I have implement a validate function, sample code are as below:
public class TestObject {
LocalDateTime d1;
LocalDateTime d2;
//getters, setters
}
public class ErrorResult {
String errorMsg;
public ErrorResult(String errorMsg){
this.errorMsg = errorMsg;
}
}
public Observable<ErrorResult> validate(TestObject testObject){
// implementation section
}
For the implementation section, I have tried to use Observable.fromCallable() and Observable.defer() functions to do the same job, for example:
// for implementation using Observable.fromCallable
return Observable.fromCallable(() -> {
LocalDateTime d1 = testObject.getD1();
LocalDateTime d2 = testObject.getD2();
if(d1.isBefore(d2))
return Observable.just(new ErrorResult("Error d1 is before d2"));
return Observable.empty();
});
// for implementation using Observable.defer
return Observable.defer(() -> {
LocalDateTime d1 = testObject.getD1();
LocalDateTime d2 = testObject.getD2();
if(d1.isBefore(d2))
return Observable.just(new ErrorResult("Error d1 is before d2"));
return Observable.empty();
});
While the implementation of the logic within the anonymous functions is the same,
the implementation using Observable.fromCallable throw a compilation error in IDE (Intellij), which stated "no instance(s) of type variable(s) T exist so that Observable conforms to ErrorResult". It was caused by the return of Observable.empty() as the fallback return in case no error exists
the implementation using Observable.defer compile successfully without error
May I know what is the difference between Observable.fromCallable() and Observable.defer() in this case?
Thanks a lot for the help
fromCallable is not designed to return an Observable, while defer is. So in your example with fromCallable, you're ending up with a Observable<Observable<ErrorResult>>. You actually can't get your desired behavior with fromCallable, because you can't use it to get an empty Observable (returning null from the Callable results in a NullPointerException).
Related
I know that my question has been asked already multiple times, but I feel like there is still no satisfying answer to it.
Basically I have two downstream services which I want to call (in parallel) and then I want to combine the results and return it (as Json). Both calls can fail but both results are not mandatory, so also an empty combined response is possible:
class FirstResponse {...}
class SecondResponse {...}
class CombinedResponse {
private FirstResponse first;
private SecondResponse second;
}
class FirstService {
Mono<FirstResponse> get(){
return webclient.get(...)
.bodyToMono(FirstResponse.class)
.onErrorResume(throwable -> Mono.empty);
}
}
class SecondService {
Mono<SecondResponse> get(){
return webclient.get(...)
.bodyToMono(SecondResponse.class)
.onErrorResume(throwable -> Mono.empty);
}
}
#RestController(...)
class CombinationController {
#GetMapping(...)
Mono<CombinedResponse> getCombined() {
Mono.zip(firstService.get(), secondService.get(), (first, second) -> {
return new CombinedResponse(first, second);
})
}
}
Now in case the calls to firstService fails, also the response from secondService gets ignored. But what I actually would like to have, is that CombinedResponse still gets (partially populated).
As a disclaimer I have to say, that I am currently migrating my code from rxjava1 and there in case of downstream errors I just return Single.just(null). This allows me to zip both results and just sets the values to null.
About Mono.zip() :
An error or empty completion of any source will cause other sources to
be cancelled and the resulting Mono to immediately error or complete,
respectively.
Also, reactor does not allow null values, so you should do some workaround in your case. In some simple cases it is easy to define some default value in case of error (for example, empty String), but for custom types it would be weird to create an empty object.
As an alternative for such cases I would suggest to use Optional.
This solution adds some boilerplate code, though.
First service:
class FirstService {
Mono<Optional<FirstResponse>> get(){
return webclient.get(...)
.bodyToMono(FirstResponse.class)
.map(Optional::of)
.onErrorReturn(Optional.empty());
}
}
Second service:
class SecondService {
Mono<Optional<SecondResponse>> get(){
return webclient.get(...)
