Repository: balamaci/rxjava-walkthrough
Branch: master
Commit: 584e36bf4e46
Files: 17
Total size: 152.9 KB
Directory structure:
gitextract_xvhlef2x/
├── .gitignore
├── README.md
├── _config.yml
├── pom.xml
└── src/
└── test/
├── java/
│ └── com/
│ └── balamaci/
│ └── rx/
│ ├── BaseTestObservables.java
│ ├── Part01CreateFlowable.java
│ ├── Part02SimpleOperators.java
│ ├── Part03MergingStreams.java
│ ├── Part04HotPublishers.java
│ ├── Part05AdvancedOperators.java
│ ├── Part06Schedulers.java
│ ├── Part07FlatMapOperator.java
│ ├── Part08ErrorHandling.java
│ ├── Part09BackpressureHandling.java
│ └── util/
│ ├── Helpers.java
│ └── Pair.java
└── resources/
└── simplelogger.properties
================================================
FILE CONTENTS
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FILE: .gitignore
================================================
# Created by .ignore support plugin (hsz.mobi)
### Java template
*.class
# Package Files #
*.jar
*.war
*.ear
# virtual machine crash logs, see http://www.java.com/en/download/help/error_hotspot.xml
hs_err_pid*
target
.idea
*.iml
================================================
FILE: README.md
================================================
# RxJava 2.x
View at [Github page](https://balamaci.github.io/rxjava-walkthrough/)
also available for [reactor-core](https://github.com/balamaci/reactor-core-playground)
## Contents
- [Flowable, Single and Observable](#flowable)
- [Simple Operators](#simple-operators)
- [Merging Streams](#merging-streams)
- [Hot Publishers](#hot-publishers)
- [Schedulers](#schedulers)
- [FlatMap Operator](#flatmap-operator)
- [Error Handling](#error-handling)
- [Backpressure](#backpressure)
- [Articles and books](#articles)
## Reactive Streams
Reactive Streams is a programming concept for handling asynchronous
data streams in a non-blocking manner while providing backpressure to stream publishers.
It has evolved into a [specification](https://github.com/reactive-streams/reactive-streams-jvm) that is based on the concept of **Publisher<T>** and **Subscriber<T>**.
A **Publisher** is the source of events **T** in the stream, and a **Subscriber** is the consumer for those events.
A **Subscriber** subscribes to a **Publisher** by invoking a "factory method" in the Publisher that will push
the stream items **<T>** starting a new **Subscription**:
```java
public interface Publisher<T> {
public void subscribe(Subscriber<? super T> s);
}
```
When the Subscriber is ready to start handling events, it signals this via a **request** to that **Subscription**
```java
public interface Subscription {
public void request(long n); //request n items
public void cancel();
}
```
Upon receiving this signal, the Publisher begins to invoke **Subscriber::onNext(T)** for each event **T**.
This continues until either completion of the stream (**Subscriber::onComplete()**)
or an error occurs during processing (**Subscriber::onError(Throwable)**).
```java
public interface Subscriber<T> {
//signals to the Publisher to start sending events
public void onSubscribe(Subscription s);
public void onNext(T t);
public void onError(Throwable t);
public void onComplete();
}
```
## Flowable and Observable
RxJava provides more types of event publishers:
- **Flowable** Publisher that emits 0..N elements, and then completes successfully or with an error
- **Observable** like Flowables but without a backpressure strategy. They were introduced in RxJava 1.x
- **Single** a specialized emitter that completes with a value successfully either an error.(doesn't have onComplete callback, instead onSuccess(val))
- **Maybe** a specialized emitter that can complete with / without a value or complete with an error.
- **Completable** a specialized emitter that just signals if it completed successfully or with an error.
Code is available at [Part01CreateFlowable.java](https://github.com/balamaci/rxjava-playground/blob/master/src/test/java/com/balamaci/rx/Part01CreateFlowable.java)
### Simple operators to create Streams
```java
Flowable<Integer> flowable = Flowable.just(1, 5, 10);
Flowable<Integer> flowable = Flowable.range(1, 10);
Flowable<String> flowable = Flowable.fromArray(new String[] {"red", "green", "blue"});
Flowable<String> flowable = Flowable.fromIterable(List.of("red", "green", "blue"));
```
### Flowable from Future
```java
CompletableFuture<String> completableFuture = CompletableFuture
.supplyAsync(() -> { //starts a background thread the ForkJoin common pool
log.info("CompletableFuture work starts");
Helpers.sleepMillis(100);
return "red";
});
Single<String> single = Single.from(completableFuture);
single.subscribe(val -> log.info("Stream completed successfully : {}", val));
```
### Creating your own stream
We can use **Flowable.create(...)** to implement the emissions of events by calling **onNext(val)**, **onComplete()**, **onError(throwable)**
When subscribing to the Observable / Flowable with flowable.subscribe(...) the lambda code inside **create(...)** gets executed.
Flowable.subscribe(...) can take 3 handlers for each type of event - onNext, onError and onCompleted.
When using **Observable.create(...)** you need to be aware of [backpressure](#backpressure) and that Observables created with 'create' are not BackPressure aware
```java
Observable<Integer> stream = Observable.create(subscriber -> {
log.info("Started emitting");
log.info("Emitting 1st");
subscriber.onNext(1);
log.info("Emitting 2nd");
subscriber.onNext(2);
subscriber.onComplete();
});
//Flowable version same Observable but with a BackpressureStrategy
//that will be discussed separately.
Flowable<Integer> stream = Flowable.create(subscriber -> {
log.info("Started emitting");
log.info("Emitting 1st");
subscriber.onNext(1);
log.info("Emitting 2nd");
subscriber.onNext(2);
subscriber.onComplete();
}, BackpressureStrategy.MISSING);
stream.subscribe(
val -> log.info("Subscriber received: {}", val),
err -> log.error("Subscriber received error", err),
() -> log.info("Subscriber got Completed event")
);
```
### Streams are lazy
Streams are lazy meaning that the code inside create() doesn't get executed without subscribing to the stream.
So event if we sleep for a long time inside create() method(to simulate a costly operation),
without subscribing to this Observable, the code is not executed and the method returns immediately.
```java
public void observablesAreLazy() {
Observable<Integer> observable = Observable.create(subscriber -> {
log.info("Started emitting but sleeping for 5 secs"); //this is not executed
Helpers.sleepMillis(5000);
subscriber.onNext(1);
});
log.info("Finished");
}
===========
[main] - Finished
```
### Multiple subscriptions to the same Observable / Flowable
When subscribing to an Observable/Flowable, the create() method gets executed for each Subscriber, the events
inside **create(..)** are re-emitted to each subscriber independently.
So every subscriber will get the same events and will not lose any events - this behavior is named **'cold observable'**
See [Hot Publishers](#hot-publisher) to understand sharing a subscription and multicasting events.
```java
Observable<Integer> observable = Observable.create(subscriber -> {
log.info("Started emitting");
log.info("Emitting 1st event");
subscriber.onNext(1);
log.info("Emitting 2nd event");
subscriber.onNext(2);
subscriber.onComplete();
});
log.info("Subscribing 1st subscriber");
observable.subscribe(val -> log.info("First Subscriber received: {}", val));
log.info("=======================");
log.info("Subscribing 2nd subscriber");
observable.subscribe(val -> log.info("Second Subscriber received: {}", val));
```
will output
```
[main] - Subscribing 1st subscriber
[main] - Started emitting
[main] - Emitting 1st event
[main] - First Subscriber received: 1
[main] - Emitting 2nd event
[main] - First Subscriber received: 2
[main] - =======================
[main] - Subscribing 2nd subscriber
[main] - Started emitting
[main] - Emitting 1st event
[main] - Second Subscriber received: 1
[main] - Emitting 2nd event
[main] - Second Subscriber received: 2
```
## Observable / Flowable lifecycle
### Operators
Between the source Observable / Flowable and the Subscriber there can be a wide range of operators and RxJava provides
lots of operators to chose from. Probably you are already familiar with functional operations like **filter** and **map**.
so let's use them as example:
```java
Flowable<Integer> stream = Flowable.create(subscriber -> {
subscriber.onNext(1);
subscriber.onNext(2);
....
subscriber.onComplete();
}, BackpressureStrategy.MISSING);
.filter(val -> val < 10)
.map(val -> val * 10)
.subscribe(val -> log.info("Received: {}", val));
```
When we call _Flowable.create()_ you might think that we're calling onNext(..), onComplete(..) on the Subscriber at the end of the chain,
not the operators between them.
This is not true because **the operators themselves are decorators for their source** wrapping it with the operator behavior
like an onion's layers.
When we call **.subscribe()** at the end of the chain, **Subscription propagates through the layers back to the source,
each operator subscribing itself to it's wrapped source Observable / Flowable and so on to the original source,
triggering it to start producing/emitting items**.
**Flowable.create** calls **---> filterOperator.onNext(val)** which if val > 10 calls **--->
mapOperator.onNext(val)** does val = val * 10 and calls **---> subscriber.onNext(val)**.
[Found](https://tomstechnicalblog.blogspot.ro/2015_10_01_archive.html) a nice analogy with a team of house movers, with every mover doing it's thing before passing it to the next in line
until it reaches the final subscriber.
### Canceling subscription
Inside the create() method, we can check is there are still active subscribers to our Flowable/Observable.
There are operators that also unsubscribe from the stream so the source knows to stop producing events.
It's a way to prevent to do extra work(like for ex. querying a datasource for entries) if no one is listening
In the following example we'd expect to have an infinite stream, but because we stop if there are no active subscribers, we stop producing events.
**take(limit)** is a simple operator. It's role is to count the number of events and then unsubscribes from it's source
once it received the specified amount and calls onComplete() to it's subscriber.
```java
Observable<Integer> observable = Observable.create(subscriber -> {
int i = 1;
while(true) {
if(subscriber.isDisposed()) {
break;
}
subscriber.onNext(i++);
//registering a callback when the downstream subscriber unsubscribes
subscriber.setCancellable(() -> log.info("Subscription canceled"));
}
});
observable
.take(5) //unsubscribes after the 5th event
.subscribe(val -> log.info("Subscriber received: {}", val),
err -> log.error("Subscriber received error", err),
() -> log.info("Subscriber got Completed event") //The Complete event
//is triggered by 'take()' operator
==================
[main] - Subscriber received: *1*
[main] - Subscriber received: *2*
[main] - Subscriber received: *3*
[main] - Subscriber received: *4*
[main] - Subscriber received: *5*
[main] - Subscriber got Completed event
[main] - Subscription canceled
```
## Simple Operators
Code is available at [Part02SimpleOperators.java](https://github.com/balamaci/rxjava-playground/blob/master/src/test/java/com/balamaci/rx/Part02SimpleOperators.java)
### delay
Delay operator - the Thread.sleep of the reactive world, it's pausing each emission for a particular increment of time.
```java
CountDownLatch latch = new CountDownLatch(1);
Flowable.range(0, 2)
.doOnNext(val -> log.info("Emitted {}", val))
.delay(5, TimeUnit.SECONDS)
.subscribe(tick -> log.info("Tick {}", tick),
(ex) -> log.info("Error emitted"),
() -> {
log.info("Completed");
latch.countDown();
});
latch.await();
==============
14:27:44 [main] - Starting
14:27:45 [main] - Emitted 0
14:27:45 [main] - Emitted 1
14:27:50 [RxComputationThreadPool-1] - Tick 0
14:27:50 [RxComputationThreadPool-1] - Tick 1
14:27:50 [RxComputationThreadPool-1] - Completed
```
The **.delay()**, **.interval()** operators uses a [Scheduler](#schedulers) by default which is why we see it executing
on a different thread _RxComputationThreadPool-1_ which actually means it's running the operators and the subscribe operations
on another thread and so the test method will terminate before we see the text from the log unless we wait for the completion of the stream.
This is the role of the **CountdownLatch**.
### interval
Periodically emits a number starting from 0 and then increasing the value on each emission.
```java
log.info("Starting");
Flowable.interval(5, TimeUnit.SECONDS)
.take(4)
.subscribe(tick -> log.info("Subscriber received {}", tick),
(ex) -> log.info("Error emitted"),
() -> log.info("Subscriber got Completed event"));
==========
12:17:56 [main] - Starting
12:18:01 [RxComputationThreadPool-1] - Subscriber received: 0
12:18:06 [RxComputationThreadPool-1] - Subscriber received: 1
12:18:11 [RxComputationThreadPool-1] - Subscriber received: 2
12:18:16 [RxComputationThreadPool-1] - Subscriber received: 3
12:18:21 [RxComputationThreadPool-1] - Subscriber received: 4
12:18:21 [RxComputationThreadPool-1] - Subscriber got Completed event
```
### scan
Takes an **initial value** and a **function(accumulator, currentValue)**. It goes through the events
sequence and combines the current event value with the previous result(accumulator) emitting downstream the function's
result for each event(the initial value is used for the first event)
```java
Flowable<Integer> numbers =
Flowable.just(3, 5, -2, 9)
.scan(0, (totalSoFar, currentValue) -> {
log.info("TotalSoFar={}, currentValue={}",
totalSoFar, currentValue);
return totalSoFar + currentValue;
});
=============
16:09:17 [main] - Subscriber received: 0
16:09:17 [main] - TotalSoFar=0, currentValue=3
16:09:17 [main] - Subscriber received: 3
16:09:17 [main] - TotalSoFar=3, currentValue=5
16:09:17 [main] - Subscriber received: 8
16:09:17 [main] - TotalSoFar=8, currentValue=-2
16:09:17 [main] - Subscriber received: 6
16:09:17 [main] - TotalSoFar=6, currentValue=9
16:09:17 [main] - Subscriber received: 15
16:09:17 [main] - Subscriber got Completed event
```
### reduce
reduce operator acts like the scan operator but it only passes downstream the final result
(doesn't pass the intermediate results downstream) so the subscriber receives just one event
```java
Flowable<Integer> numbers = Flowable.just(3, 5, -2, 9)
.reduce(0, (totalSoFar, val) -> {
log.info("totalSoFar={}, emitted={}",
totalSoFar, val);
return totalSoFar + val;
});
=============
17:08:29 [main] - totalSoFar=0, emitted=3
17:08:29 [main] - totalSoFar=3, emitted=5
17:08:29 [main] - totalSoFar=8, emitted=-2
17:08:29 [main] - totalSoFar=6, emitted=9
17:08:29 [main] - Subscriber received: 15
17:08:29 [main] - Subscriber got Completed event
```
### collect
collect operator acts similar to the _reduce_ operator, but while the _reduce_ operator uses a reduce function
which returns a value, the _collect_ operator takes a container supplier and a function which doesn't return
anything(a consumer). The mutable container is passed for every event and thus you get a chance to modify it
in this collect consumer function.
```java
Flowable<List<Integer>> numbers = Flowable.just(3, 5, -2, 9)
.collect(ArrayList::new, (container, value) -> {
log.info("Adding {} to container", value);
container.add(value);
//notice we don't need to return anything
});
=========
17:40:18 [main] - Adding 3 to container
17:40:18 [main] - Adding 5 to container
17:40:18 [main] - Adding -2 to container
17:40:18 [main] - Adding 9 to container
17:40:18 [main] - Subscriber received: [3, 5, -2, 9]
17:40:18 [main] - Subscriber got Completed event
```
because the usecase to store to a List container is so common, there is a **.toList()** operator that is just a collector adding to a List.
### defer
An easy way to switch from a blocking method to a reactive Single/Flowable is to use **.defer(() -> blockingOp())**.
Simply using **Flowable.just(blockingOp())** would still block, as Java needs to resolve the parameter when invoking
**Flux.just(param)** method, so _blockingOp()_ method would still be invoked(and block).
```java
//NOT OK
Flowable<String> flowableBlocked = Flowable.just((blockingOp())); //blocks on this line
```
In order to get around this problem, we can use **Flowable.defer(() -> blockingOp())** and wrap the _blockingOp()_ call inside a lambda which
will be invoked lazy **at subscribe time**.
```java
Flowable<String> stream = Flowable.defer(() -> Flowable.just(blockingOperation()));
stream.subscribe(val -> log.info("Val " + val)); //only now the code inside defer() is executed
```
## Merging Streams
Operators for working with multiple streams
Code at [Part03MergingStreams.java](https://github.com/balamaci/rxjava-playground/blob/master/src/test/java/com/balamaci/rx/Part03MergingStreams.java)
### zip
Zip operator operates sort of like a zipper in the sense that it takes an event from one stream and waits
for an event from another other stream. Once an event for the other stream arrives, it uses the zip function
to merge the two events.
This is an useful scenario when for example you want to make requests to remote services in parallel and
wait for both responses before continuing. It also takes a function which will produce the combined result
of the zipped streams once each has emitted a value.
Zip operator besides the streams to zip, also takes as parameter a function which will produce the
combined result of the zipped streams once each stream emitted its value
```java
Single<Boolean> isUserBlockedStream =
Single.fromFuture(CompletableFuture.supplyAsync(() -> {
Helpers.sleepMillis(200);
return Boolean.FALSE;
}));
Single<Integer> userCreditScoreStream =
Single.fromFuture(CompletableFuture.supplyAsync(() -> {
Helpers.sleepMillis(2300);
return 5;
}));
Single<Pair<Boolean, Integer>> userCheckStream = Single.zip(isUserBlockedStream, userCreditScoreStream,
(blocked, creditScore) -> new Pair<Boolean, Integer>(blocked, creditScore));
userCheckStream.subscribe(pair -> log.info("Received " + pair));
```
Even if the 'isUserBlockedStream' finishes after 200ms, 'userCreditScoreStream' is slow at 2.3secs,
the 'zip' method applies the combining function(new Pair(x,y)) after it received both values and passes it
to the subscriber.
Another good example of 'zip' is to slow down a stream by another basically **implementing a periodic emitter of events**:
```java
Flowable<String> colors = Flowable.just("red", "green", "blue");
Flowable<Long> timer = Flowable.interval(2, TimeUnit.SECONDS);
Flowable<String> periodicEmitter = Flowable.zip(colors, timer, (key, val) -> key);
```
Since the zip operator needs a pair of events, the slow stream will work like a timer by periodically emitting
with zip setting the pace of emissions downstream every 2 seconds.
**Zip is not limited to just two streams**, it can merge 2,3,4,.. streams and wait for groups of 2,3,4 'pairs' of
events which it combines with the zip function and sends downstream.
