I have the following code:
interface Device {
// ...
boolean isDisconnected();
void reconnect();
}
interface Gateway {
// ...
List<Device> getDevices();
}
...
for (Gateway gateway : gateways) {
for(Device device : gateway.getDevices()){
if(device.isDisconnected()){
device.reconnect();
}
}
}
I want to refactor the code using Stream API. My first attempt was like the following:
gateways
.stream()
.forEach(
gateway -> {
gateway
.getDevices()
.parallelStream()
.filter(device -> device.isDisconnected())
.forEach(device -> device.reconnect())
;
}
)
;
I didn't like it so after some modifications I ended up with this code:
gateways
.parallelStream()
.map(gateway -> gateway.getDevices().parallelStream())
.map(stream -> stream.filter(device -> device.isDisconnected()))
.forEach(stream -> stream.forEach(device -> device.reconnect()))
;
My question is whether there is a way to avoid nested forEach.
You should flatten the stream of streams using flatMap instead of map:
gateways
.parallelStream()
.flatMap(gateway -> gateway.getDevices().parallelStream())
.filter(device -> device.isDisconnected())
.forEach(device -> device.reconnect());
I would improve it further by using method references instead of lambda expressions:
gateways
.parallelStream()
.map(Gateway::getDevices)
.flatMap(List::stream)
.filter(Device::isDisconnected)
.forEach(Device::reconnect);
Don't refactor your code into using Streams. You gain no benefits and gain no advantages over doing it like this, since the code is now less readable and less idiomatic for future maintainers.
By not using streams, you avoid nested forEach statements.
Remember: streams are meant to be side-effect free for safer parallelization. forEach by definition introduces side-effects. You lose the benefit of streams and lose readability at the same time, making this less desirable to do at all.
I would try this with a sequential stream before using a parallel one:
gateways
.stream()
.flatMap(gateway -> gateway.getDevices().stream())
.filter(device -> device.isDisconnected())
.forEach(device -> device.reconnect())
;
The idea is to create a stream via gateways.stream() then flatten the sequences returned from gateway.getDevices() via flatMap.
Then we apply a filter operation which acts like the if statement in your code and finally, a forEach terminal operation enabling us to invoke reconnect on each and every device passing the filter operation.
see Should I always use a parallel stream when possible?
Related
Say I want to call a webservice1 and then call webservice2 if the first was successful.
I can do the following (just indicative psuedo code) :-
Mono.just(reqObj)
.flatMap(r -> callServiceA())
.then(() -> callServiceB())
or
Mono.just(reqObj)
.flatMap(r -> callServiceA())
.flatMap(f -> callServiceB())
What is the difference between the two, when using the mono.just() for a single element?
flatMap should be used for non-blocking operations, or in short anything which returns back Mono, Flux.
map should be used when you want to do the transformation of an object /data in fixed time. The operations which are done synchronously.
For ex:
return Mono.just(Person("name", "age:12"))
.map { person ->
EnhancedPerson(person, "id-set", "savedInDb")
}.flatMap { person ->
reactiveMongoDb.save(person)
}
then should be used when you want to ignore element from previous Mono and want the stream to be finised
Here's a detailed explanation from #MuratOzkan
Copy pasting the TL DR answer:
If you care about the result of the previous computation, you can use map(), flatMap() or other map variant. Otherwise, if you just want the previous stream finished, use then().
In your example, looks like your service calls do not require the input of the upstream, then you could use this instead:
Mono.just(reqObj)
.then(() -> callServiceA())
.then(() -> callServiceB())
Sorry for some kind of theoretical question, but I'd like to find a way of quick reading someone else's functional code, building chain of methods use templates.
For example:
Case 1.
When I see use of .peek method or .wireTap from Spring Integration, I primarily expect logging, triggering monitoring or just transitional running external action, for instance:
.peek(params ->
log.info("creating cache configuration {} for key class \"{}\" and value class \"{}\"",
params.getName(), params.getKeyClass(), params.getValueClass()))
or
.peek(p ->
Try.run(() -> cacheService.cacheProfile(p))
.onFailure(ex ->
log.warn("Unable to cache profile: {}", ex.toString())))
or
.wireTap(sf -> sf.handle(msg -> {
monitoring.profileRequestsReceived();
log.trace("Client info request(s) received: {}", msg);
Case 2.
When I see use of .map method or .transform from Spring Integration, I understand that I'm up to get result of someFunction(input), for instance:
.map(e -> GenerateTokenRs.builder().token(e.getKey()).phoneNum(e.getValue()).build())
or
.transform(Message.class, msg -> {
ErrorResponse response = (ErrorResponse) msg.getPayload();
MessageBuilder builder = some tranforming;
return builder.build();
})
Current case.
But I don't have such a common view to .flatMap method.
Would you give me your opinion about this, please?
Add 1:
To Turamarth: I know the difference between .map and .flatMap methods. I actively use both .map, and .flatMap in my code.
But I ask community for theirs experience and coding templates.
It always helps to study the signature/javadoc of the streamish methods to understand them:
The flatMap() operation has the effect of applying a one-to-many transformation to the elements of the stream, and then flattening the resulting elements into a new stream.
So, typical code I expect, or wrote myself:
return someMap.values().stream().flatMap(Collection::stream)
The values of that map are sets, and I want to pull the entries of all these sets into a single stream for further processing here.
In other words: it is about "pulling out things", and getting them into a stream/collection for further processing.
I've found one more use template for .flatMap.
Let's have a look at the following code:
String s = valuesFromDb
.map(v -> v.get(k))
.getOrElse("0");
where Option<Map<String, String>> valuesFromDb = Option.of(.....).
