I am new to reactor programming,and need some help on MONO/Flux
I have POJO class
Employee.java
class Employee {
String name
}
I have Mono being returned on hitting a service, I need to extract the name from Mono as a string.
Mono<Employee> m = m.map(value -> value.getName())
but this returns again a Mono but not a string. I need to extract String value from this Mono.
You should do something like this:
m.block().getName();
This solution doesn't take care of null check.
A standard approach would be:
Employee e = m.block();
if (null != e) {
e.getName();
}
But using flux you should proceed using something like this:
Mono.just(new Employee().setName("Kill"))
.switchIfEmpty(Mono.defer(() -> Mono.just(new Employee("Bill"))))
.block()
.getName();
Keep in mind that requesting for blocking operation should be avoided if possible: it blocks the flow
You should be avoiding block() because it will block indefinitely until a next signal is received.
You should not think of the reactive container as something that is going to provide your program with an answer. Instead, you need to give it whatever you want to do with that answer. For example:
employeeMono.subscribe(value -> whatYouWantToDoWithName(value.getName()));
Related
I know there is a function named "hasElements" on a Flux object. But it behaves a bit strangeļ¼
Flux<RoomBO> rooms=serverRequest.bodyToMono(PageBO.class).flatMapMany(roomRepository::getRooms);
return rooms.hasElements().flatMap(aBool -> aBool?ServerResponse.ok().body(rooms,RoomBO.class):ServerResponse.badRequest().build());
return ServerResponse.ok().body(rooms,RoomBO.class)
The second return statement can return the right things I need when the flux object is not empty,but the first return statement only returns a empty array,which likes "[]" in json.I don't know why this could happen!I use the same data to test.The only difference is that I call the hasElements function in the first situation.But I need to return badRequest when the flux object is empty. And the hasElements function seems to make my flux object empty,though I know it doesn't do this actually.
well, finally I decide to call switchIfEmpty(Mono.error()) to throw an error and then I deal with the special error globally(Sometimes it's not suitable to use onErrorReturn or onErrorResume). I think this can avoid the collect operation in memory when meets big data. But it's still not a good solution for the global error handler can be hard to maintain. I'd expect someone to give a better solution.
In your example you are transforming class Flux to class RoomBO, it is one of the reasons, why you get an empty array.
If you need to return the processed list of rooms, then, I think, collectList should be your choice. https://projectreactor.io/docs/core/release/api/reactor/core/publisher/Flux.html#collectList--
Flux<RoomBO> roomsFlux = serverRequest.bodyToMono(PageBO.class)
.flatMapMany(roomRepository::getRooms);
return rooms
.collectList()
.flatMap(rooms -> !rooms.isEmpty() ? ServerResponse.ok().bodyValue(rooms) : ServerResponse.badRequest().build());
I have the method below, where I am calling several ReactiveMongoRepositories in order to receive and process certain documents. Since I am kind of new to Webflux, I am learning as I go.
To my feeling the code below doesn't feel very efficient, as I am opening multiple streams at the same time. This non-blocking way of writing code makes it complicated somehow to get a value from a stream and re-use that value in the cascaded flatmaps down the line.
In the example below I have to call the userRepository twice, since I want the user at the beginning and than later as well. Is there a possibility to do this more efficiently with Webflux?
public Mono<Guideline> addGuideline(Guideline guideline, String keycloakUserId) {
Mono<Guideline> guidelineMono = userRepository.findByKeycloakUserId(keycloakUserId)
.flatMap(user -> {
return teamRepository.findUserInTeams(user.get_id());
}).zipWith(instructionRepository.findById(guideline.getInstructionId()))
.zipWith(userRepository.findByKeycloakUserId(keycloakUserId))
.flatMap(objects -> {
User user = objects.getT2();
Instruction instruction = objects.getT1().getT2();
Team team = objects.getT1().getT1();
if (instruction.getTeamId().equals(team.get_id())) {
guideline.setAddedByUser(user.get_id());
guideline.setTeamId(team.get_id());
guideline.setDateAdded(new Date());
guideline.setGuidelineStatus(GuidelineStatus.ACTIVE);
guideline.setGuidelineSteps(Arrays.asList());
return guidelineRepository.save(guideline);
} else {
return Mono.error(new InstructionDoesntBelongOrExistException("Unable to add, since this Instruction does not belong to you or doesn't exist anymore!"));
}
});
return guidelineMono;
}
i'll post my earlier comment as an answer. If anyone feels like writing the correct code for it then go ahead.
i don't have access to an IDE current so cant write an example but you could start by fetching the instruction from the database.