### merge
Merge operator combines one or more stream and passes events downstream as soon as they appear.
```
Flowable<String> colors = periodicEmitter("red", "green", "blue", 2, TimeUnit.SECONDS);
Flowable<Long> numbers = Flowable.interval(1, TimeUnit.SECONDS)
.take(5);
//notice we can't say Flowable<String> or Flowable<Long> as the return stream o the merge operator since
//it can emit either a color or number.
Flowable flowable = Flowable.merge(colors, numbers);
============
21:32:15 - Subscriber received: 0
21:32:16 - Subscriber received: red
21:32:16 - Subscriber received: 1
21:32:17 - Subscriber received: 2
21:32:18 - Subscriber received: green
21:32:18 - Subscriber received: 3
21:32:19 - Subscriber received: 4
21:32:20 - Subscriber received: blue
```
### concat
Concat operator appends another streams at the end of another
```java
Flowable<String> colors = periodicEmitter("red", "green", "blue", 2, TimeUnit.SECONDS);
Flowable<Long> numbers = Flowable.interval(1, TimeUnit.SECONDS)
.take(4);
Flowable events = Flowable.concat(colors, numbers);
==========
22:48:23 - Subscriber received: red
22:48:25 - Subscriber received: green
22:48:27 - Subscriber received: blue
22:48:28 - Subscriber received: 0
22:48:29 - Subscriber received: 1
22:48:30 - Subscriber received: 2
22:48:31 - Subscriber received: 3
```
Even if the 'numbers' streams should start early, the 'colors' stream emits fully its events
before we see any 'numbers'.
This is because 'numbers' stream is actually subscribed only after the 'colors' complete.
Should the second stream be a 'hot' emitter, its events would be lost until the first one finishes
and the seconds stream is subscribed.
## Hot Publishers
We've seen that with 'cold publishers', whenever a subscriber subscribes, each subscriber will get
it's version of emitted values independently, the exact set of data indifferently when they subscribe.
But cold publishers only produce data when the subscribers subscribes, however there are cases where
the events happen independently from the consumers regardless if someone is
listening or not and we don't have control to request more. So you could say we have 'cold publishers' for pull
scenarios and 'hot publishers' which push.
### Subjects
Subjects are one way to handle hot observables. Subjects keep reference to their subscribers and allow 'multicasting'
an event to them.
```java
for (Disposable<T> s : subscribers.get()) {
s.onNext(t);
}
```
Subjects besides being traditional Observables you can use the same operators and subscribe to them,
are also an **Observer**(interface like **Subscriber** from [reactive-streams](#reactive-streams), implementing the 3 methods **onNext, onError, onComplete**),
meaning you can invoke subject.onNext(value) from different parts in the code,
which means that you publish events which the Subject will pass on to their subscribers.
```java
Subject<Integer> subject = ReplaySubject.create()
.map(...);
.subscribe(); //
...
subject.onNext(val);
...
subject.onNext(val2);
```
remember for
```java
Observable.create(subscriber -> {
subscriber.onNext(val);
})
```
### ReplaySubject
ReplaySubject keeps a buffer of events that it 'replays' to each new subscriber, first he receives a batch of missed
and only later events in real-time.
```java
Subject<Integer> subject = ReplaySubject.createWithSize(50);
log.info("Pushing 0");
subject.onNext(0);
log.info("Pushing 1");
subject.onNext(1);
log.info("Subscribing 1st");
subject.subscribe(val -> log.info("Subscriber1 received {}", val),
logError(), logComplete());
log.info("Pushing 2");
subject.onNext(2);
log.info("Subscribing 2nd");
subject.subscribe(val -> log.info("Subscriber2 received {}", val),
logError(), logComplete());
log.info("Pushing 3");
subject.onNext(3);
subject.onComplete();
==================
[main] - Pushing 0
[main] - Pushing 1
[main] - Subscribing 1st
[main] - Subscriber1 received 0
[main] - Subscriber1 received 1
[main] - Pushing 2
[main] - Subscriber1 received 2
[main] - Subscribing 2nd
[main] - Subscriber2 received 0
[main] - Subscriber2 received 1
[main] - Subscriber2 received 2
[main] - Pushing 3
[main] - Subscriber1 received 3
[main] - Subscriber2 received 3
[main] - Subscriber got Completed event
[main] - Subscriber got Completed event
```
### ConnectableObservable / ConnectableFlowable and resource sharing
There are cases when we want to share a single subscription between subscribers, meaning while the code that executes
on subscribing should be executed once, the events should be published to all subscribers.
For ex. when we want to share a connection between multiple Observables / Flowables.
Using a plain Observable would just reexecute the code inside _.create()_ and opening / closing a new connection for each
new subscriber when it subscribes / cancels its subscription.
**ConnectableObservable** are a special kind of **Observable**. No matter how many Subscribers subscribe to ConnectableObservable,
it opens just one subscription to the Observable from which it was created.
Anyone who subscribes to **ConnectableObservable** is placed in a set of Subscribers(it doesn't trigger
the _.create()_ code a normal Observable would when .subscribe() is called). A **.connect()** method is available for ConnectableObservable.
**As long as connect() is not called, these Subscribers are put on hold, they never directly subscribe to upstream Observable**
```java
ConnectableObservable<Integer> connectableObservable =
Observable.<Integer>create(subscriber -> {
log.info("Inside create()");
/* A JMS connection listener example
Just an example of a costly operation that is better to be shared **/
/* Connection connection = connectionFactory.createConnection();
Session session = connection.createSession(true, AUTO_ACKNOWLEDGE);
MessageConsumer consumer = session.createConsumer(orders);
consumer.setMessageListener(subscriber::onNext); */
subscriber.setCancellable(() -> log.info("Subscription cancelled"));
log.info("Emitting 1");
subscriber.onNext(1);
log.info("Emitting 2");
subscriber.onNext(2);
subscriber.onComplete();
}).publish();
connectableObservable
.take(1)
.subscribe((val) -> log.info("Subscriber1 received: {}", val),
logError(), logComplete());
connectableObservable
.subscribe((val) -> log.info("Subscriber2 received: {}", val),
logError(), logComplete());
log.info("Now connecting to the ConnectableObservable");
connectableObservable.connect();
===================
```
### share() operator
Another operator of the ConnectableObservable **.refCount()** allows to do away with having to manually call **.connect()**,
instead it invokes the .create() code when the first Subscriber subscribes while sharing this single subscription with subsequent Subscribers.
This means that **.refCount()** basically keeps a count of references of it's subscribers and subscribes to upstream Observable
(executes the code inside .create() just for the first subscriber), but multicasts the same event to each active subscriber.
When the last subscriber unsubscribes, the ref counter goes from 1 to 0 and triggers any unsubscribe callback associated.
If another Subscriber subscribes after that, counter goes from 0 to 1 and the process starts over again.
```java
ConnectableObservable<Integer> connectableStream = Observable.<Integer>create(subscriber -> {
log.info("Inside create()");
//Simulated MessageListener emits periodically every 500 milliseconds
ResourceConnectionHandler resourceConnectionHandler = new ResourceConnectionHandler() {
@Override
public void onMessage(Integer message) {
log.info("Emitting {}", message);
subscriber.onNext(message);
}
};
resourceConnectionHandler.openConnection();
//when the last subscriber unsubscribes it will invoke disconnect on the resourceConnectionHandler
subscriber.setCancellable(resourceConnectionHandler::disconnect);
}).publish();
//publish().refCount() have been joined together in the .share() operator
Observable<Integer> observable = connectableObservable.refCount();
CountDownLatch latch = new CountDownLatch(2);
connectableStream
.take(5)
.subscribe((val) -> log.info("Subscriber1 received: {}", val),
logError(), logComplete(latch));
Helpers.sleepMillis(1000);
log.info("Subscribing 2nd");
//we're not seing the code inside .create() reexecuted
connectableStream
.take(2)
.subscribe((val) -> log.info("Subscriber2 received: {}", val),
logError(), logComplete(latch));
//waiting for the streams to complete
Helpers.wait(latch);
//subscribing another after previous Subscribers unsubscribed
latch = new CountDownLatch(1);
log.info("Subscribing 3rd");
observable
.take(1)
.subscribe((val) -> log.info("Subscriber3 received: {}", val), logError(), logComplete(latch));
private abstract class ResourceConnectionHandler {
ScheduledExecutorService scheduledExecutorService;
private int counter;
public void openConnection() {
log.info("**Opening connection");
scheduledExecutorService = periodicEventEmitter(() -> {
counter ++;
onMessage(counter);
}, 500, TimeUnit.MILLISECONDS);
}
public abstract void onMessage(Integer message);
public void disconnect() {
log.info("**Shutting down connection");
scheduledExecutorService.shutdown();
}
}
===============
14:55:23 [main] INFO BaseTestObservables - Inside create()
14:55:23 [main] INFO BaseTestObservables - **Opening connection
14:55:23 [pool-1-thread-1] INFO BaseTestObservables - Emitting 1
14:55:23 [pool-1-thread-1] INFO BaseTestObservables - Subscriber1 received: 1
14:55:24 [pool-1-thread-1] INFO BaseTestObservables - Emitting 2
14:55:24 [pool-1-thread-1] INFO BaseTestObservables - Subscriber1 received: 2
14:55:24 [pool-1-thread-1] INFO BaseTestObservables - Emitting 3
14:55:24 [pool-1-thread-1] INFO BaseTestObservables - Subscriber1 received: 3
14:55:24 [main] INFO BaseTestObservables - Subscribing 2nd
14:55:25 [pool-1-thread-1] INFO BaseTestObservables - Emitting 4
14:55:25 [pool-1-thread-1] INFO BaseTestObservables - Subscriber1 received: 4
14:55:25 [pool-1-thread-1] INFO BaseTestObservables - Subscriber2 received: 4
14:55:25 [pool-1-thread-1] INFO BaseTestObservables - Emitting 5
14:55:25 [pool-1-thread-1] INFO BaseTestObservables - Subscriber1 received: 5
14:55:25 [pool-1-thread-1] INFO BaseTestObservables - Subscriber got Completed event
14:55:25 [pool-1-thread-1] INFO BaseTestObservables - Subscriber2 received: 5
14:55:25 [pool-1-thread-1] INFO BaseTestObservables - **Shutting down connection
14:55:25 [pool-1-thread-1] INFO BaseTestObservables - Subscriber got Completed event
14:55:25 [main] INFO BaseTestObservables - Subscribing 3rd
14:55:25 [main] INFO BaseTestObservables - Inside create()
14:55:25 [main] INFO BaseTestObservables - **Opening connection
14:55:25 [pool-2-thread-1] INFO BaseTestObservables - Emitting 1
14:55:25 [pool-2-thread-1] INFO BaseTestObservables - Subscriber3 received: 1
14:55:25 [pool-2-thread-1] INFO BaseTestObservables - **Shutting down connection
14:55:25 [pool-2-thread-1] INFO BaseTestObservables - Subscriber got Completed event
```
The **share()** operator of Observable / Flowable is an operator which basically does **publish().refCount()**.
## Schedulers
RxJava provides some high level concepts for concurrent execution, like ExecutorService we're not dealing
with the low level constructs like creating the Threads ourselves. Instead we're using a **Scheduler** which create
Workers who are responsible for scheduling and running code. By default RxJava will not introduce concurrency
and will run the operations on the subscription thread.
There are two methods through which we can introduce Schedulers into our chain of operations:
- **subscribeOn** allows to specify which Scheduler invokes the code contained in the lambda code for Observable.create()
- **observeOn** allows control to which Scheduler executes the code in the downstream operators
RxJava provides some general use Schedulers:
- **Schedulers.computation()** - to be used for CPU intensive tasks. A threadpool. Should not be used for tasks involving blocking IO.
- **Schedulers.io()** - to be used for IO bound tasks
- **Schedulers.from(Executor)** - custom ExecutorService
- **Schedulers.newThread()** - always creates a new thread when a worker is needed. Since it's not thread pooled and
always creates a new thread instead of reusing one, this scheduler is not very useful
Although we said by default RxJava doesn't introduce concurrency. Notice how we are not doing anything on another thread
than the subscribing thread 'main' and the Test doesn't end until the complete event is processed:
```java
@Test
public void byDefaultRxJavaDoesntIntroduceConcurrency() {
log.info("Starting");
Observable.<Integer>create(subscriber -> {
log.info("Someone subscribed");
subscriber.onNext(1);
subscriber.onNext(2);
subscriber.onComplete();
})
.map(val -> {
log.info("Mapping {}", val);
//what if we do some Thread.sleep here
//Thread.sleep(2000);
return val * 10;
})
.subscribe(logNext());
}
===============
11:23:49 [main] INFO BaseTestObservables - Starting
11:23:50 [main] INFO BaseTestObservables - Someone subscribed
11:23:50 [main] INFO BaseTestObservables - Mapping 1
11:23:50 [main] INFO BaseTestObservables - Subscriber received: 10
11:23:50 [main] INFO BaseTestObservables - Mapping 2
11:23:50 [main] INFO BaseTestObservables - Subscriber received: 20
```
now let's enable that _Thread.sleep(2000)_ above.
```
11:42:12 [main] INFO BaseTestObservables - Starting
11:42:12 [main] INFO BaseTestObservables - Someone subscribed
11:42:12 [main] INFO BaseTestObservables - Mapping 1
11:42:14 [main] INFO BaseTestObservables - Subscriber received: 10
11:42:14 [main] INFO BaseTestObservables - Mapping 2
11:42:16 [main] INFO BaseTestObservables - Subscriber received: 20
```
as expected nothing changes, just that we receive the events in the Subscriber delayed by 2 secs.
To prevent this, lots of RxJava operators that involve waiting as **delay**,**interval**, **zip** run on a Scheduler, otherwise they would just block the subscribing thread.
By default **Schedulers.computation()** is used, but the Scheduler can be passed as a parameter to those methods.
Ok so how can we provide different threads to run the different parts of the code.
### subscribeOn
As stated above **subscribeOn** allows to specify on which Scheduler thread the subscribtion is made - which thread invokes the code contained in the lambda for Observable.create() -
(it's **not** abouth the thread for where the code in **.subscribe((val) -> {...})** gets executed).
Since the operators are lazy and nothing happens until subscription, where the **.subscribeOn()** is called doesn't make any difference.
Also calling **.subscribeOn()** multiple times at different positions doesn't have any effect, only the first **.subscribeOn()** Scheduler is considered.
```java
@Test
public void testSubscribeOn() {
log.info("Starting");
Observable<Integer> observable = Observable.create(subscriber -> {
//code that will execute inside the IO ThreadPool
log.info("Starting slow network op");
Helpers.sleepMillis(2000);
log.info("Emitting 1st");
subscriber.onNext(1);
subscriber.onComplete();
});
observable = observable
.subscribeOn(Schedulers.io()) //Specify execution on the IO Scheduler
.map(val -> {
int newValue = val * 10;
log.info("Mapping {} to {}", val, newValue);
return newValue;
});
/** Since we are switching the subscription thread we now need to wait
* for the Thread to complete so again we are using the CountDownLatch "trick" to do it.
**/
CountDownLatch latch = new CountDownLatch(1);
observable.subscribe(
logNext(),
logError(latch),
logComplete(latch)
);
Helpers.wait(latch);
}
===============
13:16:31 [main] INFO BaseTestObservables - Starting
13:16:31 [RxCachedThreadScheduler-1] INFO BaseTestObservables - Starting slow network op
13:16:33 [RxCachedThreadScheduler-1] INFO BaseTestObservables - Emitting 1st
13:16:33 [RxCachedThreadScheduler-1] INFO BaseTestObservables - Mapping 1 to 10
13:16:33 [RxCachedThreadScheduler-1] INFO BaseTestObservables - Subscriber received: 10
13:16:33 [RxCachedThreadScheduler-1] INFO BaseTestObservables - Subscriber got Completed event
```
Notice how the code and also the flow down the operators like **.map()** is switched to this new Scheduler that was specified.
### observeOn
**observeOn** allows control to which Scheduler executes the code in the downstream operators.
So by using **observeOn()** we changed the Scheduler for the **map** operator, but notice how the last **.observeOn(Schedulers.newThread())**
we also influence the code received by the subscriber, while **.subscribeOn()** just had a part on the code executed before we changed with **.observeOn()**
```java
log.info("Starting");
Observable<Integer> observable =
Observable.create(subscriber -> {
//code that will execute inside the IO Scheduler
log.info("Emitting 1st");
subscriber.onNext(1);
log.info("Emitting 2nd");
subscriber.onNext(2);
subscriber.onComplete();
})
.subscribeOn(Schedulers.io())
.observeOn(Schedulers.computation())
.map(val -> {
int newValue = val * 10;
log.info("Mapping {} to {}", val, newValue);
return newValue;
})
.observeOn(Schedulers.newThread());
CountDownLatch latch = new CountDownLatch(1);
observable.subscribe(
logNext(),
logError(latch),
logComplete(latch)
);
Helpers.wait(latch);
===============
19:35:01 [main] INFO BaseTestObservables - Starting
19:35:01 [RxCachedThreadScheduler-1] INFO BaseTestObservables - Started emitting
19:35:01 [RxCachedThreadScheduler-1] INFO BaseTestObservables - Emitting 1st
19:35:01 [RxCachedThreadScheduler-1] INFO BaseTestObservables - Emitting 2nd
19:35:01 [RxComputationThreadPool-1] INFO BaseTestObservables - Mapping 1 to 10
19:35:01 [RxNewThreadScheduler-1] INFO BaseTestObservables - Subscriber received: 10
19:35:01 [RxComputationThreadPool-1] INFO BaseTestObservables - Mapping 2 to 20
19:35:01 [RxNewThreadScheduler-1] INFO BaseTestObservables - Subscriber received: 20
19:35:01 [RxNewThreadScheduler-1] INFO BaseTestObservables - Subscriber got Completed event
```
### back to blocking world
How about when we want to switch back to a blocking flow. We saw above how we need to explicitly use latching
to keep the [main] thread. Say we're incrementally switching from legacy code and we have a Service method
**Collection\<String\> findUsers()** inside this method we can still be reactive but to the caller of the method we
still need to block until we get all the elements of the Collection.
Using **blockingIterable** will block our Test thread till the Flow completes, waiting
for the events to be emitted(we're sleeping just to show it's not completing by chance).
