This question already has answers here:
Limit a stream by a predicate
(19 answers)
Closed 8 years ago.
I have a set and a method:
private static Set<String> set = ...;
public static String method(){
final String returnVal[] = new String[1];
set.forEach((String str) -> {
returnVal[0] += str;
//if something: goto mark
});
//mark
return returnVal[0];
}
Can I terminate the forEach inside the lambda (with or without using exceptions)?
Should I use an anonymous class?
I could do this:
set.forEach((String str) -> {
if(someConditions()){
returnVal[0] += str;
}
});
but it wastes time.
implementation using stream.reduce
return set.parallelStream().reduce((output, next) -> {
return someConditions() ? next : output;
}).get(); //should avoid empty set before
I am looking for the fastest solution so exception and a 'real' for each loop are acceptable if they are fast enough.
I'm reluctant to answer this even though I'm not entirely sure what you're attempting to accomplish, but the simple answer is no, you can't terminate a forEach when it's halfway through processing elements.
The official Javadoc states that it is a terminal operation that applies against all elements in the stream.
Performs an action for each element of this stream.
This is a terminal operation.
If you want to gather the results into a single result, you want to use reduction instead.
Be sure to consider what it is a stream is doing. It is acting on all elements contained in it - and if it's filtered along the way, each step in the chain can be said to act on all elements in its stream, even if it's a subset of the original.
In case you were curious as to why simply putting a return wouldn't have any effect, here's the implementation of forEach.
default void forEach(Consumer<? super T> action) {
Objects.requireNonNull(action);
for (T t : this) {
action.accept(t);
}
}
The consumer is explicitly passed in, ad this is done independently of the actual iteration going on. I imagine you could throw an exception, but that would be tacky when more elegant solutions likely exist.
Related
This question already has answers here:
java.util.NoSuchElementException: No value present even though we use stream
(2 answers)
Closed 9 months ago.
While filtering through a list of user defined class type using Stream API has been encountered some cases where no element has been found in the list for given condition.
How to prevent exception in such case and handle according to business logic using optional class?
Stream API method looks like :
public static Optional<Policy> getPolicy(ReturnTermPolicy policyType,
String policyKey) {
Optional<Policy> policy = Optional.of(policyType.getPolicies().stream()
.filter(temp -> temp.getPolicyKey().equals(policyKey))
.findFirst().get());
return policy;
}
The calling code looks like that:
Optional<Policy> updatedPolicyOptional = getPolicy(updatedPolies,policykey); // <- exception is being generated here
if (updatedPolicyOptional.isPresent()) {
// business logic
}
else {
// business logic
}
Output :
Verify audit report for update made in TC_08
java.util.NoSuchElementException: No value present
at java.util.Optional.get(Optional.java:135)
There's no need to extract the result from the optional object just in order to wrap it with an optional again.
It's pointless and will trigger NoSuchElementException if result is not present. To solve the problem, remove the call of get() which both unsafe and redundant in this case:
public static Optional<Policy> getPolicy(ReturnTermPolicy policyType,
String policyKey) {
return policyType.getPolicies().stream()
.filter(temp -> temp.getPolicyKey().equals(policyKey))
.findFirst();
}
In order implement your conditional logic fluently you can make use of Optional.ifPresentOrElse() which expects a Consumer that would be executed if result is present and a Runnable that will be fired in case if optional is empty. Note, this method is accessible with Java 9.
getPolicy(updatedPolies,policykey).ifPresentOrElse(policy -> doSomething(policy),
() -> doSomethingElse());
With Java 8 you can use Optional.ifPresentOrElse() that expects consumer and can cave the if part of conditional logic. And for the case of empty optional, you will need a condition.
