our backpressure requests
                onError(e);
                return;
            }
            // attempt to schedule draining if needed
            schedule();
        }

        // the scheduling polling will then drain the queue and invoke `request(n)` to request more after draining
}

Many use cases will be able to use Observable.from, Observable.onBackpressureDrop and Observable.onBackpressureBuffer to achieve "reactive pull backpressure" without manually implementing Producer logic. Also, it is optional to make an Observable support backpressure. It can remain completely reactive and just push events as it always has. Most uses of RxJava this works just fine. If backpressure is needed then it can be migrated to use a Producer or several other approaches to flow control exist such as throttle, sample, debounce, window, buffer, onBackpressureBuffer, and onBackpressureDrop.

The wiki provides further documentation.

Relation to Reactive Streams

Contributors to RxJava are involved in defining the Reactive Streams spec. RxJava 1.0 is trying to comply with the semantic rules but is not attempting to comply with the type signatures. It will however have a separate module that acts as a bridge between the RxJava Observable and the Reactive Stream types.

The reasons for this are:

  • Rx has Observer.onCompleted whereas Reactive Streams has onComplete. This is a massive breaking change to remove a "d".
  • The RxJava Subscription is used also a "Closeable"/"Disposable" and it does not work well to make it now also be used for request(n), hence the separate type Producer in RxJava. It was attempted to reuse rx.Subscription but it couldn't be done without massive breaking changes.
  • Reactive Streams uses onSubscribe(Subscription s) whereas RxJava injects the Subscription as the Subscriber. Again, this change could not be done without major breaking changes.
  • RxJava 1.0 needs to be backwards compatible with the major Rx contracts established during the 0.x roadmap.

Considering these things, the major semantics of request(long n) for backpressure are compatible and this will allow interop with a bridge between the interfaces.

New Features

Compose/Transformer

The compose operator is similar to lift but allows custom operator implementations that are chaining Observable operators whereas lift is directly implementing the raw Subscriber logic.

Here is a trival example demonstrating how using compose is a better option than lift when existing Observable operators can be used to achieve the custom behavior.

import rx.Observable;
import rx.Observable.Operator;
import rx.Observable.Transformer;
import rx.Subscriber;

public class ComposeExample {

    public static void main(String[] args) {
        Observable.just("hello").compose(appendWorldTransformer()).forEach(System.out::println);
        Observable.just("hello").lift(appendWorldOperator()).forEach(System.out::println);
    }

    // if existing operators can be used, compose with Transformer is ideal
    private static Transformer<? super String, String> appendWorldTransformer() {
        return o -> o.map(s -> s + " world!").finallyDo(() -> {
            System.out.println("  some side-effect");
        });
    }

    // whereas lift is more low level
    private static Operator<? super String, String> appendWorldOperator() {
        return new Operator<String, String>() {

            @Override
            public Subscriber<? super String> call(Subscriber<? super String> child) {
                return new Subscriber<String>(child) {

                    @Override
                    public void onCompleted() {
                        child.onCompleted();
                    }

                    @Override
                    public void onError(Throwable e) {
                        child.onError(e);
                    }

                    @Override
                    public void onNext(String t) {
                        child.onNext(t + " world!");
                        System.out.println("  some side-effect");
                    }

                };
            }

        };
    }
}
retryWhen/repeatWhen

New operators retryWhen and repeatWhen were added which offer support for more advanced recursion such as retry with exponential backoff.

Here is an example that increases delay between each retry:

Observable.create((Subscriber<? super String> s) -> {
    System.out.println("subscribing");
    s.onError(new RuntimeException("always fails"));
}).retryWhen(attempts -> {
    return attempts.zipWith(Observable.range(1, 3), (n, i) -> i).flatMap(i -> {
        System.out.println("delay retry by " + i + " second(s)");
        return Observable.timer(i, TimeUnit.SECONDS);
    });
}).toBlocking().forEach(System.out::println);

Breaking Changes

The use of Producer has been added in such a way that it is optional and additive, but some operators that used to have unbounded queues are now bounded. This means that if a source Observable emits faster than the Observer can consume them, a MissingBackpressureException can be emitted via onError.

This semantic change can break existing code.

There are two ways of resolving this:

  1. Modify the source Observable to use Producer and support backpressure.
  2. Use newly added operators such as onBackpressureBuffer or onBackpressureDrop to choose a strategy for the source Observable of how to behave when it emits more data than the consuming Observer is capable of handling. Use of onBackpressureBuffer effectively returns it to having an unbounded buffer and behaving like version 0.19 or earlier.

Example:

sourceObservable.onBackpressureBuffer().subscribe(slowConsumer);

Deprecations

Various methods, operators or classes have been deprecated and will be removed in 1.0. Primarily they have been done to remove ambiguity, remove nuanced functionality that is easy to use wrong, clear out superfluous methods and eliminate cruft that was add...