.bodyToMono(SecondResponse.class)
.map(Optional::of)
.onErrorReturn(Optional.empty());
}
}
And "combiner" :
#GetMapping(...)
Mono<CombinedResponse> getCombined() {
Mono.zip(firstService.get(), secondService.get())
.map(tuple -> {
// check optionals here from tuple.getT1() and tuple.getT2()
// and do whatever you want
})
...
}
I have an interface that I am implementing that is generated from a WSDL, so I can't change the signatures. One of the methods returns a List<Attributes> with Attributes being another WSDL generated class. The call flow has been updated to be reactive, and the Mono is bubbled all the way up the chain to this implementing class.
public List<Attributes> getUserProfile(final String filterValue);
The return statement calls a method that returns a Mono<UserProfile> which is then passed to another method that returns the List, but I cannot figure out how to subscribe to this to get the List so that my code compiles and works in a non-blocking way?
#Override
public List<Attributes> getUserProfile(final String filterValue) {
return getUserProfile(serviceName, filterValue)
.map(userProfile -> userProfileToAttributeList(userProfile));
// .subscribe(userProfile -> userProfileToAttributeList(userProfile));
// .map(listAttributes -> listAttributes);
// Mono<UserProfile> userProfileMono = getUserProfile(serviceName, filterValue);
// return userProfileMono.subscribe(userProfile -> userProfileToAttributeList(userProfile));
}
private Mono<UserProfile> getUserProfile(final String serviceName,final String filterValue) {
return myService.getUserProfile(serviceName, filterValue);
}
private List<Attributes> userProfileToAttributeList(final UserProfile userProfile) {
return userProfile.getAttributes().stream().map(MyServiceEndpoint::newAttribute).collect(Collectors.toList());
}
Since you can't change the method signature to return Mono or Flux there is no other way around it, you need to block to get the "real" List<Attributes>.
Reactive only works if the complete operation is reactive on each step. Since this method "says" it will return List<Attributes> and not "promises" to return a List<Attributes> at some point in the future when needed and requested you have no option here.
I'm trying to get into basics of functional programming with Java 8 and I have a simple task which is to set a property on the object and then persist it. The database proper type is ltree so it might fail if it contains not allowed characters. I want to process items one-by-one and log exceptions/successes.
I choose to use the Vavr library because Try.of() exception handling and I want to learn to just use it as it seems very helpful.
here is what I came up with but I'm not satisfied enough:
public class PathHandler {
private final DocVersionDAO dao;
public void processWithHandling() {
Try.of(this::process)
.recover(x -> Match(x).of(
Case($(instanceOf(Exception.class)), this::logException)
));
}
private Stream<Try<DocVersion>> logException(Exception e) {
//log exception now but what to return? also I would like to have DocVersion here too..
return null;
}
public Stream<Try<DocVersion>> process() {
return dao.getAllForPathProcessing() //returns Stream<DocVersion>
.map(this::justSetIt)
.map(this::save);
}
public DocVersion justSetIt(DocVersion v) {
String path = Optional.ofNullable(v.getMetadata().getAdditionals().get(Vedantas.PATH))
.orElse(null);
log.info(String.format("document of uuid %s has matadata path %s; setting it", v.getDocument2().getUUID(), path));
v.getDocument2().setPath(path);
return v;
}
#Transactional(propagation = Propagation.REQUIRES_NEW)
public Try<DocVersion> save(DocVersion v) {
return Try.of(() -> dao.save(v));
}
}
the goal is quite simple so could you teach me proper way to do it?
I'm afraid, this will become highly opinionated. Anyway, I try something.
... which happened before I realized, what Vavr actually provides. It attempts to cover everything mentioned here, like immutable data structures and monad syntax sugaring (with the For statement), and goes beyond that by coming up even with pattern matching. It takes a comprehensive set of FP concepts and rebuilds them using Java and it is no surprise Scala comes into one's mind seeing this ("Vavr is greatly inspired by Scala").