Optional<Policy> policy = getPolicy(updatedPolies,policykey);
policy.ifPresentOrElse(policy -> doSomething(policy));
if (!policy.isPresent()) doSomethingElse();
findFirst() already returns an Optional, trying to get() it leads to an error when it is empty. So your function should be:
public static Optional<Policy> getPolicy(ReturnTermPolicy policyType,
String policyKey) {
return = policyType.getPolicies().stream()
.filter(temp -> temp.getPolicyKey().equals(policyKey))
.findFirst();
}
And depending on your Java version (and your business logic) you can use things like:
Java 8.
if (updatedPolicyOptional.isPresent()) {
// business logic
}
else {
// business logic
}
or
T value = updatedPolicyOptional(mapToTFunctor).orElse(someTValue);
Java 9.
updatedPolicyOptional.ifPresentOrElse(someConsumer,someNoParamFunctor);
I couldn't wrap my head around writing the below condition using Java Streams. Let's assume that I have a list of elements from the periodic table. I've to write a method that returns a String by checking whether the list has Silicon or Radium or Both. If it has only Silicon, method has to return Silicon. If it has only Radium, method has to return Radium. If it has both, method has to return Both. If none of them are available, method returns "" (default value).
Currently, the code that I've written is below.
String resolve(List<Element> elements) {
AtomicReference<String> value = new AtomicReference<>("");
elements.stream()
.map(Element::getName)
.forEach(name -> {
if (name.equalsIgnoreCase("RADIUM")) {
if (value.get().equals("")) {
value.set("RADIUM");
} else {
value.set("BOTH");
}
} else if (name.equalsIgnoreCase("SILICON")) {
if (value.get().equals("")) {
value.set("SILICON");
} else {
value.set("BOTH");
}
}
});
return value.get();
}
I understand the code looks messier and looks more imperative than functional. But I don't know how to write it in a better manner using streams. I've also considered the possibility of going through the list couple of times to filter elements Silicon and Radium and finalizing based on that. But it doesn't seem efficient going through a list twice.
NOTE : I also understand that this could be written in an imperative manner rather than complicating with streams and atomic variables. I just want to know how to write the same logic using streams.
Please share your suggestions on better ways to achieve the same goal using Java Streams.
It could be done with Stream IPA in a single statement and without multiline lambdas, nested conditions and impure function that changes the state outside the lambda.
My approach is to introduce an enum which elements correspond to all possible outcomes with its constants EMPTY, SILICON, RADIUM, BOTH.
All the return values apart from empty string can be obtained by invoking the method name() derived from the java.lang.Enum. And only to caver the case with empty string, I've added getName() method.
Note that since Java 16 enums can be declared locally inside a method.
The logic of the stream pipeline is the following:
stream elements turns into a stream of string;
gets filtered and transformed into a stream of enum constants;
reduction is done on the enum members;
optional of enum turs into an optional of string.
Implementation can look like this:
public static String resolve(List<Element> elements) {
return elements.stream()
.map(Element::getName)
.map(String::toUpperCase)
.filter(str -> str.equals("SILICON") || str.equals("RADIUM"))
.map(Elements::valueOf)
.reduce((result, next) -> result == Elements.BOTH || result != next ? Elements.BOTH : next)
.map(Elements::getName)
.orElse("");
}
enum
enum Elements {EMPTY, SILICON, RADIUM, BOTH;
String getName() {
return this == EMPTY ? "" : name(); // note name() declared in the java.lang.Enum as final and can't be overridden
}
}
main
public static void main(String[] args) {
System.out.println(resolve(List.of(new Element("Silicon"), new Element("Lithium"))));
System.out.println(resolve(List.of(new Element("Silicon"), new Element("Radium"))));
System.out.println(resolve(List.of(new Element("Ferrum"), new Element("Oxygen"), new Element("Aurum")))
.isEmpty() + " - no target elements"); // output is an empty string
}
output
SILICON
BOTH
true - no target elements
Note:
Although with streams you can produce the result in O(n) time iterative approach might be better for this task. Think about it this way: if you have a list of 10.000 elements in the list and it starts with "SILICON" and "RADIUM". You could easily break the loop and return "BOTH".