Read more
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0.20.0-RC6

14 Aug 22:06
@benjchristensen benjchristensen
0.20.0-RC6
f31e03f
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0.20.0-RC6 Pre-release
Pre-release

Further fixes and enhancements bringing us close to completing 0.20.0 and almost ready for 1.0.

A more major change in this release is the deprecation of Observable.from(T). The full discussion can be seen in #1563.

Artifacts: Maven Central

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0.20.0-RC5

13 Aug 17:55
@benjchristensen benjchristensen
0.20.0-RC5
5ec4686
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0.20.0-RC5 Pre-release
Pre-release

Version 0.20.0-RC5 updates parallel, buffer(size), switchOnNext, repeat, and retry to support "reactive pull" backpressure. It adds a groupBy overload with an element selector, a new compose method as an alternative to lift for custom operators, fixes bugs and other general improvements.

There are still oustanding items being tracked for 0.20 that need to be completed for the final release.

Artifacts: Maven Central

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0.20.0-RC4

31 Jul 15:39
@benjchristensen benjchristensen
0.20.0-RC4
df37e5f
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0.20.0-RC4 Pre-release
Pre-release

Version 0.20.0-RC4 continues bug fixes and completing work related to "reactive pull" backpressure. This release updates amb and concat to connect the backpressure request.

Internal uses of RxRingBuffer migrated to using SpmcArrayQueue which significantly reduces object allocations. See #1526 for details.

The multicast operators were updated to use a Subject factory so that Observable sequences can be reused. See #1515 for details.

  • Pull 1534 Concat Backpressure
  • Pull 1533 Amb + Backpressure
  • Pull 1527 Failing unit test for reduce, showing it does not implement backpressure correctly
  • Pull 1528 Add operators to create Observables from BroadcastReceiver (rebased)
  • Pull 1523 Fix issue #1522: takeLast
  • Pull 1530 Fix the unbounded check for merge
  • Pull 1526 Restore use of SpmcArrayQueue in RxRingBuffer
  • Pull 1468 RxScala: Update CompletenessTest.scala
  • Pull 1515 Support Subject Factory with Multicast
  • Pull 1518 Fix typos in javadoc comments
  • Pull 1521 Fix toIterator Exception Handling
  • Pull 1520 Fix non-deterministic RxRingBuffer test

Artifacts: Maven Central

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0.20.0-RC3

25 Jul 19:30
@benjchristensen benjchristensen
0.20.0-RC3
92dbd43
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0.20.0-RC3 Pre-release
Pre-release

Version 0.20.0-RC3 preview release fixes several bugs related to backpressure and adds retryWhen, repeatWhen for more advanced recursion use cases like retry with exponential backoff.

This version passed the Netflix API production canary process. Please test this against your code to help us find any issues before we release 0.20.0.

Artifacts: Maven Central

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0.20.0-RC2

18 Jul 22:25
@benjchristensen benjchristensen
0.20.0-RC2
cb02b1c
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0.20.0-RC2 Pre-release
Pre-release

Version 0.20.0-RC2 preview release adds support for backpressure to the zip operators, fixes bugs and removes the Subscribe.onSetProducer method.

This means signature changes are modified to be:

The new type Producer ->

public interface Producer {
    public void request(long n);
}

New methods added to Subscriber ->

public abstract class Subscriber<T> implements Observer<T>, Subscription {
    public void onStart();
    protected final void request(long n);
    public final void setProducer(Producer producer);
}

Artifacts: Maven Central

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0.20.0-RC1

15 Jul 17:28
@benjchristensen benjchristensen
0.20.0-RC1
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0.20.0-RC1 Pre-release
Pre-release

Version 0.20.0-RC1 is a preview release that adds backpressure support to RxJava as per issue #1000. It has been done in a way that is mostly additive and most existing code will not be affected by these additions. A section below on "Breaking Changes" will discuss use cases that do break and how to deal with them.

This release has been tested successfully in Netflix production canaries, but that does not exercise all use cases or operators, nor does it leverage the newly added backpressure functionality (though the backpressure code paths are used).

Outstanding Work

  • The zip operator has not yet been upgraded to support backpressure. The work is almost done and it will be included in the next release.
  • Not all operators have yet been reviewed for whether they need to be changed in any way.
  • Temporal operators (like buffer, window, sample, etc) need to be modified to disable backpressure upstream (using request(Long.MAX_VALUE)) and a decision made about how downstream backpressure requests will be supported.
  • Ensure all code works on Android. New data structures rely on sun.misc.Unsafe but are conditionally used only when it is available. We need to ensure those conditions are working and the alternative implementations are adequate. The default buffer size of 1024 also needs to be reviewed for whether it is a correct default for all systems, or needs to be modified by environment (such as smaller for Android).
  • Ensure use cases needing backpressure all work.