Now the foundations of functional programming can't be covered by a single SO post. And it might be problematic to get familiar with them in a language like Java which isn't geared towards it. So perhaps it is better to approach them in their natural habitat like the Scala language, which is still in some proximity to Java, or Haskell, which is not.
Coming back from this detour applying the features of Vavr may be more straight foward for the initiated. But likelely not for the Java developer sitting next to you in the office, who is less willing to go the extra mile and comes up with arguments that can't be just dismissed, like this one: "If we wanted to it that way, we would be a Scala shop". Therefore I'd say, applying Vavr asks for a pragmatic attitute.
To corroborate the Vavra-Scala argument, let's take Vavra's For construct (all Lists mentioned are io.vavr.collection.List), it looks like this:
Iterator<Tuple2<Integer, String>> tuples =
For(List.of(1, 2, 3), i ->
For(List.of(4, 5, 6))
.yield(a -> Tuple.of(i, String.valueOf(a))));
In Scala you'd encounter For and yield this way.
val tuples = for {
i <- 1 to 3
a <- 4 to 6
} yield (i, String.valueOf(a))
All the monad machinery remains under the hood, where Vavra brings more of an approximation, necessarily leaking some internals. For the purpose of learning it might be puzzling to start with Vavra's hybrid creatures.
So what remains of my post is a small time treatment of some FP basics, using the example of the OP, elaborating on immutability and Try on a trench-level, but omitting pattern matching. Here we go:
One of the defining characteristics of FP are functions free of side effects ("pure functions"), which naturally (so to speak) comes along with immutable data structures/objects, which may sound kind of weird. One obvious pay off is, that you don't have to worry, that your operations create unintended changes at some other place. But Java doesn't enforce that in any way, also its immutable collections are only so on a superficial level. From the FP signature characteristics Java only offers higher order functions with java-lambdas.
I used the functional style quite a bit on the job manipulating complicated structures where I stuck to those 2 principles. E.g. load a tree T of objects from a db, do some transformations on it, which meant producing another tree of objects T', sort of one big map operation, place the changes in front of the user to accept or reject them. If accepted, apply the changes to the related JPA entities and persist them. So after the functional transformation two mutations were applied.
I'd propose, to apply FP in this sense and tried to formulate an according version of your code, using an immutable DocVersion class. I chose to simplify the Metadata part for the sake of the example.
I also tried to highlight, how the "exception-free" Try approach (some of it poached from here) could be formulated and utilized some more. Its a small time version of Vavr's Try, hopefully focusing on the essentials. Note its proximity to Java's Optional and the map and flatMap methods in there, which render it an incarnation of the FP concept called monad. It became notorious in a sweep of highly confusing blog posts some years ago usually starting with "What is a monad?" (e.g. this one). They have cost me some weeks of my life, while it is rather easy to get a good intuition of the issue just by using Java streams or Optionals. Miran Lipovaca's "Learn Yourself a Haskell For Great Good" later made good for it to some extent, and Martin Odersky's Scala language.
Boasting with of, map and flatMap, Try would, roughly speaking, qualify for a syntax-sugaring like you find it in C# (linq-expressions) or Scala for-expressions. In Java there is no equivalent, but some attempts to at least compensate a bit are listed here, and Vavr looks like another one. Personally I use the jool library occasionally.
Passing around streams as function results seems not quite canonical to me, since streams are not supposed to get reused. That's also the reason to create a List as an intermediary result in process().