```java
log.info("Starting");
Flowable<String> flowable = simpleFlowable()
.subscribeOn(Schedulers.io())
.subscribeOn(Schedulers.computation())
.map(val -> {
String newValue = "^^" + val + "^^";
log.info("Mapping new val {}", newValue);
Helpers.sleepMillis(500);
return newValue;
});
Iterable<String> iterable = flowable.blockingIterable(); //this call will block until
//the stream completes
iterable.forEach(val -> log.info("Received {}", val));
==========================
17:48:13 [RxCachedThreadScheduler-1] - Started emitting
17:48:13 [RxCachedThreadScheduler-1] - Emitting 1st
17:48:13 [RxCachedThreadScheduler-1] - Mapping new val ^^1^^
17:48:14 [RxCachedThreadScheduler-1] - Emitting 2nd
17:48:14 [main] - Received ^^1^^
17:48:14 [RxCachedThreadScheduler-1] - Mapping new val ^^2^^
17:48:14 [main] - Received ^^2^^
17:48:14 [main] - Finished blockingIterable
```
we can see the events being received back on the **\[main\]** thread.
```java
//block until the stream completes or throws an error.
flowable.blockingSubscribe(val -> log.info("Subscriber received {}", val));
```
## Flatmap operator
The flatMap operator is so important and has so many different uses it deserves it's own category to explain it.
Code at [Part06FlatMapOperator.java](https://github.com/balamaci/rxjava-playground/blob/master/src/test/java/com/balamaci/rx/Part06FlatMapOperator.java)
I like to think of it as a sort of **fork-join** operation because what flatMap does is it takes individual stream items
and maps each of them to an Observable(so it creates new Streams from each object) and then 'flattens' the events from
these Streams back as coming from a single stream.
Why this looks like fork-join because for each element you can fork some jobs that keeps emitting results,
and these results are emitted back as elements to the subscribers downstream
**Rules of thumb** to consider before getting comfortable with flatMap:
- When you have an 'item' **T** and a method **T -< Flowable<X>**, you need flatMap. Most common example is when you want
to make a remote call that returns an Observable / Flowable . For ex if you have a stream of customerIds, and downstream you
want to work with actual Customer objects:
- When you have Observable<Observable<T>>(aka stream of streams) you probably need flatMap. Because flatMap means you are subscribing
to each substream.
We use a simulated remote call that returns asynchronous events. This is a most common scenario to make a remote call for each stream element,
(although in non reactive world we're more likely familiar with remote operations returning Lists **T -> List<X>**).
Our simulated remote operation produces as many events as the length of the color string received as parameter every 200ms,
so for example **red : red0, red1, red2**
```java
private Flowable<String> simulateRemoteOperation(String color) {
return Flowable.intervalRange(1, color.length(), 0, 200, TimeUnit.MILLISECONDS)
.map(iteration -> color + iteration);
}
```
If we have a stream of color names:
```java
Flowable<String> colors = Flowable.just("orange", "red", "green")
```
to invoke the remote operation:
```java
Flowable<String> colors = Flowable.just("orange", "red", "green")
.flatMap(colorName -> simulatedRemoteOperation(colorName));
colors.subscribe(val -> log.info("Subscriber received: {}", val));
====
16:44:15 [Thread-0]- Subscriber received: orange0
16:44:15 [Thread-2]- Subscriber received: green0
16:44:15 [Thread-1]- Subscriber received: red0
16:44:15 [Thread-0]- Subscriber received: orange1
16:44:15 [Thread-2]- Subscriber received: green1
16:44:15 [Thread-1]- Subscriber received: red1
16:44:15 [Thread-0]- Subscriber received: orange2
16:44:15 [Thread-2]- Subscriber received: green2
16:44:15 [Thread-1]- Subscriber received: red2
16:44:15 [Thread-0]- Subscriber received: orange3
16:44:15 [Thread-2]- Subscriber received: green3
16:44:16 [Thread-0]- Subscriber received: orange4
16:44:16 [Thread-2]- Subscriber received: green4
16:44:16 [Thread-0]- Subscriber received: orange5
```
Notice how the results are coming intertwined(mixed) and it might not be as you expected it.This is because flatMap actually subscribes to it's inner Observables
returned from 'simulateRemoteOperation'. You can specify the **concurrency level of flatMap** as a parameter. Meaning
you can say how many of the substreams should be subscribed "concurrently" - after **onComplete** is triggered on the substreams,
a new substream is subscribed-.
By setting the concurrency to **1** we don't subscribe to other substreams until the current one finishes:
```
Flowable<String> colors = Flowable.just("orange", "red", "green")
.flatMap(val -> simulateRemoteOperation(val), 1); //
```
Notice now there is a sequence from each color before the next one appears
```
17:15:24 [Thread-0]- Subscriber received: orange0
17:15:24 [Thread-0]- Subscriber received: orange1
17:15:25 [Thread-0]- Subscriber received: orange2
17:15:25 [Thread-0]- Subscriber received: orange3
17:15:25 [Thread-0]- Subscriber received: orange4
17:15:25 [Thread-0]- Subscriber received: orange5
17:15:25 [Thread-1]- Subscriber received: red0
17:15:26 [Thread-1]- Subscriber received: red1
17:15:26 [Thread-1]- Subscriber received: red2
17:15:26 [Thread-2]- Subscriber received: green0
17:15:26 [Thread-2]- Subscriber received: green1
17:15:26 [Thread-2]- Subscriber received: green2
17:15:27 [Thread-2]- Subscriber received: green3
17:15:27 [Thread-2]- Subscriber received: green4
```
There is actually an operator which is basically this **flatMap with 1 concurrency called concatMap**.
Inside the flatMap we can operate on the substream with the same stream operators
```java
Observable<Pair<String, Integer>> colorsCounted = colors
.flatMap(colorName -> {
Observable<Long> timer = Observable.interval(2, TimeUnit.SECONDS);
return simulateRemoteOperation(colorName) // <- Still a stream
.zipWith(timer, (val, timerVal) -> val)
.count()
.map(counter -> new Pair<>(colorName, counter));
}
);
```
We can also use **switchIfEmpty** to provide some values when the original Publisher doesn't return anything, just completes.
```java
Flowable<String> colors = Flowable.just("red", "", "blue")
.flatMap(colorName -> simulateRemoteOperation(colorName)
.switchIfEmpty(Flowable.just("NONE")));
13:11:02 Subscriber received: red0
13:11:02 Subscriber received: red1
13:11:02 Subscriber received: red2
13:11:03 Subscriber received: NONE
13:11:03 Subscriber received: blue0
13:11:03 Subscriber received: blue1
13:11:03 Subscriber received: blue2
13:11:03 Subscriber received: blue3
13:11:03 Subscriber got Completed event
```
**flatMapIterable** is just an easy way to pass each of the elements of a collection
as a stream
```
Flowable<String> colors = Flowable.just(1)
.flatMapIterable(it -> generateColors());
private List<String> generateColors() {
return Arrays.asList("red", "green", "blue");
}
```
**switchMap** operator also prevents inter-leavings as only one of stream is subscribed at a time,
but this is controlled from upstream. If a new value comes from upstream, the current subscribed inner-stream
gets canceled and a new subscription is made for the new value.
The current stream will remain subscribed as long as there are no new values from upstream.
```java
Flowable<String> colors = Flowable.interval(0,400, TimeUnit.MILLISECONDS)
.zipWith(Arrays.asList("EUR", "USD", "GBP"), (it, currency) -> currency)
.doOnNext(ev -> log.info("Emitting {}", ev))
.switchMap(currency -> simulateRemoteOperation(currency)
.doOnSubscribe((subscription) -> log.info("Subscribed new"))
.doOnCancel(() -> log.info("Unsubscribed {}", currency))
);
```
17:45:16 [RxComputationThreadPool-1] INFO BaseTestObservables - Emitting EUR
17:45:16 [RxComputationThreadPool-1] INFO BaseTestObservables - Subscribed new
17:45:16 [RxComputationThreadPool-2] INFO BaseTestObservables - Subscriber received: EUR1
17:45:16 [RxComputationThreadPool-2] INFO BaseTestObservables - Subscriber received: EUR2
17:45:16 [RxComputationThreadPool-1] INFO BaseTestObservables - Emitting USD
17:45:16 [RxComputationThreadPool-1] INFO BaseTestObservables - Unsubscribed EUR
17:45:16 [RxComputationThreadPool-1] INFO BaseTestObservables - Subscribed new
17:45:16 [RxComputationThreadPool-3] INFO BaseTestObservables - Subscriber received: USD1
17:45:16 [RxComputationThreadPool-3] INFO BaseTestObservables - Subscriber received: USD2
17:45:17 [RxComputationThreadPool-1] INFO BaseTestObservables - Emitting GBP
17:45:17 [RxComputationThreadPool-1] INFO BaseTestObservables - Unsubscribed USD
17:45:17 [RxComputationThreadPool-1] INFO BaseTestObservables - Subscribed new
17:45:17 [RxComputationThreadPool-3] INFO BaseTestObservables - Subscriber received: USD3
17:45:17 [RxComputationThreadPool-4] INFO BaseTestObservables - Subscriber received: GBP1
17:45:17 [RxComputationThreadPool-4] INFO BaseTestObservables - Subscriber received: GBP2
17:45:17 [RxComputationThreadPool-4] INFO BaseTestObservables - Subscriber received: GBP3
17:45:17 [RxComputationThreadPool-4] INFO BaseTestObservables - Subscriber got Completed event
## Error handling
Code at [Part08ErrorHandling.java](https://github.com/balamaci/rxjava-playground/blob/master/src/test/java/com/balamaci/rx/Part08ErrorHandling.java)
Exceptions are for exceptional situations.
The Reactive Streams specification says that **exceptions are terminal operations**.
That means in case an error occurs, it triggers an unsubscription upstream and the error travels downstream to the Subscriber, invoking the 'onError' handler:
```java
Observable<String> colors = Observable.just("green", "blue", "red", "yellow")
.map(color -> {
if ("red".equals(color)) {
throw new RuntimeException("Encountered red");
}
return color + "*";
})
.map(val -> val + "XXX");
colors.subscribe(
val -> log.info("Subscriber received: {}", val),
exception -> log.error("Subscriber received error '{}'", exception.getMessage()),
() -> log.info("Subscriber completed")
);
```
returns:
```
23:30:17 [main] INFO - Subscriber received: green*XXX
23:30:17 [main] INFO - Subscriber received: blue*XXX
23:30:17 [main] ERROR - Subscriber received error 'Encountered red'
```
After the map() operator encounters an error it unsubscribes(cancels the subscription) from upstream
(therefore 'yellow' is not even emitted). The error travels downstream and triggers the error handler in the Subscriber.
There are operators to deal with error flow control:
### onErrorReturn
The 'onErrorReturn' operator replaces an exception with a value:
```java
Flowable<Integer> numbers = Flowable.just("1", "3", "a", "4", "5", "c")
.doOnCancel(() -> log.info("Subscription canceled"))
.map(Integer::parseInt)
.onErrorReturn(0);
subscribeWithLog(numbers);
======================
Subscriber received: 1
Subscriber received: 3
Subscription canceled
Subscriber received: 0
Subscriber got Completed event
```
Notice though how **it didn't prevent map() operator from unsubscribing from the Flowable**, but it did
trigger the normal **onNext** callback instead of **onError** in the subscriber.
Let's introduce a more realcase scenario of a simulated remote request that fails whenever it's invoked
with "red" and "black" color parameters otherwise just add some \*s.
```java
private Observable<String> simulateRemoteOperation(String color) {
return Observable.<String>create(subscriber -> {
if ("red".equals(color)) {
log.info("Emitting RuntimeException for {}", color);
throw new RuntimeException("Color red raises exception");
}
if ("black".equals(color)) {
log.info("Emitting IllegalArgumentException for {}", color);
throw new IllegalArgumentException("Black is not a color");
}
String value = "**" + color + "**";
log.info("Emitting {}", value);
subscriber.onNext(value);
subscriber.onCompleted();
});
}
Flowable<String> colors = Flowable.just("green", "blue", "red", "white", "blue")
.flatMap(color -> simulateRemoteOperation(color))
.onErrorReturn(throwable -> "-blank-");
subscribeWithLog(colors);
============
22:15:51 [main] INFO - Emitting **green**
22:15:51 [main] INFO - Subscriber received: **green**
22:15:51 [main] INFO - Emitting **blue**
22:15:51 [main] INFO - Subscriber received: **blue**
22:15:51 [main] INFO - Emitting RuntimeException for red
22:15:51 [main] INFO - Subscriber received: -blank-
22:15:51 [main] INFO - Subscriber got Completed event
```
flatMap encounters an error when it subscribes to 'red' substreams and thus still unsubscribe from 'colors'
stream and the remaining colors are not longer emitted
```java
Flowable<String> colors = Flowable.just("green", "blue", "red", "white", "blue")
.flatMap(color -> simulateRemoteOperation(color)
.onErrorReturn(throwable -> "-blank-")
);
```
onErrorReturn() is applied to the flatMap substream and thus translates the exception to a value and so flatMap
continues on with the other colors after red
returns:
```
22:15:51 [main] INFO - Emitting **green**
22:15:51 [main] INFO - Subscriber received: **green**
22:15:51 [main] INFO - Emitting **blue**
22:15:51 [main] INFO - Subscriber received: **blue**
22:15:51 [main] INFO - Emitting RuntimeException for red
22:15:51 [main] INFO - Subscriber received: -blank-
22:15:51 [main] INFO - Emitting **white**
22:15:51 [main] INFO - Subscriber received: **white**
22:15:51 [main] INFO - Emitting **blue**
22:15:51 [main] INFO - Subscriber received: **blue**
22:15:51 [main] INFO - Subscriber got Completed event
```
### onErrorResumeNext
onErrorResumeNext() returns a stream instead of an exception, useful for example to invoke a fallback
method that returns an alternate Stream
```java
Observable<String> colors = Observable.just("green", "blue", "red", "white", "blue")
.flatMap(color -> simulateRemoteOperation(color)
.onErrorResumeNext(th -> {
if (th instanceof IllegalArgumentException) {
return Observable.error(new RuntimeException("Fatal, wrong arguments"));
}
return fallbackRemoteOperation();
})
);
private Observable<String> fallbackRemoteOperation() {
return Observable.just("blank");
}
```
## Retrying
### timeout()
Timeout operator raises exception when there are no events incoming before it's predecessor in the specified time limit.
### retry()
**retry()** - resubscribes in case of exception to the Observable
```java
Flowable<String> colors = Flowable.just("red", "blue", "green", "yellow")
.concatMap(color -> delayedByLengthEmitter(TimeUnit.SECONDS, color)
//if there are no events flowing in the timeframe
.timeout(6, TimeUnit.SECONDS)
.retry(2)
.onErrorResumeNext(Observable.just("blank"))
);
subscribeWithLog(colors.toBlocking());
```
returns
```
12:40:16 [main] INFO - Received red delaying for 3
12:40:19 [main] INFO - Subscriber received: red
12:40:19 [RxComputationScheduler-2] INFO - Received blue delaying for 4
12:40:23 [main] INFO - Subscriber received: blue
12:40:23 [RxComputationScheduler-4] INFO - Received green delaying for 5
12:40:28 [main] INFO - Subscriber received: green
12:40:28 [RxComputationScheduler-6] INFO - Received yellow delaying for 6
12:40:34 [RxComputationScheduler-7] INFO - Received yellow delaying for 6
12:40:40 [RxComputationScheduler-1] INFO - Received yellow delaying for 6
12:40:46 [main] INFO - Subscriber received: blank
12:40:46 [main] INFO - Subscriber got Completed event
```
When you want to retry considering the thrown exception type:
```java
Observable<String> colors = Observable.just("blue", "red", "black", "yellow")
.flatMap(colorName -> simulateRemoteOperation(colorName)
.retry((retryAttempt, exception) -> {
if (exception instanceof IllegalArgumentException) {
log.error("{} encountered non retry exception ", colorName);
return false;
}
log.info("Retry attempt {} for {}", retryAttempt, colorName);
return retryAttempt <= 2;
})
.onErrorResumeNext(Observable.just("generic color"))
);
```
```
13:21:37 [main] INFO - Emitting **blue**
13:21:37 [main] INFO - Emitting RuntimeException for red
13:21:37 [main] INFO - Retry attempt 1 for red
13:21:37 [main] INFO - Emitting RuntimeException for red
13:21:37 [main] INFO - Retry attempt 2 for red
13:21:37 [main] INFO - Emitting RuntimeException for red
13:21:37 [main] INFO - Retry attempt 3 for red
13:21:37 [main] INFO - Emitting IllegalArgumentException for black
13:21:37 [main] ERROR - black encountered non retry exception
13:21:37 [main] INFO - Emitting **yellow**
13:21:37 [main] INFO - Subscriber received: **blue**
13:21:37 [main] INFO - Subscriber received: generic color
13:21:37 [main] INFO - Subscriber received: generic color
13:21:37 [main] INFO - Subscriber received: **yellow**
13:21:37 [main] INFO - Subscriber got Completed event
```
### retryWhen
A more complex retry logic like implementing a backoff strategy in case of exception
This can be obtained with **retryWhen**(exceptionObservable -> Observable)
retryWhen resubscribes when an event from an Observable is emitted. It receives as parameter an exception stream
we zip the exceptionsStream with a .range() stream to obtain the number of retries,
however we want to wait a little before retrying so in the zip function we return a delayed event - .timer()
The delay also needs to be subscribed to be effected so we also flatMap
```java
Observable<String> colors = Observable.just("blue", "green", "red", "black", "yellow");
colors.flatMap(colorName ->
simulateRemoteOperation(colorName)
.retryWhen(exceptionStream -> exceptionStream
.zipWith(Observable.range(1, 3), (exc, attempts) -> {
//don't retry for IllegalArgumentException
if(exc instanceof IllegalArgumentException) {
return Observable.error(exc);
}
if(attempts < 3) {
return Observable.timer(2 * attempts, TimeUnit.SECONDS);
}
return Observable.error(exc);
})
.flatMap(val -> val)
)
.onErrorResumeNext(Observable.just("generic color")
)
);
```
```
15:20:23 [main] INFO - Emitting **blue**
15:20:23 [main] INFO - Emitting **green**
15:20:23 [main] INFO - Emitting RuntimeException for red
15:20:23 [main] INFO - Emitting IllegalArgumentException for black
15:20:23 [main] INFO - Emitting **yellow**
15:20:23 [main] INFO - Subscriber received: **blue**
15:20:23 [main] INFO - Subscriber received: **green**
15:20:23 [main] INFO - Subscriber received: generic color
15:20:23 [main] INFO - Subscriber received: **yellow**
15:20:25 [RxComputationScheduler-1] INFO - Emitting RuntimeException for red
15:20:29 [RxComputationScheduler-2] INFO - Emitting RuntimeException for red
15:20:29 [main] INFO - Subscriber received: generic color
15:20:29 [main] INFO - Subscriber got Completed event
```
**retryWhen vs repeatWhen**
With similar names it worth noting the difference.