If there's an entry k=null in the map, then we'll get null as a result of code above.
But we'd like to have "0" in this case as well.
So let's add .flatMap:
String s = valuesFromDb
.map(v -> v.get(k))
.flatMap(Option::of)
.getOrElse("0");
Regardless of having null as map's value we will get "0".
I have a method returning a collection of products:
Collection<Product> getProducts() { ... }
Each product may have a guarantee. But it is not required.
interface Product {
Optional<Guarantee> getGuarantee();
}
Now I need to go through all the products and check if the quarantees have expired. The non-expired ones should be collected into a list.
This is what I do:
List<Optional<Guarantee>> optionalGar = getProducts().stream()
.map(f -> f.getGuarantee()).collect(Collectors.toList());
List<Guarantee> gar = optionalGar.stream()
.map(op -> op.orElse(null))
.filter(Objects::nonNull)
.filter(g -> !g.hasExpired())
.collect(Collectors.toList());
Is there any way to avoid using .orElse(null)?
(Replacing it by op.get() would cause an exception in case the optional is empty)
P.S: I'm free to chose between Java 8 and Java 9 so both solutions (not sure if the'll be different) are welcome
Java 8
List<Guarantee> expiredGuarantees = getProducts().stream()
.map(Product::getGuarantee)
.filter(Optional::isPresent)
.map(Optional::get)
.filter(not(Guarantee::hasExpired))
.collect(toList());
Java 9
Java9 has got Optional::stream. So you can replace filtering and mapping with single flatMap:
List<Guarantee> expiredGuarantees = getProducts().stream()
.map(Product::getGuarantee)
.flatMap(Optional::stream)
.filter(not(Guarantee::hasExpired))
.collect(toList());
Note
Java 8 does not have Predicates.not method. It's included since 11th version only.
By adding the following method to your project you'll be able to use it with the solutions above.
public static <T> Predicate<T> not(Predicate<T> predicate) {
return predicate.negate();
}
Update
Although this is not the CodeReview community, here are some notes on your code:
By combining the two pipelines into a single your code will be cleaner (in this particular case).
Prefer a method reference over a lambda when possible
Give appropriate names to your variables so you'll make your code easier to maintain
I am trying to convert Flowable<List<TaskEntity>> to Flowable<List<Task>> but something is wrong.
To understand the problem I tried with converting a simpler list and it is working fine. When I try to apply the same logic to my actual problem, it is not working.
This logic is giving me expected output. [No.1 No.2 No.3]
Flowable.fromArray(Arrays.asList(1,2,3))
.flatMapIterable(ids->ids)
.map(s->"No. "+s)
.toList()
.toFlowable()
.subscribe(
t -> Log.d(TAG, "getAllActiveTasks: "+t)
);
This logic is not working . It prints Nothing
mTaskDao.getAllTasks(STATE_ACTIVE)
.flatMapIterable(task -> task)
.map(Task::create)
.toList()
.toFlowable()
.subscribe(
t -> Log.d(TAG, "getAllActiveTasks: "+t)
);
Edit 1
This is how Task.create() looks like.
public static Task create(TaskEntity eTask) {
Task task = new Task(eTask.getTaskId(), eTask.getTaskTitle(), eTask.getTaskStatus());
task.mTaskDescription = eTask.getTaskDescription();
task.mCreatedAt = eTask.getCreatedAt();
task.mTaskDeadline = eTask.getTaskDeadline();
return task;
}
Solution
As mentioned in the comments, toList() can only work if emitting source has finite number of items to emit. Since Flowable from Dao method contains an infinite stream of objects, toList() was not being used correctly by me.
Checkout this comment for the exact way to solve this problem.
https://stackoverflow.com/a/50318832/4989435
toList requires a finite source but getAllTasks is likely infinite, which is unfortunately quite typical from DAOs backed by Android databases. Change the getAllTasks to Single, use take(1), use timeout(), or use flatMap(Observable.fromIterable().map().toList()) instead of flatMapIterable.
I want to receive any updates made to tasks in db.
In this case, you need the latter option:
mTaskDao.getAllTasks(STATE_ACTIVE)
.flatMapSingle(task ->
Observable.fromIterable(task)
.map(Task::create)
.toList()
)
.subscribe(
t -> Log.d(TAG, "getAllActiveTasks: "+t)
);
You should use only map operator to convert TaskEntity to Task. I have created sample. You can check my solution which uses only map operator
In Java8 I have a stream and I want to apply a stream of mappers.
For example:
Stream<String> strings = Stream.of("hello", "world");
Stream<Function<String, String>> mappers = Stream.of(t -> t+"?", t -> t+"!", t -> t+"?");
I want to write:
strings.map(mappers); // not working
But my current best way of solving my task is:
for (Function<String, String> mapper : mappers.collect(Collectors.toList()))
strings = strings.map(mapper);
strings.forEach(System.out::println);
How can I solve this problem
without collecting the mappers into a list
without using a for loop
without breaking my fluent code
Since map requires a function that can be applied to each element, but your Stream<Function<…>> can only be evaluated a single time, it is unavoidable to process the stream to something reusable. If it shouldn’t be a Collection, just reduce it to a single Function:
strings.map(mappers.reduce(Function::andThen).orElse(Function.identity()))
Complete example:
Stream<Function<String, String>> mappers = Stream.of(t -> t+"?", t -> t+"!", t -> t+"?");
Stream.of("hello", "world")
.map(mappers.reduce(Function::andThen).orElse(Function.identity()))
.forEach(System.out::println);