Signature Changes

A new type Producer has been added:

public interface Producer {
    public void request(long n);
}

The Subscriber type now has these methods added:

public abstract class Subscriber<T> implements Observer<T>, Subscription {
    public void onStart();
    public final void request(long n);
    public final void setProducer(Producer producer);
    protected Producer onSetProducer(Producer producer);
}

Examples

This trivial example shows requesting values one at a time:

Observable.from(1, 2, 3, 4).subscribe(new Subscriber<Integer>() {

    @Override
    public void onStart() {
        request(1);
    }

    @Override
    public void onCompleted() {
    }

    @Override
    public void onError(Throwable e) {
    }

    @Override
    public void onNext(Integer t) {
        request(1);
    }

});

The OnSubscribeFromIterable operator shows how an Iterable is consumed with backpressure.

Some hi-lights (modified for simplicity rather than performance and completeness):

public final class OnSubscribeFromIterable<T> implements OnSubscribe<T> {

    @Override
    public void call(final Subscriber<? super T> o) {
        final Iterator<? extends T> it = is.iterator();
        // instead of emitting directly to the Subscriber, it emits a Producer
        o.setProducer(new IterableProducer<T>(o, it));
    }

    private static final class IterableProducer<T> implements Producer {

        public void request(long n) {
            int _c = requested.getAndAdd(n);
            if (_c == 0) {
                while (it.hasNext()) {
                    if (o.isUnsubscribed()) {
                        return;
                    }
                    T t = it.next();
                    o.onNext(t);
                    if (requested.decrementAndGet() == 0) {
                        // we're done emitting the number requested so return
                        return;
                    }
                }

                o.onCompleted();
            }

        }
    }
}

The observeOn operator is a sterotypical example of queuing on one side of a thread and draining on the other, now with backpressure.

private static final class ObserveOnSubscriber<T> extends Subscriber<T> {
        @Override
        public void onStart() {
            // signal that this is an async operator capable of receiving this many
            request(RxRingBuffer.SIZE);
        }

        @Override
        public void onNext(final T t) {
            try {
                // enqueue
                queue.onNext(t);
            } catch (MissingBackpressureException e) {
                // fail if the upstream has not obeyed our backpressure requests
                onError(e);
                return;
            }
            // attempt to schedule draining if needed
            schedule();
        }

        // the scheduling polling will then drain the queue and invoke `request(n)` to request more after draining
}

Breaking Changes

The use of Producer has been added in such a way that it is optional and additive, but some operators that used to have unbounded queues are now bounded. This means that if a source Observable emits faster than the Observer can consume them, a MissingBackpressureException can be emitted via onError.

This semantic change can break existing code.

There are two ways of resolving this:

  1. Modify the source Observable to use Producer and support backpressure.
  2. Use newly added operators such as onBackpressureBuffer or onBackpressureDrop to choose a strategy for the source Observable of how to behave when it emits more data than the consuming Observer is capable of handling. Use of onBackpressureBuffer effectively returns it to having an unbounded buffer and behaving like version 0.19 or earlier.

Example:

sourceObservable.onBackpressureBuffer().subscribe(slowConsumer);

Relation to Reactive Streams

Contributors to RxJava are involved in defining the Reactive Streams spec. RxJava 1.0 is trying to comply with the semantic rules but is not attempting to comply with the type signatures. It will however have a separate module that acts as a bridge between the RxJava Observable and the Reactive Stream types.

The reasons for this are:

  • Rx has Observer.onCompleted whereas Reactive Streams has onComplete. This is a massive breaking change to remove a "d".
  • The RxJava Subscription is used also a "Closeable"/"Disposable" and it does not work well to make it now also be used for request(n), hence the separate type Producer in RxJava. It was attempted to reuse rx.Subscription but it couldn't be done without massive breaking changes.
  • Reactive Streams uses onSubscribe(Subscription s) whereas RxJava injects the Subscription as the Subscriber. Again, this change could not be done without major breaking changes.
  • RxJava 1.0 needs to be backwards compatible with the major Rx contracts established during the 0.x roadmap.
  • Reactive Streams is not yet 1.0 and despite significant progress, it is a moving target.

Considering these things, the major semantics of request(long n) for backpressure are compatible and this will allow interop with a bridge between the interfaces. As the Reactive Streams spec matures, RxJava 2.0 may choose to fully adopt the types in the future while RxJava 1.x retains the current signatures.

How to Help

First, please test this release against your existing code to help us determine if we have broken anything.

Second, try to solve backpressure use cases and provide feedback on what works and what doesn't work.

Thank you!

Artifacts: Maven Central

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