- repeat() resubscribes when it receives onCompleted().
- retry() resubscribes when it receives onError().
Example using repeatWhen() to implement periodic polling
```java
remoteOperation.repeatWhen(completed -> completed
.delay(2, TimeUnit.SECONDS))
```
## Backpressure
It can be the case of a slow consumer that cannot keep up with the producer that is producing too many events
that the subscriber cannot process.
Backpressure relates to a feedback mechanism through which the subscriber can signal to the producer how much data
it can consume and so to produce only that amount.
The [reactive-streams](https://github.com/reactive-streams/reactive-streams-jvm) section above we saw that besides the
**onNext, onError** and **onComplete** handlers, the Subscriber
has an **onSubscribe(Subscription)**, Subscription through which it can signal upstream it's ready to receive a number
of items and after it processes the items request another batch.
```java
public interface Subscriber<T> {
//signals to the Publisher to start sending events
public void onSubscribe(Subscription s);
public void onNext(T t);
public void onError(Throwable t);
public void onComplete();
}
```
The methods exposed by **Subscription** through which the subscriber comunicates with the upstream:
```java
public interface Subscription {
public void request(long n); //request n items
public void cancel();
}
```
So in theory the Subscriber can prevent being overloaded by requesting an initial number of items. The Publisher would
send those items downstream and not produce any more, until the Subscriber would request more. We say in theory because
until now we did not see a custom **onSubscribe(Subscription)** request being implemented. This is because if not specified explicitly,
there is a default implementation which requests of **Long.MAX_VALUE** which basically means "send all you have".
Neither did we see the code in the producer that takes consideration of the number of items requested by the subscriber.
```java
Flowable.create(subscriber -> {
log.info("Started emitting");
for(int i=0; i < 300; i++) {
if(subscriber.isCanceled()) {
return;
}
log.info("Emitting {}", i);
subscriber.next(i);
}
subscriber.complete();
}, BackpressureStrategy.BUFFER); //BackpressureStrategy will be explained further bellow
```
Looks like it's not possible to slow down production based on request(as there is no reference to the requested items),
we can at most stop production if the subscriber canceled subscription.
This can be done if we extend Flowable so we can pass our custom Subscription type to the downstream subscriber:
```java
private class CustomRangeFlowable extends Flowable<Integer> {
private int startFrom;
private int count;
CustomRangeFlowable(int startFrom, int count) {
this.startFrom = startFrom;
this.count = count;
}
@Override
public void subscribeActual(Subscriber<? super Integer> subscriber) {
subscriber.onSubscribe(new CustomRangeSubscription(startFrom, count, subscriber));
}
class CustomRangeSubscription implements Subscription {
volatile boolean cancelled;
boolean completed = false;
private int count;
private int currentCount;
private int startFrom;
private Subscriber<? super Integer> actualSubscriber;
CustomRangeSubscription(int startFrom, int count, Subscriber<? super Integer> actualSubscriber) {
this.count = count;
this.startFrom = startFrom;
this.actualSubscriber = actualSubscriber;
}
@Override
public void request(long items) {
log.info("Downstream requests {} items", items);
for(int i=0; i < items; i++) {
if(cancelled || completed) {
return;
}
if(currentCount == count) {
completed = true;
if(cancelled) {
return;
}
actualSubscriber.onComplete();
return;
}
int emitVal = startFrom + currentCount;
currentCount++;
actualSubscriber.onNext(emitVal);
}
}
@Override
public void cancel() {
cancelled = true;
}
}
}
```
Now lets see how we can custom control how many items we request from upstream, to simulate an initial big request,
and then a request for other smaller batches of items as soon as the subscriber finishes and is ready for another batch.
```java
Flowable<Integer> flowable = new CustomRangeFlowable(5, 10);
flowable.subscribe(new Subscriber<Integer>() {
private Subscription subscription;
private int backlogItems;
private final int BATCH = 2;
private final int INITIAL_REQ = 5;
@Override
public void onSubscribe(Subscription subscription) {
this.subscription = subscription;
backlogItems = INITIAL_REQ;
log.info("Initial request {}", backlogItems);
subscription.request(backlogItems);
}
@Override
public void onNext(Integer val) {
log.info("Subscriber received {}", val);
backlogItems --;
if(backlogItems == 0) {
backlogItems = BATCH;
subscription.request(BATCH);
}
}
@Override
public void onError(Throwable throwable) {
log.info("Subscriber encountered error");
}
@Override
public void onComplete() {
log.info("Subscriber completed");
}
});
=====================
Initial request 5
Downstream requests 5 items
Subscriber received 5
Subscriber received 6
Subscriber received 7
Subscriber received 8
Subscriber received 9
Downstream requests 2 items
Subscriber received 10
Subscriber received 11
Downstream requests 2 items
Subscriber received 12
Subscriber received 13
Downstream requests 2 items
Subscriber received 14
Subscriber completed
```
Returning to the _Flowable.create()_ example since it's not taking any account of the requested
items by the subscriber, does it mean it might overwhelm a slow Subscriber?
```java
private Flowable<Integer> createFlowable(int items,
BackpressureStrategy backpressureStrategy) {
return Flowable.create(subscriber -> {
log.info("Started emitting");
for (int i = 0; i < items; i++) {
if(subscriber.isCancelled()) {
return;
}
log.info("Emitting {}", i);
subscriber.onNext(i);
}
subscriber.onComplete();
}, backpressureStrategy); //can be BackpressureStrategy.DROP, BUFFER, LATEST,..
```
This is where the 2nd parameter _BackpressureStrategy_ comes in that allows you to specify what to do
in the case.
- BackpressureStrategy.BUFFER buffer in memory the events that overflow. Of course is we don't drop over some threshold, it might lead to OufOfMemory.
- BackpressureStrategy.DROP just drop the overflowing events
- BackpressureStrategy.LATEST keep only recent event and discards previous unconsumed events.
- BackpressureStrategy.ERROR we get an error in the subscriber immediately
- BackpressureStrategy.MISSING means we don't care about backpressure(we let one of the downstream operators
onBackpressureXXX handle it -explained further down-)
Still what does it mean to 'overwhelm' the subscriber?
It means to emit more items than requested by downstream subscriber.
But we said that by default the subscriber requests Long.MAX_VALUE since the code
**flowable.subscribe(onNext(), onError, onComplete)** uses a default **onSubscribe**:
```
(subscription) -> subscription.request(Long.MAX_VALUE);
```
so unless we override it like in our custom Subscriber above, it means it would never overflow. But between the Publisher and the Subscriber you'd have a series of operators.
When we subscribe, a Subscriber travels up through all operators to the original Publisher and some operators override
the requested items upstream. One such operator is **observeOn**() which makes it's own request to the upstream Publisher(256 by default),
but can take a parameter to specify the request size.
```
Flowable<Integer> flowable = createFlowable(5, BackpressureStrategy.DROP)
.observeOn(Schedulers.io(), false, 3);
flowable.subscribe((val) -> {
log.info("Subscriber received: {}", val);
Helpers.sleepMillis(millis);
}, logError(), logComplete());
======
[main] - Started emitting
[main] - Emitting 0
[main] - Emitting 1
[main] - Emitting 2
[main] - Emitting 3
[main] - Emitting 4
[RxCachedThreadScheduler-1] - Subscriber received: 0
[RxCachedThreadScheduler-1] - Subscriber received: 1
[RxCachedThreadScheduler-1] - Subscriber received: 2
[RxCachedThreadScheduler-1] - Subscriber got Completed event
```
This is expected, as the subscription travels upstream through the operators to the source Flowable, while initially
the Subscriber requesting Long.MAX_VALUE from the upstream operator **observeOn**, which in turn subscribes to the source and it requests just 3 items from the source instead.
Since we used **BackpressureStrategy.DROP** all the items emitted outside the expected 3, get discarded and thus never reach our subscriber.
You may wonder what would have happened if we didn't use **observeOn**. We had to use it if we wanted to be able
to produce faster than the subscriber(it wasn't just to show a limited request operator), because we'd need a
separate thread to produce events faster than the subscriber processes them.
Also you can transform an Observable to Flowable by specifying a BackpressureStrategy, otherwise Observables
just throw exception on overflowing(same as using BackpressureStrategy.DROP in Flowable.create()).
```
Flowable flowable = observable.toFlowable(BackpressureStrategy.DROP)
```
so can a hot Publisher be converted to a Flowable:
```
PublishSubject<Integer> subject = PublishSubject.create();
Flowable<Integer> flowable = subject
.toFlowable(BackpressureStrategy.DROP)
```
There are also specialized operators to handle backpressure the onBackpressureXXX operators: **onBackpressureBuffer**,
**onBackpressureDrop**, **onBackpressureLatest**
These operators request Long.MAX_VALUE(unbounded amount) from upstream and then take it upon themselves to manage the
requests from downstream.
In the case of _onBackpressureBuffer_ it adds in an internal queue and send downstream the events as requested,
_onBackpressureDrop_ just discards events that are received from upstream more than requested from downstream,
_onBackpressureLatest_ also drops emitted events excluding the last emitted event(most recent).
```java
Flowable<Integer> flowable = createFlowable(10, BackpressureStrategy.MISSING)
.onBackpressureBuffer(5, () -> log.info("Buffer has overflown"));
flowable = flowable
.observeOn(Schedulers.io(), false, 3);
subscribeWithSlowSubscriber(flowable);
=====
[main] - Started emitting
[main] - Emitting 0
[main] - Emitting 1
[RxCachedThreadScheduler-1] - Subscriber received: 0
[main] - Emitting 2
[main] - Emitting 3
[main] - Emitting 4
[main] - Emitting 5
[main] - Emitting 6
[main] - Emitting 7
[main] - Emitting 8
[main] - Emitting 9
[main] - Buffer has overflown
[RxCachedThreadScheduler-1] ERROR - Subscriber received error 'Buffer is full'
```
We create the Flowable with _BackpressureStrategy.MISSING_ saying we don't care about backpressure
but let one of the onBackpressureXXX operators handle it.
Notice however
Chaining together multiple onBackpressureXXX operators doesn't actually make sense
Using something like
```java
Flowable<Integer> flowable = createFlowable(10, BackpressureStrategy.MISSING)
.onBackpressureBuffer(5)
.onBackpressureDrop((val) -> log.info("Dropping {}", val))
flowable = flowable
.observeOn(Schedulers.io(), false, 3);
subscribeWithSlowSubscriber(flowable);
```
is not behaving as probably you'd expected - buffer 5 values, and then dropping overflowing events-.
Because _onBackpressureDrop_ subscribes to the previous _onBackpressureBuffer_ operator
signaling it's requesting **Long.MAX_VALUE**(unbounded amount) from it.
Thus **onBackpressureBuffer** will never feel its subscriber is overwhelmed and never "trigger", meaning that the last
onBackpressureXXX operator overrides the previous one if they are chained.
Of course for implementing an event dropping strategy after a full buffer, there is the special overrided
version of **onBackpressureBuffer** that takes a **BackpressureOverflowStrategy**.
```java
Flowable<Integer> flowable = createFlowable(10, BackpressureStrategy.MISSING)
.onBackpressureBuffer(5, () -> log.info("Buffer has overflown"),
BackpressureOverflowStrategy.DROP_OLDEST);
flowable = flowable
.observeOn(Schedulers.io(), false, 3);
subscribeWithSlowSubscriber(flowable);
===============
[main] - Started emitting
[main] - Emitting 0
[main] - Emitting 1
[RxCachedThreadScheduler-1] - Subscriber received: 0
[main] - Emitting 2
[main] - Emitting 3
[main] - Emitting 4
[main] - Emitting 5
[main] - Emitting 6
[main] - Emitting 7
[main] - Emitting 8
[main] - Buffer has overflown
[main] - Emitting 9
[main] - Buffer has overflown
[RxCachedThreadScheduler-1] - Subscriber received: 1
[RxCachedThreadScheduler-1] - Subscriber received: 2
[RxCachedThreadScheduler-1] - Subscriber received: 5
[RxCachedThreadScheduler-1] - Subscriber received: 6
[RxCachedThreadScheduler-1] - Subscriber received: 7
[RxCachedThreadScheduler-1] - Subscriber received: 8
[RxCachedThreadScheduler-1] - Subscriber received: 9
[RxCachedThreadScheduler-1] - Subscriber got Completed event
```
onBackpressureXXX operators can be added whenever necessary and it's not limited to cold publishers and we can use them
on hot publishers also.
## Articles and books for further reading
[Reactive Programming with RxJava](http://shop.oreilly.com/product/0636920042228.do)
================================================
FILE: _config.yml
================================================
theme: jekyll-theme-cayman
================================================
FILE: pom.xml
================================================
<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<groupId>com.balamaci</groupId>
<artifactId>rxjava-playground</artifactId>
<version>1.0-SNAPSHOT</version>
<name>RxJava Playground</name>
<description>RxJava Playground - Test scenarios describing RxJava functionality</description>
<properties>
<rxjava.version>2.2.3</rxjava.version>
<slf4j.version>1.7.25</slf4j.version>
</properties>
<dependencies>
<dependency>
<groupId>io.reactivex.rxjava2</groupId>
<artifactId>rxjava</artifactId>
<version>${rxjava.version}</version>
</dependency>
<!-- Logging -->
<dependency>
<groupId>org.slf4j</groupId>
<artifactId>slf4j-api</artifactId>
<version>${slf4j.version}</version>
</dependency>
<dependency>
<groupId>org.slf4j</groupId>
<artifactId>slf4j-simple</artifactId>
<version>${slf4j.version}</version>
</dependency>
<dependency>
<groupId>junit</groupId>
<artifactId>junit</artifactId>
<version>4.12</version>
<scope>test</scope>
</dependency>
<!-- https://mvnrepository.com/artifact/io.vavr/vavr -->
<dependency>
<groupId>io.vavr</groupId>
<artifactId>vavr</artifactId>
<version>0.9.2</version>
</dependency>
</dependencies>
<build>
<plugins>
<plugin>
<inherited>true</inherited>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-compiler-plugin</artifactId>
<version>3.1</version>
<configuration>
<source>1.8</source>
<target>1.8</target>
<encoding>UTF-8</encoding>
<showWarnings>true</showWarnings>
<showDeprecation>true</showDeprecation>
</configuration>
</plugin>
</plugins>
</build>
</project>
================================================
FILE: src/test/java/com/balamaci/rx/BaseTestObservables.java
================================================
package com.balamaci.rx;
import com.balamaci.rx.util.Helpers;
import io.reactivex.BackpressureStrategy;
import io.reactivex.Flowable;
import io.reactivex.Observable;
import io.reactivex.Single;
import io.reactivex.functions.Action;
import io.reactivex.functions.Consumer;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import java.util.concurrent.CountDownLatch;
import java.util.concurrent.TimeUnit;
/**
* @author sbalamaci
*/
public interface BaseTestObservables {
Logger log = LoggerFactory.getLogger(BaseTestObservables.class);
default Flowable<Integer> simpleFlowable() {
return Flowable.create(subscriber -> {
log.info("Started emitting");
log.info("Emitting 1st");
subscriber.onNext(1);
log.info("Emitting 2nd");
subscriber.onNext(2);
subscriber.onComplete();
}, BackpressureStrategy.BUFFER);
}
default <T> void subscribeWithLog(Flowable<T> flowable) {
flowable.subscribe(
logNext(),
logError(),
logComplete()
);
}
default <T> void subscribeWithLog(Observable<T> observable) {
observable.subscribe(
logNext(),
logError(),
logComplete()
);
}
default <T> void subscribeWithLogOutputWaitingForComplete(Observable<T> observable) {
CountDownLatch latch = new CountDownLatch(1);
observable.subscribe(
logNext(),
logError(latch),
logComplete(latch)
);
Helpers.wait(latch);
}
default <T> void subscribeWithLog(Single<T> single) {
single.subscribe(
val -> log.info("Subscriber received: {}", val),
logError()
);
}
default <T> void subscribeWithLogOutputWaitingForComplete(Flowable<T> flowable) {
CountDownLatch latch = new CountDownLatch(1);
flowable.subscribe(
logNext(),
logError(latch),
logComplete(latch)
);
Helpers.wait(latch);
}
default <T> void subscribeWithLogOutputWaitingForComplete(Single<T> single) {
CountDownLatch latch = new CountDownLatch(1);
single.subscribe(
val -> {
log.info("Subscriber received: {} and completed", val);
latch.countDown();
},
logError(latch)
);
Helpers.wait(latch);
}
default <T> Flowable<T> periodicEmitter(T t1, T t2, T t3, int interval, TimeUnit unit) {
return periodicEmitter(t1, t2, t3, interval, unit, interval);
}
default <T> Flowable<T> periodicEmitter(T t1, T t2, T t3, int interval,
TimeUnit unit, int initialDelay) {
Flowable<T> itemsStream = Flowable.just(t1, t2, t3);
Flowable<Long> timer = Flowable.interval(initialDelay, interval, unit);
return Flowable.zip(itemsStream, timer, (key, val) -> key);
}
default <T> Observable<T> periodicEmitter(T[] items, int interval,
TimeUnit unit, int initialDelay) {
Observable<T> itemsStream = Observable.fromArray(items);
Observable<Long> timer = Observable.interval(initialDelay, interval, unit);
return Observable.zip(itemsStream, timer, (key, val) -> key);
}
default <T> Observable<T> periodicEmitter(T[] items, int interval,
TimeUnit unit) {
return periodicEmitter(items, interval, unit);
}
default Flowable<String> delayedByLengthEmitter(TimeUnit unit, String...items) {
Flowable<String> itemsStream = Flowable.fromArray(items);
return itemsStream.concatMap(item -> Flowable.just(item)
.doOnNext(val -> log.info("Received {} delaying for {} ", val, val.length()))
.delay(item.length(), unit)
);
}
default <T> Consumer<? super T> logNext() {
return (Consumer<T>) val -> log.info("Subscriber received: {}", val);
}
default <T> Consumer<? super T> logNextAndSlowByMillis(int millis) {
return (Consumer<T>) val -> {
log.info("Subscriber received: {}", val);
Helpers.sleepMillis(millis);
};
}
default Consumer<? super Throwable> logError() {
return err -> log.error("Subscriber received error '{}'", err.getMessage());
}
default Consumer<? super Throwable> logError(CountDownLatch latch) {
return err -> {
log.error("Subscriber received error '{}'", err.getMessage());
latch.countDown();
};
}
default Action logComplete() {
return () -> log.info("Subscriber got Completed event");
}
default Action logComplete(CountDownLatch latch) {
return () -> {
log.info("Subscriber got Completed event");
latch.countDown();
};
}
}
================================================
FILE: src/test/java/com/balamaci/rx/Part01CreateFlowable.java
================================================
package com.balamaci.rx;
import com.balamaci.rx.util.Helpers;
import io.reactivex.BackpressureStrategy;
import io.reactivex.Flowable;
import io.reactivex.Observable;
import io.reactivex.Single;
import io.reactivex.disposables.Disposable;
import org.junit.Test;
import java.util.Arrays;
import java.util.concurrent.CompletableFuture;
/**
*
*
* @author sbalamaci
*/
public class Part01CreateFlowable implements BaseTestObservables {
@Test
public void just() {
Flowable<Integer> flowable = Flowable.just(1, 5, 10);
flowable.subscribe(
val -> log.info("Subscriber received: {}", val));
}
@Test
public void range() {
Flowable<Integer> flowable = Flowable.range(1, 10);
flowable.subscribe(
val -> log.info("Subscriber received: {}", val));
}
@Test
public void fromArray() {
Flowable<String> flowable = Flowable.fromArray(new String[]{"red", "green", "blue", "black"});
flowable.subscribe(
val -> log.info("Subscriber received: {}"));
}
@Test
public void fromIterable() {
Flowable<String> flowable = Flowable.fromIterable(Arrays.asList("red", "green", "blue"));
flowable.subscribe(
val -> log.info("Subscriber received: {}"));
}
/**
* We can also create a stream from Future, making easier to switch from legacy code to reactive
*/
@Test
public void fromFuture() {
CompletableFuture<String> completableFuture = CompletableFuture.