Stateful operations in the streams has to be avoided according to the documentation, also to understand why javadoc warns against stateful streams you might take a look at this question. If you want to play around with AtomicReference it's totally fine, just keep in mind that this approach is not considered to be good practice.
I guess if I had implemented such a method with streams, the overall logic would be the same as above, but without utilizing an enum. Since only a single object is needed it's a reduction, so I'll apply reduce() on a stream of strings, extract the reduction logic with all the conditions to a separate method. Normally, lambdas have to be well-readable one-liners.
Collect the strings to a unique set. Then check containment in constant time.
Set<String> names = elements.stream().map(Element::getName).map(String::toLowerCase).collect(toSet());
boolean hasSilicon = names.contains("silicon");
boolean hasRadium = names.contains("radium");
String result = "";
if (hasSilicon && hasRadium) {
result = "BOTH";
} else if (hasSilicon) {
result = "SILICON";
} else if (hasRadium) {
result = "RADIUM";
}
return result;
i have used predicate in filter to for radium and silicon and using the resulted set i am printing the result.
import java.util.ArrayList;
import java.util.List;
import java.util.Set;
import java.util.stream.Collectors;
public class Test {
public static void main(String[] args) {
List<Element> elementss = new ArrayList<>();
Set<String> stringSet = elementss.stream().map(e -> e.getName())
.filter(string -> (string.equals("Radium") || string.equals("Silicon")))
.collect(Collectors.toSet());
if(stringSet.size()==2){
System.out.println("both");
}else if(stringSet.size()==1){
System.out.println(stringSet);
}else{
System.out.println(" ");
}
}
}
You could save a few lines if you use regex, but I doubt if it is better than the other answers:
String resolve(List<Element> elements) {
String result = elements.stream()
.map(Element::getName)
.map(String::toUpperCase)
.filter(str -> str.matches("RADIUM|SILICON"))
.sorted()
.collect(Collectors.joining());
return result.matches("RADIUMSILICON") ? "BOTH" : result;
}
I have a POJO:
class MyObject {
private Double a;
private String b;
//constructor, getter + setter
}
Some function is creating a list of this POJO. Some values for a might be null, so I want to replace them with 0.0. At the moment I am doing it like this.
public List<MyObject> fetchMyObjects(Predicate predicate) {
List<MyObject> list = getMyListsOfTheDatabase(predicate);
list
.forEach(myObject -> {
if (myObject.getA() == null) {
myObject.setA(0.0);
}
});
return list;
}
Is there a way to integrate the forEach in the return? Something like
return list
.stream()
.someStatement();
It's not about, if this is the best place to convert the nulls to zero, but rather a questions to better understand the streaming api.
Use the peek function
Returns a stream consisting of the elements of this stream, additionally performing the provided action on each element as elements are consumed from the resulting stream.
public List<MyObject> fetchMyObjects(Predicate predicate) {
return getMyListsOfTheDatabase(predicate)
.stream()
.peek(it -> if(it.getA() == null) it.setA(0.0))
.collect(Collectors.toList());
}
While others have been happy to answer your question as it stands, allow me to step a step back and give you the answer you didn’t ask for (but maybe the answer that you want): You don’t want to do that. A stream operation should be free from side effects. What you are asking for is exactly a stream operation that has the side effect of modifying the original objects going into the stream. Such is poor code style and likely to confuse those reading your code after you.
The code you already have solves your problem much more nicely than any combined stream pipeline.
What you may want to have if you can modify your POJO is either a constructor that sets a to 0 if null was retrieved from the database, or method that does it that you may call from list.forEach:
list.forEach(MyObject::setAToZeroIfNull);
It's not about, if this is the best place to convert the nulls to
zero, but rather a questions to better understand the streaming api.
That’s fair. In any case I will let this answer stand for anyone else popping by.