public class PathHandler {
class DocVersionDAO {
public void save(DocVersion v) {
}
public DocVersion validate(DocVersion v) {
return v;
}
public Stream<DocVersion> getAllForPathProcessing() {
return null;
}
}
class Metadata {
#Id
private final Long id;
private final String value;
Metadata() {
this.id = null;
this.value = null;
}
Metadata(Long id, String value) {
this.id = id;
this.value = value;
}
public Optional<String> getValue() {
return Optional.of(value);
}
public Metadata withValue(String value) {
return new Metadata(id, value);
}
}
public #interface Id {
}
class DocVersion {
#Id
private Long id;
private final Metadata metadatata;
public Metadata getMetadatata() {
return metadatata;
}
public DocVersion(Long id) {
this.id = id;
this.metadatata = new Metadata();
}
public DocVersion(Long id, Metadata metadatata) {
this.id = id;
this.metadatata = metadatata;
}
public DocVersion withMetadatata(Metadata metadatata) {
return new DocVersion(id, metadatata);
}
public DocVersion withMetadatata(String metadatata) {
return new DocVersion(id, this.metadatata.withValue(metadatata));
}
}
private DocVersionDAO dao;
public List<DocVersion> process() {
List<Tuple2<DocVersion, Try<DocVersion>>> maybePersisted = dao.getAllForPathProcessing()
.map(d -> augmentMetadata(d, LocalDateTime.now().toString()))
.map(d -> Tuple.of(d, Try.of(() -> dao.validate(d))
.flatMap(this::trySave)))
.peek(i -> i._2.onException(this::logExceptionWithBadPracticeOfUsingPeek))
.collect(Collectors.toList());
maybePersisted.stream()
.filter(i -> i._2.getException().isPresent())
.map(e -> String.format("Item %s caused exception %s", e._1.toString(), fmtException(e._2.getException().get())))
.forEach(this::log);
return maybePersisted.stream()
.filter(i -> !i._2.getException().isPresent())
.map(i -> i._2.get())
.collect(Collectors.toList());
}
private void logExceptionWithBadPracticeOfUsingPeek(Exception exception) {
logException(exception);
}
private String fmtException(Exception e) {
return null;
}
private void logException(Exception e) {
log(fmtException(e));
}
public DocVersion augmentMetadata(DocVersion v, String augment) {
v.getMetadatata().getValue()
.ifPresent(m -> log(String.format("Doc %d has matadata %s, augmenting it with %s", v.id, m, augment)));
return v.withMetadatata(v.metadatata.withValue(v.getMetadatata().value + augment));
}
public Try<DocVersion> trySave(DocVersion v) {
return new Try<>(() -> {
dao.save(v);
return v;
});
}
private void log(String what) {
}
}
Try looks like this
public class Try<T> {
private T result;
private Exception exception;
private Try(T result, Exception exception) {
this.result = result;
this.exception = exception;
}
public static <T> Try<T> of(Supplier<T> f)
{
return new Try<>(f);
}
T get() {
if (result == null) {
throw new IllegalStateException();
}
return result;
}
public void onException(Consumer<Exception> handler)
{
if (exception != null)
{
handler.accept(exception);
}
}
public <U> Try<U> map(Function<T, U> mapper) {
return exception != null ? new Try<>(null, exception) : new Try<>(() -> mapper.apply(result));
}
public <U> Try<U> flatMap(Function<T, Try<U>> mapper) {
return exception != null ? null : mapper.apply(result);
}
public void onError(Consumer<Exception> exceptionHandler) {
if (exception != null) {
exceptionHandler.accept(exception);
}
}
public Optional<Exception> getException() {
return Optional.of(exception);
}
public Try(Supplier<T> r) {
try {
result = r.get();
} catch (Exception e) {
exception = e;
}
}
}
I have a validation function that return which part is failing. For example -
public class DateValidator{
public String validateDate(startDate, endDate){
try{
LocalDate.parse(startDate, formatter);
LocalDate.parse(endDate, formatter);
} catch(DateTimeParseException e) {
return "INVALID_DATE_FORMAT";
}
if (startDate.isAfter(endDate)) {
return "INVALID_START_AND_END_DATES";
}
..... so on
}
}
I want to use the this in Drools for Validation as
rule
"ValidateDate"
when
$error: Error();
$request: Request();
DateValidator( $dateValidation: validateDate($request.getStartDate(), $request.getEndDate()) != null);
then
$error.getBadRequest($dateValidation);
end;
I want to use the return type of the variable as not null means the validation did not passed. But I am getting below exception for the DRL file -
text=Variables can not be used inside bindings.