Keep that Mono<Instruction> then you fetch your User and flatMap the User and fetch the Team from the database. Then you flatMap the team and build a Mono<Tuple> consisting of Mono<Tuple<User, Team>>.
After that you take your 2 Monos and use zipWith with a Combinator function and build a Mono<Tuple<User, Team, Instruction>> that you can flatMap over.
So basically fetch 1 item, then fetch 2 items, then Combinate into 3 items. You can create Tuples using the Tuples.of(...) function.
Following issue: In a client/server environment with Spring-Boot and Kotlin the client wants to create objects of type A and therefore posts the data through a RESTful endpoint to the server.
Entity A is realized as a data class in Kotlin like this:
data class A(val mandatoryProperty: String)
Business-wise that property (which is a primary key, too) must never be null. However, it is not known by the client, as it gets generated quite expensively by a Spring #Service Bean on the server.
Now, at the endpoint Spring tries to deserialize the client's payload into an object of type A, however, the mandatoryProperty is unknown at that point in time, which would result in a mapping exception.
Several ways to circumvent that problem, none of which really amazes me.
Don't expect an object of type A at the endpoint, but get a bunch of parameters describing A that are passed on until the entity has actually been created and mandatoryProperty is present . Quite cumbersome actually, since there are a lot more properties than just that single one.
Quite similar to 1, but create a DTO. One of my favorites, however, since data classes can't be extended it would mean to duplicate the properties of type A into the DTO (except for the mandatory property) and copy them over. Furthemore, when A grows, the DTO has to grow, too.
Make mandatoryProperty nullable and work with !! operator throughout the code. Probably the worst solution as it foils the sense of nullable and non-nullable variables.
The client would set a dummy value for the mandatoryProperty which is replaced as soon as the property has been generated. However, A is validated by the endpoint and therefore the dummy value must obey its #Pattern constraint. So each dummy value would be a valid primary key, which gives me a bad feeling.
Any other ways I might have overseen that are more feasible?
I don't think there is a general-purpose answer to this... So I will just give you my 2 cents regarding your variants...
Your first variant has a benefit which no other really has, i.e. that you will not use the given objects for anything else then they were designed to be (i.e. endpoint or backend purposes only), which however probably will lead to cumbersome development.
The second variant is nice, but could lead to some other development errors, e.g. when you thought you used the actual A but you were rather operating on the DTO instead.
Variant 3 and 4 are in that regard similar to 2... You may use it as A even though it has all the properties of a DTO only.
So... if you want to go the safe route, i.e. no one should ever use this object for anything else then its specific purpose you should probably use the first variant. 4 sounds rather like a hack. 2 & 3 are probably ok. 3 because you actually have no mandatoryProperty when you use it as DTO...
Still, as you have your favorite (2) and I have one too, I will concentrate on 2 & 3, starting with 2 using a subclass approach with a sealed class as supertype:
sealed class AbstractA {
// just some properties for demo purposes
lateinit var sharedResettable: String
abstract val sharedReadonly: String
}
data class A(
val mandatoryProperty: Long = 0,
override val sharedReadonly: String
// we deliberately do not override the sharedResettable here... also for demo purposes only
) : AbstractA()
data class ADTO(
// this has no mandatoryProperty
override val sharedReadonly: String
) : AbstractA()
Some demo code, demonstrating the usage:
// just some random setup:
val a = A(123, "from backend").apply { sharedResettable = "i am from backend" }
val dto = ADTO("from dto").apply { sharedResettable = "i am dto" }
listOf(a, dto).forEach { anA ->
// somewhere receiving an A... we do not know what it is exactly... it's just an AbstractA
val param: AbstractA = anA
println("Starting with: $param sharedResettable=${param.sharedResettable}")
// set something on it... we do not mind yet, what it is exactly...
param.sharedResettable = UUID.randomUUID().toString()
// now we want to store it... but wait... did we have an A here? or a newly created DTO?
// lets check: (demo purpose again)
when (param) {
is ADTO -> store(param) // which now returns an A
is A -> update(param) // maybe updated also our A so a current A is returned
}.also { certainlyA ->
println("After saving/updating: $certainlyA sharedResettable=${certainlyA.sharedResettable /* this was deliberately not part of the data class toString() */}")
}
}
// assume the following signature for store & update:
fun <T> update(param : T) : T
fun store(a : AbstractA) : A
Sample output:
Starting with: A(mandatoryProperty=123, sharedReadonly=from backend) sharedResettable=i am from backend
After saving/updating: A(mandatoryProperty=123, sharedReadonly=from backend) sharedResettable=ef7a3dc0-a4ac-47f0-8a73-0ca0ef5069fa
Starting with: ADTO(sharedReadonly=from dto) sharedResettable=i am dto
After saving/updating: A(mandatoryProperty=127, sharedReadonly=from dto) sharedResettable=57b8b3a7-fe03-4b16-9ec7-742f292b5786
I did not yet show you the ugly part, but you already mentioned it yourself... How do you transform your ADTO to A and viceversa? I will leave that up to you. There are several approaches here (manually, using reflection or mapping utilities, etc.).