supplyAsync(() -> { //starts a background thread the ForkJoin common pool
Helpers.sleepMillis(100);
return "red";
});
Single<String> single = Single.fromFuture(completableFuture);
single.subscribe(val -> log.info("Stream completed successfully : {}", val));
}
/**
* Using Flowable.create to handle the actual emissions of events with the events like onNext, onComplete, onError
* <p>
* When subscribing to the Flowable / Observable with flowable.subscribe(), the lambda code inside create() gets executed.
* Flowable.subscribe can take 3 handlers for each type of event - onNext, onError and onComplete
* <p>
* When using Observable.create you need to be aware of <b>Backpressure</b> and that Observables based on 'create' method
* are not Backpressure aware {@see Part09BackpressureHandling}.
*/
@Test
public void createSimpleObservable() {
Flowable<Integer> flowable = Flowable.create(subscriber -> {
log.info("Started emitting");
log.info("Emitting 1st");
subscriber.onNext(1);
log.info("Emitting 2nd");
subscriber.onNext(2);
subscriber.onComplete();
}, BackpressureStrategy.BUFFER);
log.info("Subscribing");
Disposable subscription = flowable.subscribe(
val -> log.info("Subscriber received: {}", val),
err -> log.error("Subscriber received error", err),
() -> log.info("Subscriber got Completed event"));
}
/**
* Observable emits an Error event which is a terminal operation and the subscriber is no longer executing
* it's onNext callback. We're actually breaking the the Observable contract that we're still emitting events
* after onComplete or onError have fired.
*/
@Test
public void createSimpleObservableThatEmitsError() {
Observable<Integer> observable = Observable.create(subscriber -> {
log.info("Started emitting");
log.info("Emitting 1st");
subscriber.onNext(1);
subscriber.onError(new RuntimeException("Test exception"));
log.info("Emitting 2nd");
subscriber.onNext(2);
});
Disposable disposable = observable.subscribe(
val -> log.info("Subscriber received: {}", val),
err -> log.error("Subscriber received error", err),
() -> log.info("Subscriber got Completed event")
);
}
/**
* Observables are lazy, meaning that the code inside create() doesn't get executed without subscribing to the Observable
* So even if we sleep for a long time inside create() method(to simulate a costly operation),
* without subscribing to this Observable the code is not executed and the method returns immediately.
*/
@Test
public void flowablesAreLazy() {
Observable<Integer> flowable = Observable.create(subscriber -> {
log.info("Started emitting but sleeping for 5 secs"); //this is not executed
Helpers.sleepMillis(5000);
subscriber.onNext(1);
});
log.info("Finished");
}
/**
* When subscribing to an Observable, the create() method gets executed for each subscription
* this means that the events inside create are re-emitted to each subscriber. So every subscriber will get the
* same events and will not lose any events.
*/
@Test
public void multipleSubscriptionsToSameObservable() {
Observable<Integer> flowable = Observable.create(subscriber -> {
log.info("Started emitting");
log.info("Emitting 1st event");
subscriber.onNext(1);
log.info("Emitting 2nd event");
subscriber.onNext(2);
subscriber.onComplete();
});
log.info("Subscribing 1st subscriber");
flowable.subscribe(val -> log.info("First Subscriber received: {}", val));
log.info("=======================");
log.info("Subscribing 2nd subscriber");
flowable.subscribe(val -> log.info("Second Subscriber received: {}", val));
}
/**
* Inside the create() method, we can check is there are still active subscribers to our Observable.
* It's a way to prevent to do extra work(like for ex. querying a datasource for entries) if no one is listening
* In the following example we'd expect to have an infinite stream, but because we stop if there are no active
* subscribers we stop producing events.
* The take() operator unsubscribes from the Observable after it's received the specified amount of events
* while in the same time calling onComplete() downstream.
*/
@Test
public void showUnsubscribeObservable() {
Observable<Integer> observable = Observable.create(subscriber -> {
int i = 1;
while(true) {
if(subscriber.isDisposed()) {
break;
}
subscriber.onNext(i++);
}
//subscriber.onCompleted(); too late to emit Complete event since subscriber already unsubscribed
subscriber.setCancellable(() -> log.info("Subscription canceled"));
});
observable
.take(5)
.map(val -> "*" + val + "*")
.subscribe(
val -> log.info("Subscriber received: {}", val),
err -> log.error("Subscriber received error", err),
() -> log.info("Subscriber got Completed event") //The Complete event is triggered by 'take()' operator
);
}
/**
* .defer acts as a factory of Flowables, just when subscribed it actually invokes the logic to create the
* Flowable to be emitted.
* It's an easy way to switch from a blocking method to a reactive Single/Flowable.
* Simply using Flowable.just(blockingOp()) would still block, as Java needs to resolve the parameter when invoking
* Flux.just(param) method, so blockingOp() method would still be invoked(and block).
*
* The solution is to wrap the blockingOp() method inside a lambda that gets passed to .defer(() -> blockingOp())
*
*/
@Test
public void deferCreateObservable() {
log.info("Starting blocking Flowable");
Flowable<String> flowableBlocked = Flowable.just((blockingOperation()));
log.info("After blocking Flowable");
log.info("Starting defered op");
Flowable<String> stream = Flowable.defer(() -> Flowable.just(blockingOperation()));
log.info("After defered op");
log.info("Sleeping a little before subscribing and executing the defered code");
Helpers.sleepMillis(2000);
log.info("Subscribing");
subscribeWithLogOutputWaitingForComplete(stream);
}
private String blockingOperation() {
log.info("Blocking 1sec...");
Helpers.sleepMillis(1000);
log.info("Ended blocking");
return "Hello";
}
}
================================================
FILE: src/test/java/com/balamaci/rx/Part02SimpleOperators.java
================================================
package com.balamaci.rx;
import com.balamaci.rx.util.Helpers;
import io.reactivex.Flowable;
import io.reactivex.Single;
import org.junit.Test;
import java.util.ArrayList;
import java.util.List;
import java.util.Random;
import java.util.concurrent.CountDownLatch;
import java.util.concurrent.TimeUnit;
/**
* @author sbalamaci
*/
public class Part02SimpleOperators implements BaseTestObservables {
/**
* Delay operator - the Thread.sleep of the reactive world, it's pausing for a particular increment of time
* before emitting the whole range events which are thus shifted by the specified time amount.
*
* The delay operator uses a Scheduler {@see Part06Schedulers} by default, which actually means it's
* running the operators and the subscribe operations on a different thread, which means the test method
* will terminate before we see the text from the log. That is why we use the CountDownLatch waiting for the
* completion of the stream.
*
*/
@Test
public void delayOperator() {
log.info("Starting");
CountDownLatch latch = new CountDownLatch(1);
Flowable.range(0, 2)
.doOnNext(val -> log.info("Emitted {}", val))
.delay(5, TimeUnit.SECONDS)
.subscribe(
tick -> log.info("Tick {}", tick),
(ex) -> log.info("Error emitted"),
() -> {
log.info("Completed");
latch.countDown();
});
Helpers.wait(latch);
}
/**
* Timer operator waits for a specific amount of time before it emits an event and then completes
*/
@Test
public void timerOperator() {
log.info("Starting");
Flowable<Long> flowable = Flowable.timer(5, TimeUnit.SECONDS);
subscribeWithLogOutputWaitingForComplete(flowable);
}
@Test
public void delayOperatorWithVariableDelay() {
log.info("Starting");
Flowable<Integer> flowable = Flowable.range(0, 5)
.doOnNext(val -> log.info("Emitted {}", val))
.delay(val -> Flowable.timer(val * 2, TimeUnit.SECONDS));
subscribeWithLogOutputWaitingForComplete(flowable);
}
/**
* Periodically emits a number starting from 0 and then increasing the value on each emission
*/
@Test
public void intervalOperator() {
log.info("Starting");
Flowable<Long> flowable = Flowable.interval(1, TimeUnit.SECONDS)
.take(5);
subscribeWithLogOutputWaitingForComplete(flowable);
}
/**
* scan operator - takes an initial value and a function(accumulator, currentValue). It goes through the events
* sequence and combines the current event value with the previous result(accumulator) emitting downstream the
* the function's result for each event(the initial value is used for the first event).
*/
@Test
public void scanOperator() {
Flowable<Integer> numbers = Flowable.just(3, 5, -2, 9)
.scan(0, (totalSoFar, currentValue) -> {
log.info("totalSoFar={}, emitted={}", totalSoFar, currentValue);
return totalSoFar + currentValue;
});
subscribeWithLog(numbers);
}
/**
* reduce operator acts like the scan operator but it only passes downstream the final result
* (doesn't pass the intermediate results downstream) so the subscriber receives just one event
*/
@Test
public void reduceOperator() {
Single<Integer> numbers = Flowable.just(3, 5, -2, 9)
.reduce(0, (totalSoFar, val) -> {
log.info("totalSoFar={}, emitted={}", totalSoFar, val);
return totalSoFar + val;
});
subscribeWithLog(numbers);
}
/**
* collect operator acts similar to the reduce() operator, but while the reduce() operator uses a reduce function
* which returns a value, the collect() operator takes a container supplie and a function which doesn't return
* anything(a consumer). The mutable container is passed for every event and thus you get a chance to modify it
* in this collect consumer function
*/
@Test
public void collectOperator() {
Single<List<Integer>> numbers = Flowable.just(3, 5, -2, 9)
.collect(ArrayList::new, (container, value) -> {
log.info("Adding {} to container", value);
container.add(value);
//notice we don't need to return anything
});
subscribeWithLog(numbers);
}
/**
* repeat resubscribes to the observable after it receives onComplete
*/
@Test
public void repeat() {
Flowable<Integer> random = Flowable.defer(() -> {
Random rand = new Random();
return Flowable.just(rand.nextInt(20));
})
.repeat(5);
subscribeWithLogOutputWaitingForComplete(random);
}
}
================================================
FILE: src/test/java/com/balamaci/rx/Part03MergingStreams.java
================================================
package com.balamaci.rx;
import com.balamaci.rx.util.Helpers;
import com.balamaci.rx.util.Pair;
import io.reactivex.Flowable;
import io.reactivex.Single;
import org.junit.Test;
import java.util.concurrent.CompletableFuture;
import java.util.concurrent.TimeUnit;
/**
* Operators for working with multiple streams
*
*
*/
public class Part03MergingStreams implements BaseTestObservables {
/**
* Zip operator operates sort of like a zipper in the sense that it takes an event from one stream and waits
* for an event from another other stream. Once an event for the other stream arrives, it uses the zip function
* to merge the two events.
* <p>
* This is an useful scenario when for example you want to make requests to remote services in parallel and
* wait for both responses before continuing.
* <p>
* Zip operator besides the streams to zip, also takes as parameter a function which will produce the
* combined result of the zipped streams once each stream emitted it's value
*/
@Test
public void zipUsedForTakingTheResultOfCombinedAsyncOperations() {
Single<Boolean> isUserBlockedStream = Single.fromFuture(CompletableFuture.supplyAsync(() -> {
Helpers.sleepMillis(200);
return Boolean.FALSE;
}));
Single<Integer> userCreditScoreStream = Single.fromFuture(CompletableFuture.supplyAsync(() -> {
Helpers.sleepMillis(2300);
return 200;
}));
Single<Pair<Boolean, Integer>> userCheckStream = Single.zip(isUserBlockedStream, userCreditScoreStream,
Pair::new);
subscribeWithLogOutputWaitingForComplete(userCheckStream);
}
/**
* Implementing a periodic emitter, by waiting for a slower stream to emit periodically.
* Since the zip operator need a pair of events, the slow stream will work like a timer by periodically emitting
* with zip setting the pace of emissions downstream.
*/
@Test
public void zipUsedToSlowDownAnotherStream() {
Flowable<String> colors = Flowable.just("red", "green", "blue");
Flowable<Long> timer = Flowable.interval(2, TimeUnit.SECONDS);
Flowable<String> periodicEmitter = Flowable.zip(colors, timer, (key, val) -> key);
subscribeWithLogOutputWaitingForComplete(periodicEmitter);
}
/**
* Merge operator combines one or more stream and passes events downstream as soon
* as they appear
* <p>
* The subscriber will receive both color strings and numbers from the Observable.interval
* as soon as they are emitted
*/
@Test
public void mergeOperator() {
log.info("Starting");
Flowable<String> colors = periodicEmitter("red", "green", "blue", 2, TimeUnit.SECONDS);
Flowable<Long> numbers = Flowable.interval(1, TimeUnit.SECONDS)
.take(5);
Flowable flowable = Flowable.merge(colors, numbers);
subscribeWithLogOutputWaitingForComplete(flowable);
}
/**
* Concat operator appends another streams at the end of another
* The ex. shows that even the 'numbers' streams should start early, the 'colors' stream emits fully its events
* before we see any 'numbers'.
* This is because 'numbers' stream is actually subscribed only after the 'colors' complete.
* Should the second stream be a 'hot' emitter, its events would be lost until the first one finishes
* and the seconds stream is subscribed.
*/
@Test
public void concatStreams() {
log.info("Starting");
Flowable<String> colors = periodicEmitter("red", "green", "blue", 2, TimeUnit.SECONDS);
Flowable<Long> numbers = Flowable.interval(1, TimeUnit.SECONDS)
.take(4);
Flowable observable = Flowable.concat(colors, numbers);
subscribeWithLogOutputWaitingForComplete(observable);
}
/**
* combineLatest pairs events from multiple streams, but instead of waiting for an event
* from other streams, it uses the last emitted event from that stream
*/
@Test
public void combineLatest() {
log.info("Starting");
Flowable<String> colors = periodicEmitter("red", "green", "blue", 3, TimeUnit.SECONDS);
Flowable<Long> numbers = Flowable.interval(1, TimeUnit.SECONDS)
.take(4);
Flowable combinedFlowables = Flowable.combineLatest(colors, numbers, Pair::new);
subscribeWithLogOutputWaitingForComplete(combinedFlowables);
}
}
================================================
FILE: src/test/java/com/balamaci/rx/Part04HotPublishers.java
================================================
package com.balamaci.rx;
import com.balamaci.rx.util.Helpers;
import io.reactivex.Observable;
import io.reactivex.observables.ConnectableObservable;
import io.reactivex.subjects.PublishSubject;
import io.reactivex.subjects.ReplaySubject;
import io.reactivex.subjects.Subject;
import org.junit.Test;
import java.util.concurrent.CountDownLatch;
import java.util.concurrent.Executors;
import java.util.concurrent.ScheduledExecutorService;
import java.util.concurrent.TimeUnit;
/**
* @author sbalamaci
*/
public class Part04HotPublishers implements BaseTestObservables {
/**
* We've seen that with 'cold publishers', whenever a subscriber subscribes, each subscriber will get
* it's version of emitted values independently
*
* Subjects keep reference to their subscribers and allow 'multicasting' to them.
*
* for (Disposable<T> s : subscribers.get()) {
* s.onNext(t);
* }
*
* Subjects besides being traditional Observables you can use the same operators and subscribe to them,
* are also an Observer, meaning you can invoke subject.onNext(value) from different parts in the code,
* which means that you publish events which the Subject will pass on to their subscribers.
*
* Observable.create(subscriber -> {
* subscriber.onNext(val);
* })
* .map(...)
* .subscribe(...);
*
* With Subjects you can call onNext from different parts of the code:
* Subject<Integer> subject = ReplaySubject.create()
* .map(...);
* .subscribe(); //
*
* ...
* subject.onNext(val);
* ...
* subject.onNext(val2);
*
* ReplaySubject keeps a buffer of events that it 'replays' to each new subscriber, first he receives a batch of missed
* and only later events in real-time.