Variable [$request] is being used in binding
'validateDate($request.getStartDate(), $request.getEndDate())']
Try to execute the function call as part of a from Conditional Element:
rule
"ValidateDate"
when
$error: Error();
$request: Request(
$startDate: startDate,
$endDate: endDate
);
$dv: DateValidator()
$msg: String() from $dv.validateDate($startDate, $endDate)
then
$error.getBadRequest($msg);
end
Hope it helps,
Let's say I'd like to perform the following command:
house.getFloor(0).getWall(WEST).getDoor().getDoorknob();
To avoid a NullPointerException, I'd have to do the following if:
if (house != null && house.getFloor(0) && house.getFloor(0).getWall(WEST) != null
&& house.getFloor(0).getWall(WEST).getDoor() != null) ...
Is there a way or an already existing Utils class that does this more elegantly, let's say something like the following?
checkForNull(house.getFloor(0).getWall(WEST).getDoor().getDoorknob());
In case you can't avoid breaking Law of Demeter (LoD) as stated in the chosen answer, and with Java 8 introducing Optional, it would be probably the best practice to handle nulls in chains of gets such as yours.
The Optional type will enable you to pipe multiple map operations (which contain get calls) in a row. Null checks are automatically handled under the hood.
For example, when the objects aren't initialized, no print() will be made and no Exceptions will be thrown. It all we be handled gently under the hood. When objects are initialized, a print will be made.
System.out.println("----- Not Initialized! -----");
Optional.ofNullable(new Outer())
.map(out -> out.getNested())
.map(nest -> nest.getInner())
.map(in -> in.getFoo())
.ifPresent(foo -> System.out.println("foo: " + foo)); //no print
System.out.println("----- Let's Initialize! -----");
Optional.ofNullable(new OuterInit())
.map(out -> out.getNestedInit())
.map(nest -> nest.getInnerInit())
.map(in -> in.getFoo())
.ifPresent(foo -> System.out.println("foo: " + foo)); //will print!
class Outer {
Nested nested;
Nested getNested() {
return nested;
}
}
class Nested {
Inner inner;
Inner getInner() {
return inner;
}
}
class Inner {
String foo = "yeah!";
String getFoo() {
return foo;
}
}
class OuterInit {
NestedInit nested = new NestedInit();
NestedInit getNestedInit() {
return nested;
}
}
class NestedInit {
InnerInit inner = new InnerInit();
InnerInit getInnerInit() {
return inner;
}
}
class InnerInit {
String foo = "yeah!";
String getFoo() {
return foo;
}
}
So, with your getters chain it will look like this:
Optional.ofNullable(house)
.map(house -> house.getFloor(0))
.map(floorZero -> floorZero.getWall(WEST))
.map(wallWest -> wallWest.getDoor())
.map(door -> wallWest.getDoor())
The return of it will be something like Optional<Door> which will allow you much safer work without worrying of null exceptions.
In order to check a chain of gets for null you may need to call your code from a closure. The closure call code will look like this:
public static <T> T opt(Supplier<T> statement) {
try {
return statement.get();
} catch (NullPointerException exc) {
return null;
}
}
And you call it using the following syntax:
Doorknob knob = opt(() -> house.getFloor(0).getWall(WEST).getDoor().getDoorknob());
This code is also type safe and in general works as intended:
Returns an actual value of the specified type if all the objects in the chain are not null.
Returns null if any of the objects in the chain are null.
You may place opt method into shared util class and use it everywhere in your application.
The best way would be to avoid the chain. If you aren't familiar with the Law of Demeter (LoD), in my opinion you should. You've given a perfect example of a message chain that is overly intimate with classes that it has no business knowing anything about.