You can't return the same List instance with a single statement, but you can return a new List instance containing the same (possibly modified) elements:
return list.stream()
.map(myObject -> {
if (myObject.getA() == null) {
myObject.setA(0.0);
}
return myObject;
})
.collect(Collectors.toList());
Actually you should be using List::replaceAll:
list.replaceAll(x -> {
if(x.getA() == null) x.setA(0.0D);
return x;
})
forEach doesn't have a return value, so what you might be looking for is map
return list
.stream()
.map(e -> {
if (e.getA() == null) e.setA(0d);
return e;
})
.whateverElse()...
The following would be fine:
list.stream()
.filter(obj -> obj.getA() == null)
.forEach(obj -> obj.setA(0.0));
return list;
However in your case just returning a Stream might be more appropriate (depends):
public Stream<MyObject> fetchMyObjects(Predicate predicate) {
return getMyListsOfTheDatabase(predicate);
}
public Stream<MyObject> streamMyObjects(List<MyObject> list) {
return list.stream()
.peek(obj -> {
if (obj.getA() == null) {
obj.setA(0.0);
}
});
}
I personally never used peek, but here it corrects values.
On code conventions, which are more string in the java community:
Indentation: Java took 4 as opposed to C++'s 3 as more separate methods,
and less indentation was expected. Debatable but okay.
For generic type parameters often a single capital like T, C, S.
For lambda parameters short names, often a single letter, hence I used obj.
I am creating snippets with takeWhile to explore its possibilities. When used in conjunction with flatMap, the behaviour is not in line with the expectation. Please find the code snippet below.
String[][] strArray = {{"Sample1", "Sample2"}, {"Sample3", "Sample4", "Sample5"}};
Arrays.stream(strArray)
.flatMap(indStream -> Arrays.stream(indStream))
.takeWhile(ele -> !ele.equalsIgnoreCase("Sample4"))
.forEach(ele -> System.out.println(ele));
Actual Output:
Sample1
Sample2
Sample3
Sample5
ExpectedOutput:
Sample1
Sample2
Sample3
Reason for the expectation is that takeWhile should be executing till the time the condition inside turns true. I have also added printout statements inside flatmap for debugging. The streams are returned just twice which is inline with the expectation.
However, this works just fine without flatmap in the chain.
String[] strArraySingle = {"Sample3", "Sample4", "Sample5"};
Arrays.stream(strArraySingle)
.takeWhile(ele -> !ele.equalsIgnoreCase("Sample4"))
.forEach(ele -> System.out.println(ele));
Actual Output:
Sample3
Here the actual output matches with the expected output.
Disclaimer: These snippets are just for code practise and does not serve any valid usecases.
Update:
Bug JDK-8193856: fix will be available as part of JDK 10.
The change will be to correct whileOps
Sink::accept
#Override
public void accept(T t) {
if (take = predicate.test(t)) {
downstream.accept(t);
}
}
Changed Implementation:
#Override
public void accept(T t) {
if (take && (take = predicate.test(t))) {
downstream.accept(t);
}
}
This is a bug in JDK 9 - from issue #8193856:
takeWhile is incorrectly assuming that an upstream operation supports and honors cancellation, which unfortunately is not the case for flatMap.
Explanation
If the stream is ordered, takeWhile should show the expected behavior. This is not entirely the case in your code because you use forEach, which waives order. If you care about it, which you do in this example, you should use forEachOrdered instead. Funny thing: That doesn't change anything. 🤔
So maybe the stream isn't ordered in the first place? (In that case the behavior is ok.) If you create a temporary variable for the stream created from strArray and check whether it is ordered by executing the expression ((StatefulOp) stream).isOrdered(); at the breakpoint, you will find that it is indeed ordered:
String[][] strArray = {{"Sample1", "Sample2"}, {"Sample3", "Sample4", "Sample5"}};
Stream<String> stream = Arrays.stream(strArray)
.flatMap(indStream -> Arrays.stream(indStream))
.takeWhile(ele -> !ele.equalsIgnoreCase("Sample4"));
// breakpoint here
System.out.println(stream);
That means that this is very likely an implementation error.