*
* PublishSubject - doesn't keep a buffer but instead, meaning if another subscriber subscribes later, it's going to loose events
*/
@Test
public void replaySubject() {
Subject<Integer> subject = ReplaySubject.createWithSize(50);
// Runnable pushAction = pushEventsToSubjectAction(subject, 10);
// periodicEventEmitter(pushAction, 500, TimeUnit.MILLISECONDS);
pushToSubject(subject, 0);
pushToSubject(subject, 1);
CountDownLatch latch = new CountDownLatch(2);
log.info("Subscribing 1st");
subject.subscribe(val -> log.info("Subscriber1 received {}", val), logError(), logComplete(latch));
pushToSubject(subject, 2);
log.info("Subscribing 2nd");
subject.subscribe(val -> log.info("Subscriber2 received {}", val), logError(), logComplete(latch));
pushToSubject(subject, 3);
subject.onComplete();
Helpers.wait(latch);
}
private void pushToSubject(Subject<Integer> subject, int val) {
log.info("Pushing {}", val);
subject.onNext(val);
}
@Test
public void publishSubject() {
Subject<Integer> subject = PublishSubject.create();
Helpers.sleepMillis(1000);
log.info("Subscribing 1st");
CountDownLatch latch = new CountDownLatch(2);
subject
.subscribe(val -> log.info("Subscriber1 received {}", val), logError(), logComplete(latch));
Helpers.sleepMillis(1000);
log.info("Subscribing 2nd");
subject.subscribe(val -> log.info("Subscriber2 received {}", val), logError(), logComplete(latch));
Helpers.wait(latch);
}
/**
* Because reactive stream specs mandates that events should be ordered(cannot emit downstream two events simultaneously)
* it means that it's illegal to call onNext,onComplete,onError from different threads.
*
* To make this easy there is the .toSerialized() operator that wraps the Subject inside a SerializedSubject
* which basically just calls the onNext,.. methods of the wrapped Subject inside a synchronized block.
*/
@Test
public void callsToSubjectMethodsMustHappenOnSameThread() {
Subject<Integer> subject = PublishSubject.create();
CountDownLatch latch = new CountDownLatch(1);
Subject<Integer> serializedSubject = subject.toSerialized();
subject.subscribe(logNext(), logError(), logComplete(latch));
new Thread(() -> serializedSubject.onNext(1), "thread1").start();
new Thread(() -> serializedSubject.onNext(2), "thread2").start();
new Thread(() -> serializedSubject.onComplete(), "thread3").start();
Helpers.wait(latch);
}
/**
* ConnectableObservable is a special kind of Observable that when calling .subscribe()
* it just keeps a reference to its subscribers, it only subscribes once the .connect() method is called
*/
@Test
public void sharingResourcesBetweenSubscriptions() {
ConnectableObservable<Integer> connectableObservable = Observable.<Integer>create(subscriber -> {
log.info("Inside create()");
/* A JMS connection listener example
Just an example of a costly operation that is better to be shared **/
/* Connection connection = connectionFactory.createConnection();
Session session = connection.createSession(true, AUTO_ACKNOWLEDGE);
MessageConsumer consumer = session.createConsumer(orders);
consumer.setMessageListener(subscriber::onNext); */
subscriber.setCancellable(() -> log.info("Subscription cancelled"));
log.info("Emitting 1");
subscriber.onNext(1);
log.info("Emitting 2");
subscriber.onNext(2);
subscriber.onComplete();
}).publish(); //calling .publish makes an Observable a ConnectableObservable
log.info("Before subscribing");
CountDownLatch latch = new CountDownLatch(2);
/* calling .subscribe() bellow doesn't actually subscribe, but puts them in a list to actually subscribe
when calling .connect() */
connectableObservable
.take(1)
.subscribe((val) -> log.info("Subscriber1 received: {}", val), logError(), logComplete(latch));
connectableObservable
.subscribe((val) -> log.info("Subscriber2 received: {}", val), logError(), logComplete(latch));
//we need to call .connect() to trigger the real subscription
log.info("Now connecting to the ConnectableObservable");
connectableObservable.connect();
Helpers.wait(latch);
}
/**
* We can get away with having to call ourselves .connect(), by using
*/
@Test
public void autoConnectingWithFirstSubscriber() {
ConnectableObservable<Integer> connectableObservable = Observable.<Integer>create(subscriber -> {
log.info("Inside create()");
//simulating some listener that produces events after
//connection is initialized
ResourceConnectionHandler resourceConnectionHandler = new ResourceConnectionHandler() {
@Override
public void onMessage(Integer message) {
log.info("Emitting {}", message);
subscriber.onNext(message);
}
};
resourceConnectionHandler.openConnection();
subscriber.setCancellable(resourceConnectionHandler::disconnect);
}).publish();
Observable<Integer> observable = connectableObservable.autoConnect();
CountDownLatch latch = new CountDownLatch(2);
observable
.take(5)
.subscribe((val) -> log.info("Subscriber1 received: {}", val), logError(), logComplete(latch));
Helpers.sleepMillis(1000);
observable
.take(2)
.subscribe((val) -> log.info("Subscriber2 received: {}", val), logError(), logComplete(latch));
Helpers.wait(latch);
}
/**
* Even the above .autoConnect() can be improved
*/
@Test
public void refCountTheConnectableObservableAutomaticSubscriptionOperator() {
ConnectableObservable<Integer> connectableObservable = Observable.<Integer>create(subscriber -> {
log.info("Inside create()");
//simulating some listener that produces events after
//connection is initialized
ResourceConnectionHandler resourceConnectionHandler = new ResourceConnectionHandler() {
@Override
public void onMessage(Integer message) {
log.info("Emitting {}", message);
subscriber.onNext(message);
}
};
resourceConnectionHandler.openConnection();
subscriber.setCancellable(resourceConnectionHandler::disconnect);
}).publish();
Observable<Integer> observable = connectableObservable.refCount();
//publish().refCount() equals share()
CountDownLatch latch = new CountDownLatch(2);
observable
.take(5)
.subscribe((val) -> log.info("Subscriber1 received: {}", val), logError(), logComplete(latch));
Helpers.sleepMillis(1000);
log.info("Subscribing 2nd");
//we're not seeing the code inside .create() re-executed
observable
.take(2)
.subscribe((val) -> log.info("Subscriber2 received: {}", val), logError(), logComplete(latch));
Helpers.wait(latch);
//Previous Subscribers all unsubscribed, subscribing another will trigger the execution of the code
//inside .create()
latch = new CountDownLatch(1);
log.info("Subscribing 3rd");
observable
.take(1)
.subscribe((val) -> log.info("Subscriber3 received: {}", val), logError(), logComplete(latch));
Helpers.wait(latch);
}
private ScheduledExecutorService periodicEventEmitter(Runnable action,
int period, TimeUnit timeUnit) {
ScheduledExecutorService scheduledExecutorService = Executors.newScheduledThreadPool(1);
scheduledExecutorService.scheduleAtFixedRate(action, 0, period, timeUnit);
return scheduledExecutorService;
}
private abstract class ResourceConnectionHandler {
ScheduledExecutorService scheduledExecutorService;
private int counter;
public void openConnection() {
log.info("**Opening connection");
scheduledExecutorService = periodicEventEmitter(() -> {
counter ++;
onMessage(counter);
}, 500, TimeUnit.MILLISECONDS);
}
public abstract void onMessage(Integer message);
public void disconnect() {
log.info("**Shutting down connection");
scheduledExecutorService.shutdown();
}
}
/* private Runnable pushEventsToSubjectAction(Subject<Integer> subject, int maxEvents) {
return () -> {
if(counter == maxEvents) {
subject.onComplete();
return;
}
counter ++;
log.info("Emitted {}", counter);
subject.onNext(counter);
};
}*/
}
================================================
FILE: src/test/java/com/balamaci/rx/Part05AdvancedOperators.java
================================================
package com.balamaci.rx;
import com.balamaci.rx.util.Pair;
import io.reactivex.Flowable;
import io.reactivex.Observable;
import io.reactivex.flowables.GroupedFlowable;
import org.junit.Test;
import java.util.List;
import java.util.concurrent.TimeUnit;
/**
* @author sbalamaci
*/
public class Part05AdvancedOperators implements BaseTestObservables {
@Test
public void buffer() {
Flowable<Long> numbers = Flowable.interval(1, TimeUnit.SECONDS);
Flowable<List<Long>> delayedNumbersWindow = numbers
.buffer(5);
subscribeWithLog(delayedNumbersWindow);
}
@Test
public void simpleWindow() {
Flowable<Long> numbers = Flowable.interval(1, TimeUnit.SECONDS);
Flowable<Long> delayedNumbersWindow = numbers
.window(5)
.flatMap(window -> window.doOnComplete(() -> log.info("Window completed")));
subscribeWithLog(delayedNumbersWindow);
}
@Test
public void window() {
Flowable<Long> numbers = Flowable.interval(1, TimeUnit.SECONDS);
Flowable<Long> delayedNumbersWindow = numbers
.window(10, 5, TimeUnit.SECONDS)
.flatMap(window -> window.doOnComplete(() -> log.info("Window completed")));
subscribeWithLog(delayedNumbersWindow);
}
/**
* groupBy splits the stream into multiple streams with the key generated by the function passed as
* parameter to groupBy
*/
@Test
public void groupBy() {
Flowable<String> colors = Flowable.fromArray("red", "green", "blue",
"red", "yellow", "green", "green");
Flowable<GroupedFlowable<String, String>> groupedColorsStream = colors
.groupBy(val -> val); //identity function
// .groupBy(val -> "length" + val.length());
Flowable<Pair<String, Long>> colorCountStream = groupedColorsStream
.flatMap(groupedColor -> groupedColor
.count()
.map(count -> new Pair<>(groupedColor.getKey(), count))
.toFlowable()
);
subscribeWithLog(colorCountStream);
}
@Test
public void bufferWithLimitTriggeredByObservable() {
Observable<String> colors = Observable.fromArray("red", "green", "blue",
"red", "yellow", "#", "green", "green");
colors.publish(p -> p.filter(val -> ! val.equals("#"))
.buffer(() -> p.filter(val -> val.equals("#")))
)
.subscribe(list -> {
String listCommaSeparated = String.join(",", list);
log.info("List {}", listCommaSeparated);
});
}
}
================================================
FILE: src/test/java/com/balamaci/rx/Part06Schedulers.java
================================================
package com.balamaci.rx;
import com.balamaci.rx.util.Helpers;
import io.reactivex.Flowable;
import io.reactivex.Observable;
import io.reactivex.Single;
import io.reactivex.schedulers.Schedulers;
import org.junit.Test;
import java.util.concurrent.CountDownLatch;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
/**
* RxJava provides some high level concepts for concurrent execution, like ExecutorService we're not dealing
* with the low level constructs like creating the Threads ourselves. Instead we're using a {@see rx.Scheduler} which create
* Workers who are responsible for scheduling and running code. By default RxJava will not introduce concurrency
* and will run the operations on the subscription thread.
*
* There are two methods through which we can introduce Schedulers into our chain of operations:
* - <b>subscribeOn allows to specify which Scheduler invokes the code contained in the lambda code for Observable.create()
* - <b>observeOn</b> allows control to which Scheduler executes the code in the downstream operators
*
* RxJava provides some general use Schedulers already implemented:
* - Schedulers.computation() - to be used for CPU intensive tasks. A threadpool equal to the numbers of available CPUs
* - Schedulers.io() - to be used for IO bound tasks
* - Schedulers.from(Executor) - custom ExecutorService
* - Schedulers.newThread() - always creates a new thread when a worker is needed. Since it's not thread pooled
* and always creates a new thread instead of reusing one, this scheduler is not very useful
*
* Although we said by default RxJava doesn't introduce concurrency, some operators that involve waiting like 'delay',
* 'interval' need to run on a Scheduler, otherwise they would just block the subscribing thread.
* By default **Schedulers.computation()** is used, but the Scheduler can be passed as a parameter.
*
* @author sbalamaci
*/
public class Part06Schedulers implements BaseTestObservables {
@Test
public void byDefaultRxJavaDoesntIntroduceConcurrency() {
log.info("Starting");
Observable.<Integer>create(subscriber -> {
log.info("Someone subscribed");
subscriber.onNext(1);
subscriber.onNext(2);
subscriber.onComplete();
})
.map(val -> {
int newValue = val * 10;
log.info("Mapping {} to {}", val, newValue);
// Helpers.sleepMillis(2000);
return newValue;
})
.subscribe(logNext());
}
@Test
public void subscribingThread() {
CountDownLatch latch = new CountDownLatch(1);
Observable<Integer> observable = Observable.<Integer>create(subscriber -> {
log.info("Someone subscribed");
new Thread(() -> {
log.info("Emitting..");
subscriber.onNext(1);
subscriber.onComplete();
}, "custom-thread").start();
})
.map(val -> {
int newValue = val * 10;
log.info("Mapping {} to {}", val, newValue);
return newValue;
});
observable.subscribe(logNext(), logError(), logComplete(latch));
Helpers.wait(latch);
log.info("Blocking Subscribe");
observable.blockingSubscribe(logNext(), logError(), logComplete());
observable.observeOn(Schedulers.trampoline());
log.info("Got");
}
/**
* subscribeOn allows to specify which Scheduler invokes the code contained in the lambda code for Observable.create()
*/
@Test
public void testSubscribeOn() {
log.info("Starting");
Observable<Integer> observable = Observable.create(subscriber -> { //code that will execute inside the IO ThreadPool
log.info("Starting slow network op");
Helpers.sleepMillis(2000);
log.info("Emitting 1st");
subscriber.onNext(1);
subscriber.onComplete();
});
observable = observable
.subscribeOn(Schedulers.io()) //Specify execution on the IO Scheduler
.map(val -> {
int newValue = val * 10;
log.info("Mapping {} to {}", val, newValue);
return newValue;
});
subscribeWithLogOutputWaitingForComplete(observable);
}
/**
* observeOn switches the thread that is used for the subscribers downstream.
* If we initially subscribedOn the IoScheduler we and we
* further make another .
*/
@Test
public void testObserveOn() {
log.info("Starting");
Flowable<Integer> observable = simpleFlowable()
.subscribeOn(Schedulers.io())
.observeOn(Schedulers.computation())
.map(val -> {
int newValue = val * 10;
log.info("Mapping {} to {}", val, newValue);
return newValue;
})
.observeOn(Schedulers.newThread());
subscribeWithLogOutputWaitingForComplete(observable);
}
/**
* Multiple calls to subscribeOn have no effect, just the first one will take effect, so we'll see the code
* execute on an IoScheduler thread.
*/
@Test
public void multipleCallsToSubscribeOn() {
log.info("Starting");
Flowable<Integer> observable = simpleFlowable()
.subscribeOn(Schedulers.io())
.subscribeOn(Schedulers.computation())
.map(val -> {
int newValue = val * 2;
log.info("Mapping new val {}", newValue);
return newValue;
});
subscribeWithLogOutputWaitingForComplete(observable);
}
@Test
public void blocking() {
log.info("Starting");
Flowable<String> flowable = simpleFlowable()
.subscribeOn(Schedulers.io())
.subscribeOn(Schedulers.computation())
.map(val -> {
String newValue = "^^" + val + "^^";
log.info("Mapping new val {}", newValue);
Helpers.sleepMillis(500);
return newValue;
});
flowable.blockingSubscribe(val -> log.info("Subscriber received {}", val));
log.info("Finished blocking subscribe");
Iterable<String> iterable = flowable.blockingIterable();
iterable.forEach(val -> log.info("Received {}", val));
log.info("Finished blockingIterable");
}
/**
* Controlling concurrency in flatMap
*
* By using subscribeOn in flatMap you can control the thread on which flapMap subscribes to the particular
* stream. By using a scheduler from a custom executor to which we allow a limited number of threads,
* we can also control how many concurrent threads are handling stream operations inside the flatMap
*/
@Test
public void flatMapSubscribesToSubstream() {
ExecutorService fixedThreadPool = Executors.newFixedThreadPool(2);
Flowable<String> observable = Flowable.range(1, 5)
.observeOn(Schedulers.io()) //Scheduler for multiply
.map(val -> {
log.info("Multiplying {}", val);
return val * 10;
})
.flatMap(val -> simulateRemoteOp(val)
.subscribeOn(Schedulers.from(fixedThreadPool))
);
subscribeWithLogOutputWaitingForComplete(observable);
}
private Flowable<String> simulateRemoteOp(Integer val) {
return Single.<String>create(subscriber -> {
log.info("Simulate remote call {}", val);
Helpers.sleepMillis(3000);
subscriber.onSuccess("***" + val + "***");
}).toFlowable();
}
}
================================================
FILE: src/test/java/com/balamaci/rx/Part07FlatMapOperator.java
================================================
package com.balamaci.rx;
import com.balamaci.rx.util.Pair;
import io.reactivex.Flowable;
import io.reactivex.flowables.GroupedFlowable;
import io.reactivex.schedulers.Schedulers;
import org.junit.Test;
import java.util.Arrays;
import java.util.List;
import java.util.concurrent.TimeUnit;
/**
* The flatMap operator is so important and has so many different uses it deserves it's own category to explain
* I like to think of it as a sort of fork-join operation because what flatMap does is it takes individual items
* and maps each of them to an Observable(so it creates new Streams from each object) and then 'flattens' the
* events from these Streams back into a single Stream.
* Why this looks like fork-join because for each element you can fork some async jobs that emit some items before completing,
* and these items are sent downstream to the subscribers as coming from a single stream
*
* RuleOfThumb 1: When you have an 'item' as parameter and you need to invoke something that returns an
* Observable<T> instead of <T>, you need flatMap
* RuleOfThumb 2: When you have Observable<Observable<T>> you probably need flatMap.
*
* @author sbalamaci
*/
public class Part07FlatMapOperator implements BaseTestObservables {
/**
* Common usecase when for each item you make an async remote call that returns a stream of items (an Observable<T>)
*
* The thing to notice that it's not clear upfront that events from the flatMaps 'substreams' don't arrive
* in a guaranteed order and events from a substream might get interleaved with the events from other substreams.