Law of Demeter: http://en.wikipedia.org/wiki/Law_of_Demeter
You could of course simply wrap the whole expression up in a try-catch block, but that's a bad idea. Something cleaner is the Null object pattern. With that, if your house doesn't have floor 0, it just returns a Floor that acts like a regular Floor, but has no real content; Floors, when asked for Walls they don't have, return similar "Null" Walls, etc, down the line.
Make sure things that can't logically be null are not. For example - a house always has a West wall. In order to avoid such exceptions in state, you can have methods to check whether the state you expect is present:
if (wall.hasDoor()) {
wall.getDoor().etc();
}
This is essentially a null-check, but might not always be.
The point is that you should do something in case you have a null. For example - return or throw an IllegalStateException
And what you shouldn't do - don't catch NullPointerException. Runtime exceptions are not for catching - it is not expected that you can recover from them, nor it is a good practice to rely on exceptions for the logic flow. Imagine that you actually don't expect something to be null, and you catch (and log) a NullPointerException. This will not be very useful information, since many things can be null at that point.
Better solution for me is to use java.util.Optional.map(..) to chain these checks : https://stackoverflow.com/a/67216752/1796826
There is no checkForNull method that you can write that will facilitate this (that's simply not how method invokation and argument evaluation works in Java).
You can break down the chained statements into multiple statements, checking at every step. However, perhaps a better solution is to not have these methods return null in the first place. There is something called the Null Object Pattern that you may want to use instead.
Related questions
How to avoid != null statements in Java?
You could potentially have a generic method like below:
public static <T> void ifPresentThen(final Supplier<T> supplier, final Consumer<T> consumer) {
T value;
try {
value = supplier.get();
} catch (NullPointerException e) {
// Don't consume "then"
return;
}
consumer.accept(value);
}
So now you would be able to do
ifPresentThen(
() -> house.getFloor(0).getWall(WEST).getDoor().getDoorknob(),
doorKnob -> doSomething());
implementing nullPointer try/catch with a Supplier you can send it all chain of get
public static <T> T getValue(Supplier<T> getFunction, T defaultValue) {
try {
return getFunction.get();
} catch (NullPointerException ex) {
return defaultValue;
}
}
and then call it in this way.
ObjectHelper.getValue(() -> object1.getObject2().getObject3().getObject4()));
Very old question, but still adding my suggestion:
I would suggest instead of getting the DoorKnob from deep within the House in one method call chain, you should try to let the DoorKnob be provided to this class from the calling code, or by creating a central lookup facility specifically for this purpose (e.g. a DoorKnob service)
Simplified example of design with loose coupling:
class Architect {
FloorContractor floorContractor;
void build(House house) {
for(Floor floor: house.getFloors()) {
floorContractor.build(floor);
}
}
}
class FloorContractor {
DoorMaker doorMaker;
void build(Floor floor) {
for(Wall wall: floor.getWalls()) {
if (wall.hasDoor()) {
doorMaker.build(wall.getDoor());
}
}
}
}
class DoorMaker {
Tool tool;
void build(Door door) {
tool.build(door.getFrame());
tool.build(door.getHinges());
tool.build(door.getDoorKnob());
}
}
// Example
LazyObject.from(curr).apply(A.class, A::getB).apply(B.class, B::getC).apply(C.class, C::getD).to(String.class);
// LazyObject.java
public class LazyObject {
private Object value;
private LazyObject(Object object) {
this.value = object;
}
public <F, T> LazyObject apply(Class<F> type, Function<F, T> func) {
Object v = value;
if (type.isInstance(v)) {
value = func.apply(type.cast(v));
} else {
value = null; // dead here
}
return this;
}
public <T> void accept(Class<T> type, Consumer<T> consumer) {
Object v = value;
if (type.isInstance(v)) {
consumer.accept(type.cast(v));
}
}
public <T> T to(Class<T> type) {
Object v = value;
if (type.isInstance(v)) {
return type.cast(v);
}
return null;
}
public static LazyObject from(Object object) {
return new LazyObject(object);
}
}