The RxJava team has released version 2.0 of their reactive Java framework, after an 18 month development cycle. RxJava is part of the ReactiveX family of libraries and frameworks, which is in their words, "a combination of the best ideas from the Observer pattern, the Iterator pattern, and functional programming". The project's "What's different in 2.0" is a good guide for developers already familiar with RxJava 1.x.
RxJava 2.0 is a brand new implementation of RxJava. This release is based on the Reactive Streams specification, an initiative for providing a standard for asynchronous stream processing with non-blocking back pressure, targeting runtime environments (JVM and JavaScript) as well as network protocols.
Reactive implementations have concepts of publishers and subscribers, as well as ways to subscribe to data streams, get the next stream of data, handle errors and close the connection.
The Reactive Streams spec will be included in JDK 9 as java.util.concurrent.Flow. The following interfaces correspond to the Reactive Streams spec. As you can see, the spec is small, consisting of just four interfaces:
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Flow.Processor<T,R>: A component that acts as both a Subscriber and Publisher.
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Flow.Publisher<T>: A producer of items (and related control messages) received by Subscribers.
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Flow.Subscriber<T>: A receiver of messages.
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Flow.Subscription: Message control linking a Flow.Publisher and Flow.Subscriber.
Spring Framework 5 is also going reactive. To see how this looks, refer to Josh Long's Functional Reactive Endpoints with Spring Framework 5.0.
To learn more about RxJava 2.0, InfoQ interviewed main RxJava 2.0 contributor, David Karnok.
InfoQ: First of all, congrats on RxJava 2.0! 18 months in the making, that's quite a feat. What are you most proud of in this release?
David Karnok: Thanks! In some way, I wish it didn't take so long. There was a 10 month pause when Ben Christensen, the original author who started RxJava, left and there was no one at Netflix to push this forward. I'm sure many will contest that things got way better when I took over the lead role this June. I'm proud my research into more advanced and more performant Reactive Streams paid off and RxJava 2 is the proof all of it works.
InfoQ: What’s different in RxJava 2.0 and how does it help developers?
Karnok: There are a lot of differences between version 1 and 2 and it's impossible to list them all here ,but you can visit the dedicated wiki page for a comprehensible explanation. In headlines, we now support the de-facto standard Reactive Streams specification, have significant overhead reduction in many places, no longer allow nulls, have split types into two groups based on support of or lack of backpressure and have explicit interop between the base reactive types.
InfoQ: Where do you see RxJava used the most (e.g. IoT, real-time data processing, etc.)?
Karnok: RxJava is more dominantly used by the Android community, based on the feedback I saw. I believe the server side is dominated by Project Reactor and Akka at the moment. I haven't specifically seen IoT mentioned or use RxJava (it requires Java), but maybe they use some other reactive library available on their platform. For real-time data processing people still tend to use other solutions, most of them not really reactive, and I'm not aware of any providers (maybe Pivotal) who are pushing for reactive in this area.
InfoQ: What benefits does RxJava provide Android more than other environments that would explain the increased traction?
Karnok: As far as I see, Android wanted to "help" their users solving async and concurrent problems with Android-only tools such as AsyncTask, Looper/Handler etc.
Unfortunately, their design and use is quite inconvenient, often hard to understand or predict and generally brings frustration to Android developers. These can largely contribute to callback hell and the difficulty of keeping async operations off the main thread.
RxJava's design (inherited from the ReactiveX design of Microsoft) is dataflow-oriented and orthogonalized where actions execute from when data appears for processing. In addition, error handling and reporting is a key part of the flows. With AsyncTask, you had to manually work out the error delivery pattern and cancel pending tasks, whereas RxJava does that as part of its contract.
In practical terms, having a flow that queries several services in the background and then presents the results in the main thread can be expressed in a few lines with RxJava (+Retrofit) and a simple screen rotation will cancel the service calls promptly.
This is a huge productivity win for Android developers, and the simplicity helps them climb the steep learning curve the whole reactive programming's paradigm shift requires. Maybe at the end, RxJava is so attractive to Android because it reduces the "time-to-market" for individual developers, startups and small companies in the mobile app business.
There was nothing of a comparable issue on the desktop/server side Java, in my opinion, at that time. People learned to fire up ExecutorService's and wait on Future.get(), knew about SwingUtilities.invokeLater to send data back to the GUI thread and otherwise the Servlet API, which is one thread per request only (pre 3.0) naturally favored blocking APIs (database, service calls).