*
*/
@Test
public void flatMap() {
Flowable<String> colors = Flowable.just("orange", "red", "green")
.flatMap(colorName -> simulateRemoteOperation(colorName));
subscribeWithLogOutputWaitingForComplete(colors);
}
/**
* Inside the flatMap we can operate on the substream with the same stream operators like for ex count
*/
@Test
public void flatMapSubstreamOperations() {
Flowable<String> colors = Flowable.just("orange", "red", "green", "blue");
Flowable<Pair<String, Long>> colorsCounted = colors
.flatMap(colorName -> {
Flowable<Long> timer = Flowable.interval(2, TimeUnit.SECONDS);
return simulateRemoteOperation(colorName) // <- Still a stream
.zipWith(timer, (val, timerVal) -> val)
.count()
.map(counter -> new Pair<>(colorName, counter))
.toFlowable();
}
);
subscribeWithLogOutputWaitingForComplete(colorsCounted);
}
/**
* Controlling the level of concurrency of the substreams.
* In the ex. below, only one of the substreams(the Observables returned by simulateRemoteOperation)
* is subscribed. As soon the substream completes, another substream is subscribed.
* Since only one substream is subscribed at any time, this way we don't see any values interleaved
*/
@Test
public void flatMapConcurrency() {
Flowable<String> colors = Flowable.just("orange", "red", "green")
.flatMap(colorName -> simulateRemoteOperation(colorName), 1);
subscribeWithLogOutputWaitingForComplete(colors);
}
/**
* As seen above flatMap might mean that events emitted by multiple streams might get interleaved
*
* concatMap operator acts as a flatMap with 1 level of concurrency which means only one of the created
* substreams(Observable) is subscribed and thus only one emits events so it's just this substream which
* emits events until it finishes and a new one will be subscribed and so on
*/
@Test
public void concatMap() {
Flowable<String> colors = Flowable.just("orange", "red", "green", "blue")
.subscribeOn(Schedulers.io())
.concatMap(val -> simulateRemoteOperation(val)
.subscribeOn(Schedulers.io())
);
subscribeWithLogOutputWaitingForComplete(colors);
}
/**
* When you have a Stream of Streams - Observable<Observable<T>>
*/
@Test
public void flatMapForProcessingAStreamOfStreams() {
Flowable<String> colors = Flowable.just("red", "green", "blue",
"red", "yellow", "green", "green");
Flowable<GroupedFlowable<String, String>> groupedColorsStream = colors
.groupBy(val -> val);//grouping key
// is the String itself, the color
Flowable<Pair<String, Long>>
countedColors = groupedColorsStream
.flatMap(groupedFlow -> groupedFlow
.count()
.map(countVal -> new Pair<>(groupedFlow.getKey(), countVal))
.toFlowable()
);
subscribeWithLogOutputWaitingForComplete(countedColors);
}
/**
* 'switchIfEmpty' push some value(s) when the original stream just completes without 'returning' anything
*/
@Test
public void flatMapSubstituteEmptyStream() {
Flowable<String> colors = Flowable.just("red", "", "blue")
.flatMap(colorName -> simulateRemoteOperation(colorName)
.switchIfEmpty(Flowable.just("NONE")));
subscribeWithLogOutputWaitingForComplete(colors);
}
/**
* flatMapIterable just takes as List and emits each of the elements
* as a stream.
*/
@Test
public void flatMapIterable() {
Flowable<String> colors = Flowable.just(1)
.flatMapIterable(it -> generateColors());
subscribeWithLogOutputWaitingForComplete(colors);
}
private List<String> generateColors() {
return Arrays.asList("red", "green", "blue");
}
@Test
public void switchMap() {
Flowable<String> colors = Flowable.interval(0,400, TimeUnit.MILLISECONDS)
.zipWith(Arrays.asList("EUR", "USD", "GBP"), (it, currency) -> currency)
.doOnNext(ev -> log.info("Emitting {}", ev))
.switchMap(currency -> simulateRemoteOperation(currency)
.doOnSubscribe((subscription) -> log.info("Subscribed new"))
.doOnCancel(() -> log.info("Unsubscribed {}", currency))
);
subscribeWithLogOutputWaitingForComplete(colors);
}
/**
* Simulated remote operation that emits as many events as the length of the color string
* @param color color
* @return stream of events
*/
private Flowable<String> simulateRemoteOperation(String color) {
return Flowable.intervalRange(1, color.length(), 0, 200, TimeUnit.MILLISECONDS)
.map(iteration -> color + iteration);
}
}
================================================
FILE: src/test/java/com/balamaci/rx/Part08ErrorHandling.java
================================================
package com.balamaci.rx;
import io.reactivex.BackpressureStrategy;
import io.reactivex.Flowable;
import org.junit.Test;
import java.util.Random;
import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.TimeUnit;
import java.util.concurrent.atomic.AtomicInteger;
/**
* Exceptions are for exceptional situations.
* The Observable contract specifies that exceptions are terminal operations.
* There are however operator available for error flow control
*/
public class Part08ErrorHandling implements BaseTestObservables {
private static final ConcurrentHashMap<String, AtomicInteger> attemptsMap = new ConcurrentHashMap<>();
/**
* After the map() operator encounters an error, it triggers the error handler
* in the subscriber which also unsubscribes from the stream,
* therefore 'yellow' is not even sent downstream.
*/
@Test
public void errorIsTerminalOperation() {
Flowable<String> colors = Flowable.just("green", "blue", "red", "yellow")
.map(color -> {
if ("red".equals(color)) {
throw new RuntimeException("Encountered red");
}
return color + "*";
})
.map(val -> val + "XXX");
subscribeWithLog(colors);
}
/**
* The 'onErrorReturn' operator doesn't prevent the unsubscription from the 'colors'
* but it does translate the exception for the downstream operators and the final Subscriber
* receives it in the 'onNext()' instead in 'onError()'
*/
@Test
public void onErrorReturn() {
Flowable<String> colors = Flowable.just("green", "blue", "red", "yellow")
.map(color -> {
if ("red".equals(color)) {
throw new RuntimeException("Encountered red");
}
return color + "*";
})
.onErrorReturn(th -> "-blank-")
.map(val -> val + "XXX");
subscribeWithLog(colors);
}
@Test
public void onErrorReturnWithFlatMap() {
//flatMap encounters an error when it subscribes to 'red' substreams and thus unsubscribe from
// 'colors' stream and the remaining colors still are not longer emitted
Flowable<String> colors = Flowable.just("green", "blue", "red", "white", "blue")
.flatMap(color -> simulateRemoteOperation(color))
.onErrorReturn(throwable -> "-blank-"); //onErrorReturn just has the effect of translating
subscribeWithLog(colors);
log.info("*****************");
//bellow onErrorReturn() is applied to the flatMap substream and thus translates the exception to
//a value and so flatMap continues on with the other colors after red
colors = Flowable.just("green", "blue", "red", "white", "blue")
.flatMap(color -> simulateRemoteOperation(color)
.onErrorReturn(throwable -> "-blank-") //onErrorReturn doesn't trigger
// the onError() inside flatMap so it doesn't unsubscribe from 'colors'
);
subscribeWithLog(colors);
}
/**
* onErrorResumeNext() returns a stream instead of an exception and subscribes to that stream instead,
* useful for example to invoke a fallback method that returns also a stream
*/
@Test
public void onErrorResumeNext() {
Flowable<String> colors = Flowable.just("green", "blue", "red", "white", "blue")
.flatMap(color -> simulateRemoteOperation(color)
.onErrorResumeNext(th -> {
if (th instanceof IllegalArgumentException) {
return Flowable.error(new RuntimeException("Fatal, wrong arguments"));
}
return fallbackRemoteOperation();
})
);
subscribeWithLog(colors);
}
private Flowable<String> fallbackRemoteOperation() {
return Flowable.just("blank");
}
/**
************* Retry Logic ****************
****************************************** */
/**
* timeout operator raises exception when there are no events incoming before it's predecessor in the specified
* time limit
* <p>
* retry() resubscribes in case of exception to the Observable
*/
@Test
public void timeoutWithRetry() {
Flowable<String> colors = Flowable.just("red", "blue", "green", "yellow")
.concatMap(color -> delayedByLengthEmitter(TimeUnit.SECONDS, color)
.timeout(6, TimeUnit.SECONDS)
.retry(2)
.onErrorResumeNext(Flowable.just("blank"))
);
subscribeWithLog(colors);
//there is also
}
/**
* When you want to retry based on the number considering the thrown exception type
*/
@Test
public void retryBasedOnAttemptsAndExceptionType() {
Flowable<String> colors = Flowable.just("blue", "red", "black", "yellow");
colors = colors
.flatMap(colorName -> simulateRemoteOperation(colorName, 2)
.retry((retryAttempt, exception) -> {
if (exception instanceof IllegalArgumentException) {
log.error("{} encountered non retry exception ", colorName);
return false;
}
log.info("Retry attempt {} for {}", retryAttempt, colorName);
return retryAttempt <= 3;
})
.onErrorResumeNext(Flowable.just("generic color"))
);
subscribeWithLog(colors);
}
/**
* A more complex retry logic like implementing a backoff strategy in case of exception
* This can be obtained with retryWhen(exceptionObservable -> Observable)
* <p>
* retryWhen resubscribes when an event from an Observable is emitted. It receives as parameter an exception stream
* <p>
* we zip the exceptionsStream with a .range() stream to obtain the number of retries,
* however we want to wait a little before retrying so in the zip function we return a delayed event - .timer()
* <p>
* The delay also needs to be subscribed to be effected so we also need flatMap
*/
@Test
public void retryWhenUsedForRetryWithBackoff() {
Flowable<String> colors = Flowable.just("blue", "green", "red", "black", "yellow");
colors = colors.flatMap(colorName ->
simulateRemoteOperation(colorName, 3)
.retryWhen(exceptionStream -> exceptionStream
.zipWith(Flowable.range(1, 3), (exc, attempts) -> {
//don't retry for IllegalArgumentException
if (exc instanceof IllegalArgumentException) {
return Flowable.error(exc);
}
if (attempts < 3) {
log.info("Attempt {}, waiting before retry", attempts);
return Flowable.timer(2 * attempts, TimeUnit.SECONDS);
}
return Flowable.error(exc);
})
.flatMap(val -> val)
)
.onErrorResumeNext(Flowable.just("generic color"))
);
subscribeWithLog(colors);
}
/**
* repeatWhen is identical to retryWhen only it responds to 'onCompleted' instead of 'onError'
*/
@Test
public void testRepeatWhen() {
Flowable<Integer> remoteOperation = Flowable.defer(() -> {
Random random = new Random();
return Flowable.just(random.nextInt(10));
});
remoteOperation = remoteOperation.repeatWhen(completed -> completed
.delay(2, TimeUnit.SECONDS)
)
.take(10);
subscribeWithLogOutputWaitingForComplete(remoteOperation);
}
private Flowable<String> simulateRemoteOperation(String color) {
return simulateRemoteOperation(color, Integer.MAX_VALUE);
}
private Flowable<String> simulateRemoteOperation(String color, int workAfterAttempts) {
return Flowable.create(subscriber -> {
AtomicInteger attemptsHolder = attemptsMap.computeIfAbsent(color, (colorKey) -> new AtomicInteger(0));
int attempts = attemptsHolder.incrementAndGet();
if ("red".equals(color)) {
checkAndThrowException(color, attempts, workAfterAttempts,
new RuntimeException("Color red raises exception"));
}
if ("black".equals(color)) {
checkAndThrowException(color, attempts, workAfterAttempts,
new IllegalArgumentException("Black is not a color"));
}
String value = "**" + color + "**";
log.info("Emitting {}", value);
subscriber.onNext(value);
subscriber.onComplete();
}, BackpressureStrategy.BUFFER);
}
private void checkAndThrowException(String color, int attempts, int workAfterAttempts, Exception exception) {
if(attempts < workAfterAttempts) {
log.info("Emitting {} for {}", exception.getClass(), color);
throw new IllegalArgumentException("Black is not a color");
} else {
log.info("After attempt {} we don't throw exception", attempts);
}
}
}
================================================
FILE: src/test/java/com/balamaci/rx/Part09BackpressureHandling.java
================================================
package com.balamaci.rx;
import com.balamaci.rx.util.Helpers;
import io.reactivex.BackpressureOverflowStrategy;
import io.reactivex.BackpressureStrategy;
import io.reactivex.Flowable;
import io.reactivex.schedulers.Schedulers;
import io.reactivex.subjects.PublishSubject;
import org.junit.Test;
import org.reactivestreams.Subscriber;
import org.reactivestreams.Subscription;
import java.util.concurrent.CountDownLatch;
import java.util.concurrent.TimeUnit;
/**
* Backpressure is related to preventing overloading the subscriber with too many events.
* It can be the case of a slow consumer that cannot keep up with the producer.
* Backpressure relates to a feedback mechanism through which the subscriber can signal
* to the producer how much data it can consume.
*
* However the producer must be 'backpressure-aware' in order to know how to throttle back.
*
* If the producer is not 'backpressure-aware', in order to prevent an OutOfMemory due to an unbounded increase of events,
* we still can define a BackpressureStrategy to specify how we should deal with piling events.
* If we should buffer(BackpressureStrategy.BUFFER) or drop(BackpressureStrategy.DROP, BackpressureStrategy.LATEST)
* incoming events.
*
* @author sbalamaci
*/
public class Part09BackpressureHandling implements BaseTestObservables {
@Test
public void customBackpressureAwareFlux() {
Flowable<Integer> flux = new CustomRangeFlowable(5, 10);
flux.subscribe(new Subscriber<Integer>() {
private Subscription subscription;
private int backlogItems;
private final int BATCH = 2;
private final int INITIAL_REQ = 5;
@Override
public void onSubscribe(Subscription subscription) {
this.subscription = subscription;
backlogItems = INITIAL_REQ;
log.info("Initial request {}", backlogItems);
subscription.request(backlogItems);
}
@Override
public void onNext(Integer val) {
log.info("Subscriber received {}", val);
backlogItems--;
if (backlogItems == 0) {
backlogItems = BATCH;
subscription.request(BATCH);
}
}
@Override
public void onError(Throwable throwable) {
log.info("Subscriber encountered error");
}
@Override
public void onComplete() {
log.info("Subscriber completed");
}
});
}
/**
* We use BackpressureStrategy.DROP in create() to handle events that are emitted outside
* the request amount from the downstream subscriber.
*
* We see that events that reach the subscriber are those only 3 requested by the
* observeOn operator, the events produced outside of the requested amount
* are discarded (BackpressureStrategy.DROP).
*
* observeOn has a default request size from upstream of 128(system parameter {@code rx2.buffer-size})
*
*/
@Test
public void createFlowableWithBackpressureStrategy() {
BackpressureStrategy backpressureStrategy =
BackpressureStrategy.DROP
// BackpressureStrategy.BUFFER
// BackpressureStrategy.LATEST
// BackpressureStrategy.ERROR
;
Flowable<Integer> flowable = createFlowable(5, backpressureStrategy);
//we need to switch threads to not run the producer in the same thread as the subscriber(which waits some time
// to simulate a slow subscriber)
flowable = flowable
.observeOn(Schedulers.io(), false, 3);
subscribeWithSlowSubscriberAndWait(flowable);
}
/**
* There are operators for specifying backpressure strategy anywhere in the operators chain,
* not just at Flowable.create().
* - onBackpressureBuffer
* - onBackpressureDrop
* - onBackpressureLatest
* These operators request from upstream the Long.MAX_VALUE(unbounded amount) and then they buffer(onBackpressureBuffer)
* the events for downstream and send the events as requested.
*
* In the example we specify a buffering strategy in the example, however since the buffer is not very large,
* we still get an exception after the 8th value - 3(requested) + 5(buffer)
*
* We create the Flowable with BackpressureStrategy.MISSING saying we don't care about backpressure
* but let one of the onBackpressureXXX operators handle it.
*
*/
@Test
public void bufferingBackpressureOperator() {
Flowable<Integer> flowable = createFlowable(10, BackpressureStrategy.MISSING)
.onBackpressureBuffer(5, () -> log.info("Buffer has overflown"));
flowable = flowable
.observeOn(Schedulers.io(), false, 3);
subscribeWithSlowSubscriberAndWait(flowable);
}
/**
* We can opt for a variant of the onBackpressureBuffer, to drop events that do not fit
* inside the buffer
*/
@Test
public void bufferingThenDroppingEvents() {
Flowable<Integer> flowable = createFlowable(10, BackpressureStrategy.MISSING)
.onBackpressureBuffer(5, () -> log.info("Buffer has overflown"),
BackpressureOverflowStrategy.DROP_OLDEST);
//we need to switch threads to not run the producer in the same thread as the subscriber(which waits some time
// to simulate a slow subscriber)
flowable = flowable
.observeOn(Schedulers.io(), false, 3);
subscribeWithSlowSubscriberAndWait(flowable);
}
/**
* Not only a slow subscriber triggers backpressure, but also a slow operator
* that slows down the handling of events and new request calls for new items
*/
@Test
public void throwingBackpressureNotSupportedSlowOperator() {
Flowable<String> flowable = createFlowable(10, BackpressureStrategy.MISSING)
.onBackpressureDrop((val) -> log.info("Dropping {}", val))
.observeOn(Schedulers.io(), false, 3)
.map(val -> {
Helpers.sleepMillis(50);
return "*" + val + "*";
});
subscribeWithLogOutputWaitingForComplete(flowable); //notice it's not the slowSubscribe method used
}
/**
* Backpressure operators can be added whenever necessary and it's not limited to
* cold publishers and we can use them on hot publishers also
*/
@Test
public void backpressureWithHotPublisher() {
CountDownLatch latch = new CountDownLatch(1);
PublishSubject<Integer> subject = PublishSubject.create();
Flowable<Integer> flowable = subject
.toFlowable(BackpressureStrategy.MISSING)
.onBackpressureDrop(val -> log.info("Dropped {}", val));
flowable = flowable.observeOn(Schedulers.io(), false, 3);
subscribeWithSlowSubscriber(flowable, latch);
for (int i = 1; i <= 10; i++) {
log.info("Emitting {}", i);
subject.onNext(i);
}
subject.onComplete();
Helpers.wait(latch);
}
/**
* Chaining together multiple onBackpressureXXX operators doesn't actually make sense
* Using
* .onBackpressureBuffer(5)
* .onBackpressureDrop((val) -> log.info("Dropping {}", val))
* is not behaving as maybe expected - buffer 5 values, and then dropping overflowing events-.
*
* Because onBackpressureDrop subscribes to the previous onBackpressureBuffer operator
* signaling its requesting Long.MAX_VALUE(unbounded amount) from it, the onBackpressureBuffer will never feel
* its subscriber is overwhelmed and never "trigger" meaning that the last onBackpressureXXX operator overrides
* the previous one.