This variant cleanly seperates all the DTO specific from the non-DTO-specific properties. However it will also lead to redundant code (all the override, etc.). But at least you know on which object type you operate and can setup signatures accordingly.
Something like 3 is probably easier to setup and to maintain (regarding the data class itself ;-)) and if you set the boundaries correctly it may even be clear, when there is a null in there and when not... So showing that example too. Starting with a rather annoying variant first (annoying in the sense that it throws an exception when you try accessing the variable if it wasn't set yet), but at least you spare the !! or null-checks here:
data class B(
val sharedOnly : String,
var sharedResettable : String
) {
// why nullable? Let it hurt ;-)
lateinit var mandatoryProperty: ID // ok... Long is not usable with lateinit... that's why there is this ID instead
}
data class ID(val id : Long)
Demo:
val b = B("backend", "resettable")
// println(newB.mandatoryProperty) // uh oh... this hurts now... UninitializedPropertyAccessException on the way
val newB = store(b)
println(newB.mandatoryProperty) // that's now fine...
But: even though accessing mandatoryProperty will throw an Exception it is not visible in the toString nor does it look nice if you need to check whether it already has been initialized (i.e. by using ::mandatoryProperty::isInitialized).
So I show you another variant (meanwhile my favorite, but... uses null):
data class C(val mandatoryProperty: Long?,
val sharedOnly : String,
var sharedResettable : String) {
// this is our DTO constructor:
constructor(sharedOnly: String, sharedResettable: String) : this(null, sharedOnly, sharedResettable)
fun hasID() = mandatoryProperty != null // or isDTO, etc. what you like/need
}
// note: you could extract the val and the method also in its own interface... then you would use an override on the mandatoryProperty above instead
// here is what such an interface may look like:
interface HasID {
val mandatoryProperty: Long?
fun hasID() = mandatoryProperty != null // or isDTO, etc. what you like/need
}
Usage:
val c = C("dto", "resettable") // C(mandatoryProperty=null, sharedOnly=dto, sharedResettable=resettable)
when {
c.hasID() -> update(c)
else -> store(c)
}.also {newC ->
// from now on you should know that you are actually dealing with an object that has everything in place...
println("$newC") // prints: C(mandatoryProperty=123, sharedOnly=dto, sharedResettable=resettable)
}
The last one has the benefit, that you can use the copy-method again, e.g.:
val myNewObj = c.copy(mandatoryProperty = 123) // well, you probably don't do that yourself...
// but the following might rather be a valid case:
val myNewDTO = c.copy(mandatoryProperty = null)
The last one is my favorite as it needs the fewest code and uses a val instead (so also no accidental override is possible or you operate on a copy instead). You could also just add an accessor for the mandatoryProperty if you do not like using ? or !!, e.g.
fun getMandatoryProperty() = mandatoryProperty ?: throw Exception("You didn't set it!")
Finally if you have some helper methods like hasID(isDTO or whatever) in place it might also be clear from the context what you are exactly doing. The most important is probably to setup a convention that everyone understands, so they know when to apply what or when to expect something specific.
I need to convert these code into Java 8 Stream I tried it using the given below code written by me but still I haven't got what I wanted.