Desktop/server folks are more interested in the performance benefits a non-blocking design of their services offers (rather than how easy one can write a service). However, unlike Android development, having just RxJava is not enough and many expect/need complete frameworks to assist their business logic as there is no "proper" standard for non-blocking web services to replace the Servlet API. (Yes, there is Spring (~Boot) and Play but they feel a bit bandwagon-y to me at the moment).
InfoQ: HTTP is a synchronous protocol and can cause a lot of back pressure when using microservices. Streaming platforms like Akka and Apache Kafka help to solve this. Does RxJava 2.0 do anything to allow automatic back pressure?
Karnok: RxJava 2's Flowable type implements the Reactive Streams interface/specification and does support backpressure. However, the Java level backpressure is quite different from the network level backpressure. For us, backpressure means how many objects to deliver through the pipeline between different stages where these objects can be non uniform in type and size. On the network level one deals with usually fixed size packets, and backpressure manifests via the lack of acknowledgement of previously sent packets. In classical setup, the network backpressure manifests on the Java level as blocking calls that don't return until all pieces of data have been written. There are non-blocking setups, such as Netty, where the blocking is replaced by implicit buffering, and as far as I know there are only individual, non-uniform and non Reactive Streams compatible ways of handling those (i.e., a check for canWrite which one has to spin over/retry periodically). There exist libraries that try to bridge the two worlds (RxNetty, some Spring) with varying degrees of success as I see it.
InfoQ: Do you think reactive frameworks are necessary to handle large amounts of traffic and real-time data?
Karnok: It depends on the problem complexity. For example, if your task is to count the number of characters in a big-data source, there are faster and more dedicated ways of doing that. If your task is to compose results from services on top of a stream of incoming data in order to return something detailed, reactive-based solutions are quite adequate. As far as I know, most libraries and frameworks around Reactive Streams were designed for throughput and not really for latency. For example, in high-frequency trading, the predictable latency is very important and can be easily met by Aeron but not the main focus for RxJava due to the unpredictable latency behavior.
InfoQ: Does HTTP/2 help solve the scalability issues that HTTP/1.1 has?
Karnok: This is not related to RxJava and I personally haven't played with HTTP/2 but only read the spec. Multiplexing over the same channel is certainly a win in addition to the support for explicit backpressure (i.e., even if the network can deliver, the client may still be unable to process the data in that volume) per stream. I don't know all the technical details but I believe Spring Reactive Web does support HTTP/2 transport if available but they hide all the complexity behind reactive abstractions so you can express your processing pipeline in RxJava 2 and Reactor 3 terms if you wish.
InfoQ: Java 9 is projected to be featuring some reactive functionality. Is that a complete spec?
Karnok: No. Java 9 will only feature 4 Java interfaces with 7 methods total. No stream-like or Rx-like API on top of that nor any JDK features built on that.
InfoQ: Will that obviate the need for RxJava if it is built right into the JDK?
Karnok: No and I believe there's going to be more need for a true and proven library such as RxJava. Once the toolchains grow up to Java 9, we will certainly provide adapters and we may convert (or rewrite) RxJava 3 on top of Java 9's features (VarHandles).
One of my fears is that once Java 9 is out, many will try to write their own libraries (individuals, companies) and the "market" gets diluted with big branded-low quality solutions, not to mention the increased amount of "how does RxJava differ from X" questions.
My personal opinion is that this is already happening today around Reactive Streams where certain libraries and frameworks advertise themselves as RS but fail to deliver based on it. My (likely biased) conjecture is that RxJava 2 is the closest library/technology to an optimal Reactive Streams-based solution that can be.
InfoQ: What's next for RxJava?
Karnok: We had fantastic reviewers, such as Jake Wharton, during the development of RxJava 2. Unfortunately, the developer previews and release candidates didn't generate enough attention and despite our efforts, small problems and oversights slipped into the final release. I don't expect major issues in the coming months but we will keep fixing both version 1 and 2 as well as occasionally adding new operators to support our user base. A few companion libraries, such as RxAndroid, now provide RxJava 2 compatible versions, but the majority of the other libraries don't yet or haven't yet decided how to go forward. In terms of RxJava, I plan to retire RxJava 1 within six months (i.e., only bugfixes then on), partly due to the increasing maintenance burden on my "one man army" for some time now; partly to "encourage" the others to switch to the RxJava 2 ecosystem. As for RxJava 3, I don't have any concrete plans yet. There are ongoing discussions about splitting the library along types or along backpressure support as well as making the so-called operator-fusion elements (which give a significant boost to our performance) a standard extension of the Reactive Streams specification.