*
* Of course for implementing an event dropping strategy after a full buffer, there is the special overrided
* version of onBackpressureBuffer that takes a BackpressureOverflowStrategy.
*/
@Test
public void cascadingOnBackpressureXXXOperators() {
Flowable<Integer> flowable = createFlowable(10, BackpressureStrategy.MISSING)
.onBackpressureBuffer(5)
.onBackpressureDrop((val) -> log.info("Dropping {}", val))
.observeOn(Schedulers.io(), false, 3);
subscribeWithSlowSubscriberAndWait(flowable);
}
/**
* Zipping a slow stream with a faster one also can cause a backpressure problem
*/
@Test
public void zipOperatorHasALimit() {
Flowable<Integer> fast = createFlowable(200, BackpressureStrategy.MISSING);
Flowable<Long> slowStream = Flowable.interval(100, TimeUnit.MILLISECONDS);
Flowable<String> observable = Flowable.zip(fast, slowStream,
(val1, val2) -> val1 + " " + val2);
subscribeWithSlowSubscriberAndWait(observable);
}
@Test
public void backpressureAwareObservable() {
Flowable<Integer> flowable = Flowable.range(0, 10);
flowable = flowable
.observeOn(Schedulers.io(), false, 3);
subscribeWithSlowSubscriberAndWait(flowable);
}
private Flowable<Integer> createFlowable(int items,
BackpressureStrategy backpressureStrategy) {
return Flowable.<Integer>create(subscriber -> {
log.info("Started emitting");
for (int i = 0; i < items; i++) {
if(subscriber.isCancelled()) {
return;
}
log.info("Emitting {}", i);
subscriber.onNext(i);
}
subscriber.onComplete();
}, backpressureStrategy);
}
private <T> void subscribeWithSlowSubscriberAndWait(Flowable<T> flowable) {
CountDownLatch latch = new CountDownLatch(1);
flowable.subscribe(logNextAndSlowByMillis(50), logError(latch), logComplete(latch));
Helpers.wait(latch);
}
private <T> void subscribeWithSlowSubscriber(Flowable<T> flowable, CountDownLatch latch) {
flowable.subscribe(logNextAndSlowByMillis(50), logError(latch), logComplete(latch));
}
private class CustomRangeFlowable extends Flowable<Integer> {
private int startFrom;
private int count;
CustomRangeFlowable(int startFrom, int count) {
this.startFrom = startFrom;
this.count = count;
}
@Override
public void subscribeActual(Subscriber<? super Integer> subscriber) {
subscriber.onSubscribe(new CustomRangeSubscription(startFrom, count, subscriber));
}
class CustomRangeSubscription implements Subscription {
volatile boolean cancelled;
boolean completed = false;
private int count;
private int currentCount;
private int startFrom;
private Subscriber<? super Integer> actualSubscriber;
CustomRangeSubscription(int startFrom, int count, Subscriber<? super Integer> actualSubscriber) {
this.count = count;
this.startFrom = startFrom;
this.actualSubscriber = actualSubscriber;
}
@Override
public void request(long items) {
log.info("Downstream requests {} items", items);
for(int i=0; i < items; i++) {
if(cancelled || completed) {
return;
}
if(currentCount == count) {
completed = true;
if(cancelled) {
return;
}
actualSubscriber.onComplete();
return;
}
int emitVal = startFrom + currentCount;
currentCount++;
actualSubscriber.onNext(emitVal);
}
}
@Override
public void cancel() {
cancelled = true;
}
}
}
}
================================================
FILE: src/test/java/com/balamaci/rx/util/Helpers.java
================================================
package com.balamaci.rx.util;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import java.util.concurrent.CountDownLatch;
/**
* @author sbalamaci
*/
public class Helpers {
private static final Logger log = LoggerFactory.getLogger(Helpers.class);
public static void sleepMillis(int millis) {
try {
Thread.sleep(millis);
} catch (InterruptedException e) {
log.error("Interrupted Thread");
throw new RuntimeException("Interrupted thread");
}
}
public static void wait(CountDownLatch waitOn) {
try {
waitOn.await();
} catch (InterruptedException e) {
log.error("Interrupted waiting on CountDownLatch");
throw new RuntimeException("Interrupted thread");
}
}
}
================================================
FILE: src/test/java/com/balamaci/rx/util/Pair.java
================================================
package com.balamaci.rx.util;
public class Pair<T, V> {
private T key;
private V value;
public Pair(T key, V value) {
this.key = key;
this.value = value;
}
public T getKey() {
return key;
}
public V getValue() {
return value;
}
@Override
public String toString() {
return "Pair{" +
"key=" + key +
", value=" + value +
'}';
}
}
================================================
FILE: src/test/resources/simplelogger.properties
================================================
# SLF4J's SimpleLogger configuration file
# Simple implementation of Logger that sends all enabled log messages, for all defined loggers, to System.err.
# Default logging detail level for all instances of SimpleLogger.
# Must be one of ("trace", "debug", "info", "warn", or "error").
# If not specified, defaults to "info".
org.slf4j.simpleLogger.defaultLogLevel=info
# Logging detail level for a SimpleLogger instance named "xxxxx".
# Must be one of ("trace", "debug", "info", "warn", or "error").
# If not specified, the default logging detail level is used.
#org.slf4j.simpleLogger.log.xxxxx=
org.slf4j.simpleLogger.log.ro.fortsoft.monitor=info
# Set to true if you want the current date and time to be included in output messages.
# Default is false, and will output the number of milliseconds elapsed since startup.
#org.slf4j.simpleLogger.showDateTime=false
org.slf4j.simpleLogger.showDateTime=true
# The date and time format to be used in the output messages.
# The pattern describing the date and time format is the same that is used in java.text.SimpleDateFormat.
# If the format is not specified or is invalid, the default format is used.
# The default format is yyyy-MM-dd HH:mm:ss:SSS Z.
#org.slf4j.simpleLogger.dateTimeFormat=yyyy-MM-dd HH:mm:ss:SSS Z
org.slf4j.simpleLogger.dateTimeFormat=HH:mm:ss
# Set to true if you want to output the current thread name.
# Defaults to true.
#org.slf4j.simpleLogger.showThreadName=true
# Set to true if you want the Logger instance name to be included in output messages.
# Defaults to true.
#org.slf4j.simpleLogger.showLogName=true
# Set to true if you want the last component of the name to be included in output messages.
# Defaults to false.
org.slf4j.simpleLogger.showShortLogName=true
gitextract_xvhlef2x/
├── .gitignore
├── README.md
├── _config.yml
├── pom.xml
└── src/
└── test/
├── java/
│ └── com/
│ └── balamaci/
│ └── rx/
│ ├── BaseTestObservables.java
│ ├── Part01CreateFlowable.java
│ ├── Part02SimpleOperators.java
│ ├── Part03MergingStreams.java
│ ├── Part04HotPublishers.java
│ ├── Part05AdvancedOperators.java
│ ├── Part06Schedulers.java
│ ├── Part07FlatMapOperator.java
│ ├── Part08ErrorHandling.java
│ ├── Part09BackpressureHandling.java
│ └── util/
│ ├── Helpers.java
│ └── Pair.java
└── resources/
└── simplelogger.properties
SYMBOL INDEX (127 symbols across 12 files)
FILE: src/test/java/com/balamaci/rx/BaseTestObservables.java
type BaseTestObservables (line 19) | public interface BaseTestObservables {
method simpleFlowable (line 23) | default Flowable<Integer> simpleFlowable() {
method subscribeWithLog (line 37) | default <T> void subscribeWithLog(Flowable<T> flowable) {
method subscribeWithLog (line 45) | default <T> void subscribeWithLog(Observable<T> observable) {
method subscribeWithLogOutputWaitingForComplete (line 53) | default <T> void subscribeWithLogOutputWaitingForComplete(Observable<T...
method subscribeWithLog (line 65) | default <T> void subscribeWithLog(Single<T> single) {
method subscribeWithLogOutputWaitingForComplete (line 72) | default <T> void subscribeWithLogOutputWaitingForComplete(Flowable<T> ...
method subscribeWithLogOutputWaitingForComplete (line 84) | default <T> void subscribeWithLogOutputWaitingForComplete(Single<T> si...
method periodicEmitter (line 98) | default <T> Flowable<T> periodicEmitter(T t1, T t2, T t3, int interva...
method periodicEmitter (line 102) | default <T> Flowable<T> periodicEmitter(T t1, T t2, T t3, int interval,
method periodicEmitter (line 110) | default <T> Observable<T> periodicEmitter(T[] items, int interval,
method periodicEmitter (line 118) | default <T> Observable<T> periodicEmitter(T[] items, int interval,
method delayedByLengthEmitter (line 123) | default Flowable<String> delayedByLengthEmitter(TimeUnit unit, String...
method logNext (line 132) | default <T> Consumer<? super T> logNext() {
method logNextAndSlowByMillis (line 136) | default <T> Consumer<? super T> logNextAndSlowByMillis(int millis) {
method logError (line 143) | default Consumer<? super Throwable> logError() {
method logError (line 147) | default Consumer<? super Throwable> logError(CountDownLatch latch) {
method logComplete (line 154) | default Action logComplete() {
method logComplete (line 158) | default Action logComplete(CountDownLatch latch) {
FILE: src/test/java/com/balamaci/rx/Part01CreateFlowable.java
class Part01CreateFlowable (line 19) | public class Part01CreateFlowable implements BaseTestObservables {
method just (line 22) | @Test
method range (line 30) | @Test
method fromArray (line 38) | @Test
method fromIterable (line 46) | @Test
method fromFuture (line 57) | @Test
method createSimpleObservable (line 80) | @Test
method createSimpleObservableThatEmitsError (line 107) | @Test
method flowablesAreLazy (line 133) | @Test
method multipleSubscriptionsToSameObservable (line 148) | @Test
method showUnsubscribeObservable (line 179) | @Test
method deferCreateObservable (line 216) | @Test
method blockingOperation (line 233) | private String blockingOperation() {
FILE: src/test/java/com/balamaci/rx/Part02SimpleOperators.java
class Part02SimpleOperators (line 17) | public class Part02SimpleOperators implements BaseTestObservables {
method delayOperator (line 29) | @Test
method timerOperator (line 51) | @Test
method delayOperatorWithVariableDelay (line 60) | @Test
method intervalOperator (line 72) | @Test
method scanOperator (line 86) | @Test
method reduceOperator (line 101) | @Test
method collectOperator (line 117) | @Test
method repeat (line 131) | @Test
FILE: src/test/java/com/balamaci/rx/Part03MergingStreams.java
class Part03MergingStreams (line 17) | public class Part03MergingStreams implements BaseTestObservables {
method zipUsedForTakingTheResultOfCombinedAsyncOperations (line 30) | @Test
method zipUsedToSlowDownAnotherStream (line 51) | @Test
method mergeOperator (line 69) | @Test
method concatStreams (line 90) | @Test
method combineLatest (line 106) | @Test
FILE: src/test/java/com/balamaci/rx/Part04HotPublishers.java
class Part04HotPublishers (line 19) | public class Part04HotPublishers implements BaseTestObservables {
method replaySubject (line 58) | @Test
method pushToSubject (line 83) | private void pushToSubject(Subject<Integer> subject, int val) {
method publishSubject (line 88) | @Test
method callsToSubjectMethodsMustHappenOnSameThread (line 113) | @Test
method sharingResourcesBetweenSubscriptions (line 134) | @Test
method autoConnectingWithFirstSubscriber (line 181) | @Test
method refCountTheConnectableObservableAutomaticSubscriptionOperator (line 219) | @Test
method periodicEventEmitter (line 269) | private ScheduledExecutorService periodicEventEmitter(Runnable action,
class ResourceConnectionHandler (line 278) | private abstract class ResourceConnectionHandler {
method openConnection (line 284) | public void openConnection() {
method onMessage (line 293) | public abstract void onMessage(Integer message);
method disconnect (line 295) | public void disconnect() {
FILE: src/test/java/com/balamaci/rx/Part05AdvancedOperators.java
class Part05AdvancedOperators (line 15) | public class Part05AdvancedOperators implements BaseTestObservables {
method buffer (line 17) | @Test
method simpleWindow (line 27) | @Test
method window (line 39) | @Test
method groupBy (line 54) | @Test
method bufferWithLimitTriggeredByObservable (line 73) | @Test
FILE: src/test/java/com/balamaci/rx/Part06Schedulers.java
class Part06Schedulers (line 37) | public class Part06Schedulers implements BaseTestObservables {
method byDefaultRxJavaDoesntIntroduceConcurrency (line 39) | @Test
method subscribingThread (line 59) | @Test
method testSubscribeOn (line 90) | @Test
method testObserveOn (line 121) | @Test
method multipleCallsToSubscribeOn (line 142) | @Test
method blocking (line 158) | @Test
method flatMapSubscribesToSubstream (line 186) | @Test
method simulateRemoteOp (line 203) | private Flowable<String> simulateRemoteOp(Integer val) {
FILE: src/test/java/com/balamaci/rx/Part07FlatMapOperator.java
class Part07FlatMapOperator (line 27) | public class Part07FlatMapOperator implements BaseTestObservables {
method flatMap (line 36) | @Test
method flatMapSubstreamOperations (line 47) | @Test
method flatMapConcurrency (line 73) | @Test
method concatMap (line 88) | @Test
method flatMapForProcessingAStreamOfStreams (line 102) | @Test
method flatMapSubstituteEmptyStream (line 125) | @Test
method flatMapIterable (line 138) | @Test
method generateColors (line 146) | private List<String> generateColors() {
method switchMap (line 150) | @Test
method simulateRemoteOperation (line 169) | private Flowable<String> simulateRemoteOperation(String color) {
FILE: src/test/java/com/balamaci/rx/Part08ErrorHandling.java
class Part08ErrorHandling (line 17) | public class Part08ErrorHandling implements BaseTestObservables {
method errorIsTerminalOperation (line 26) | @Test
method onErrorReturn (line 46) | @Test
method onErrorReturnWithFlatMap (line 62) | @Test
method onErrorResumeNext (line 90) | @Test
method fallbackRemoteOperation (line 105) | private Flowable<String> fallbackRemoteOperation() {
method timeoutWithRetry (line 120) | @Test
method retryBasedOnAttemptsAndExceptionType (line 136) | @Test
method retryWhenUsedForRetryWithBackoff (line 167) | @Test
method testRepeatWhen (line 197) | @Test
method simulateRemoteOperation (line 211) | private Flowable<String> simulateRemoteOperation(String color) {
method simulateRemoteOperation (line 215) | private Flowable<String> simulateRemoteOperation(String color, int wor...
method checkAndThrowException (line 237) | private void checkAndThrowException(String color, int attempts, int wo...
FILE: src/test/java/com/balamaci/rx/Part09BackpressureHandling.java
class Part09BackpressureHandling (line 31) | public class Part09BackpressureHandling implements BaseTestObservables {
method customBackpressureAwareFlux (line 35) | @Test
method createFlowableWithBackpressureStrategy (line 90) | @Test
method bufferingBackpressureOperator (line 126) | @Test
method bufferingThenDroppingEvents (line 141) | @Test
method throwingBackpressureNotSupportedSlowOperator (line 160) | @Test
method backpressureWithHotPublisher (line 177) | @Test
method cascadingOnBackpressureXXXOperators (line 215) | @Test
method zipOperatorHasALimit (line 229) | @Test
method backpressureAwareObservable (line 240) | @Test
method createFlowable (line 251) | private Flowable<Integer> createFlowable(int items,
method subscribeWithSlowSubscriberAndWait (line 270) | private <T> void subscribeWithSlowSubscriberAndWait(Flowable<T> flowab...
method subscribeWithSlowSubscriber (line 277) | private <T> void subscribeWithSlowSubscriber(Flowable<T> flowable, Cou...
class CustomRangeFlowable (line 281) | private class CustomRangeFlowable extends Flowable<Integer> {
method CustomRangeFlowable (line 286) | CustomRangeFlowable(int startFrom, int count) {
method subscribeActual (line 291) | @Override
class CustomRangeSubscription (line 296) | class CustomRangeSubscription implements Subscription {
method CustomRangeSubscription (line 306) | CustomRangeSubscription(int startFrom, int count, Subscriber<? sup...
method request (line 312) | @Override
method cancel (line 336) | @Override
FILE: src/test/java/com/balamaci/rx/util/Helpers.java
class Helpers (line 11) | public class Helpers {
method sleepMillis (line 15) | public static void sleepMillis(int millis) {
method wait (line 24) | public static void wait(CountDownLatch waitOn) {
FILE: src/test/java/com/balamaci/rx/util/Pair.java
class Pair (line 3) | public class Pair<T, V> {
method Pair (line 8) | public Pair(T key, V value) {
method getKey (line 13) | public T getKey() {
method getValue (line 17) | public V getValue() {
method toString (line 21) | @Override
Condensed preview — 17 files, each showing path, character count, and a content snippet. Download the .json file or copy for the full structured content (163K chars).
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{
"path": ".gitignore",
"chars": 232,
"preview": "# Created by .ignore support plugin (hsz.mobi)\n### Java template\n*.class\n\n# Package Files #\n*.jar\n*.war\n*.ear\n\n# virtual"
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{
"path": "README.md",
"chars": 75628,
"preview": "# RxJava 2.x\n\nView at [Github page](https://balamaci.github.io/rxjava-walkthrough/)\n\nalso available for [reactor-core](h"
},
{
"path": "_config.yml",
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"preview": "theme: jekyll-theme-cayman"
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"preview": "package com.balamaci.rx;\n\nimport com.balamaci.rx.util.Helpers;\nimport io.reactivex.BackpressureStrategy;\nimport io.react"
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About this extraction
This page contains the full source code of the balamaci/rxjava-walkthrough GitHub repository, extracted and formatted as plain text for AI agents and large language models (LLMs). The extraction includes 17 files (152.9 KB), approximately 34.5k tokens, and a symbol index with 127 extracted functions, classes, methods, constants, and types. Use this with OpenClaw, Claude, ChatGPT, Cursor, Windsurf, or any other AI tool that accepts text input. You can copy the full output to your clipboard or download it as a .txt file.
Extracted by GitExtract — free GitHub repo to text converter for AI. Built by Nikandr Surkov.