//contractList is list of Contract class
//contract.getProgramId() returns String
//contract.getEnrollmentID() returns String
//'usage = CommonUtils.getUsageType()' is other service to call wich returns String
//enroll and usage are String type
//enrollNoWithUsageTypeJson is json object '{"enroll": value, "usage": value}'
//usages is List<JSONObject> where enrollNoWithUsageTypeJson need to add
for (Contract contract : contractList) {
if (!StringUtils.isEmpty(contract.getProgramId())) {
enroll = contract.getEnrollmentID();
usage = CommonUtils.getUsageType(envProperty, contract.getProgramId());
if (!(StringUtils.isEmpty(enroll) || StringUtils.isEmpty(usage))) {
enrollNoWithUsageTypeJson.put("enroll", enroll);
enrollNoWithUsageTypeJson.put("usage", usage);
usages.add(enrollNoWithUsageTypeJson);
}
}
}
This is till now what I have got:
contractList.stream()
.filter(contract -> !StringUtils.isEmpty(contract) &&
!StringUtils.isEmpty(contract.getProgramId()))
.collect(Collectors.to);
Thakyou in advance :)
Here is how a stream based version of your code might look like (add static imports as needed):
List<JSONObject> usages = contractList.stream()
.filter(c -> isNotEmpty(c.getProgramId()))
.map(c -> new SimpleEntry<>(c.getEnrollmentID(), getUsageType(envProperty, c.getProgramId())))
.filter(e -> isNotEmpty(e.getKey()) && isNotEmpty(e.getValue())))
.map(e -> {
enrollNoWithUsageTypeJson.put("enroll", e.getKey());
enrollNoWithUsageTypeJson.put("usage", e.getValue());
return enrollNoWithUsageTypeJson; })
.collect(toList());
I took the liberty of using isNotEmpty from Apache Commons as given this option !isEmpty looks terrible. I am (ab)using AbstractMap.SimpleEntry to hold a pair of values. If you feel getKey, getValue make the code less readable, you can introduce a class to hold these 2 variables. E.g.:
class EnrollUsage {
String enroll, usage;
}
You may also prefer to define a method:
JSONObject withEnrollAndUsage(JSONObject json, String enroll, String usage) {
json.put("enroll", enroll);
json.put("usage", usage);
return json;
}
and in the above use instead:
.map(e -> withEnrollAndUsage(enrollNoWithUsageTypeJson, e.getKey(), e.getValue()))
Keep in mind that you never really "need" to convert code to use streams. There are cases where using streams, albeit intellectually satisfying, actually complicates your code. Exercise your best judgement in this case.
I have 3 interfaces
public interface IGhOrg {
int getId();
String getLogin();
String getName();
String getLocation();
Stream<IGhRepo> getRepos();
}
public interface IGhRepo {
int getId();
int getSize();
int getWatchersCount();
String getLanguage();
Stream<IGhUser> getContributors();
}
public interface IGhUser {
int getId();
String getLogin();
String getName();
String getCompany();
Stream<IGhOrg> getOrgs();
}
and I need to implement Optional<IGhRepo> highestContributors(Stream<IGhOrg> organizations)
this method returns a IGhRepo with most Contributors(getContributors())
I tried this
Optional<IGhRepo> highestContributors(Stream<IGhOrg> organizations){
return organizations
.flatMap(IGhOrg::getRepos)
.max((repo1,repo2)-> (int)repo1.getContributors().count() - (int)repo2.getContributors().count() );
}
but it gives me the
java.lang.IllegalStateException: stream has already been operated upon or closed
I understand that count() is a terminal operation in Stream but I can't solve this problem, please help!
thanks
Is possible to know the size of a stream without using a terminal operation
No it's not, because streams can be infinite or generate output on demand. It's not necessary that they are backed by collections.
but it gives me the
java.lang.IllegalStateException: stream has already been operated upon or closed
That's becase you are returning the same stream instance on each method invocation. You should return a new Stream instead.
I understand that count() is a terminal operation in Stream but I can't solve this problem, please help!
IMHO you are misusing the streams here. Performance and simplicity wise it's much better that you return some Collection<XXX> instead of Stream<XXX>
NO.
This is not possible to know the size of a stream in java.
As mentioned in java 8 stream docs
No storage. A stream is not a data structure that stores elements;
instead, it conveys elements from a source such as a data structure,
an array, a generator function, or an I/O channel, through a pipeline
of computational operations.
You don't specify this, but it looks like some or possibly all of the interface methods that return Stream<...> values don't return a fresh stream each time they are called.
This seems problematic to me from an API point of view, as it means each of these streams, and a fair chunk of the object's functionality can be used at most once.
You may be able to solve the particular problem you are having by ensuring that the stream from each object is used only once in the method, something like this:
Optional<IGhRepo> highestContributors(Stream<IGhOrg> organizations) {
return organizations
.flatMap(IGhOrg::getRepos)
.distinct()
.map(repo -> new AbstractMap.SimpleEntry<>(repo, repo.getContributors().count()))
.max(Map.Entry.comparingByValue())
.map(Map.Entry::getKey);
}
Unfortunately it looks like you will now be stuck if you want to (for example) print a list of the contributors, as the stream returned from getContributors() for the returned IGhRepo has already been consumed.
You might want to consider having your implementation objects return a fresh stream each time a stream returning method is called.
You could keep a counter that is incremented per "iteration" using peek. In the example below the counter is incremented before every item is processed with doSomeLogic
final var counter = new AtomicInteger();
getStream().peek(item -> counter.incrementAndGet()).forEach(this::doSomeLogic);