Into The Code
As others have suspected, I now also think that this might be connected to flatMap being eager. More precisely, both problems might have the same root cause.
Looking into the source of WhileOps, we can see these methods:
#Override
public void accept(T t) {
if (take = predicate.test(t)) {
downstream.accept(t);
}
}
#Override
public boolean cancellationRequested() {
return !take || downstream.cancellationRequested();
}
This code is used by takeWhile to check for a given stream element t whether the predicate is fulfilled:
If so, it passes the element on to the downstream operation, in this case System.out::println.
If not, it sets take to false, so when it is asked next time whether the pipeline should be canceled (i.e. it is done), it returns true.
This covers the takeWhile operation. The other thing you need to know is that forEachOrdered leads to the terminal operation executing the method ReferencePipeline::forEachWithCancel:
#Override
final boolean forEachWithCancel(Spliterator<P_OUT> spliterator, Sink<P_OUT> sink) {
boolean cancelled;
do { } while (
!(cancelled = sink.cancellationRequested())
&& spliterator.tryAdvance(sink));
return cancelled;
}
All this does is:
check whether pipeline was canceled
if not, advance the sink by one element
stop if this was the last element
Looks promising, right?
Without flatMap
In the "good case" (without flatMap; your second example) forEachWithCancel directly operates on the WhileOp as sink and you can see how this plays out:
ReferencePipeline::forEachWithCancel does its loop:
WhileOps::accept is given each stream element
WhileOps::cancellationRequested is queried after each element
at some point "Sample4" fails the predicate and the stream is canceled
Yay!
With flatMap
In the "bad case" (with flatMap; your first example), forEachWithCancel operates on the flatMap operation, though, , which simply calls forEachRemaining on the ArraySpliterator for {"Sample3", "Sample4", "Sample5"}, which does this:
if ((a = array).length >= (hi = fence) &&
(i = index) >= 0 && i < (index = hi)) {
do { action.accept((T)a[i]); } while (++i < hi);
}
Ignoring all that hi and fence stuff, which is only used if the array processing is split for a parallel stream, this is a simple for loop, which passes each element to the takeWhile operation, but never checks whether it is cancelled. It will hence eagerly ply through all elements in that "substream" before stopping, likely even through the rest of the stream.
This is a bug no matter how I look at it - and thank you Holger for your comments. I did not want to put this answer in here (seriously!), but none of the answer clearly states that this is a bug.
People are saying that this has to with ordered/un-ordered, and this is not true as this will report true 3 times:
Stream<String[]> s1 = Arrays.stream(strArray);
System.out.println(s1.spliterator().hasCharacteristics(Spliterator.ORDERED));
Stream<String> s2 = Arrays.stream(strArray)
.flatMap(indStream -> Arrays.stream(indStream));
System.out.println(s2.spliterator().hasCharacteristics(Spliterator.ORDERED));
Stream<String> s3 = Arrays.stream(strArray)
.flatMap(indStream -> Arrays.stream(indStream))
.takeWhile(ele -> !ele.equalsIgnoreCase("Sample4"));
System.out.println(s3.spliterator().hasCharacteristics(Spliterator.ORDERED));
It's very interesting also that if you change it to:
String[][] strArray = {
{ "Sample1", "Sample2" },
{ "Sample3", "Sample5", "Sample4" }, // Sample4 is the last one here
{ "Sample7", "Sample8" }
};
then Sample7 and Sample8 will not be part of the output, otherwise they will. It seems that flatmap ignores a cancel flag that would be introduced by dropWhile.
If you look at the documentation for takeWhile:
if this stream is ordered, [returns] a stream consisting of the
longest prefix of elements taken from this stream that match the given
predicate.
if this stream is unordered, [returns] a stream consisting of a subset
of elements taken from this stream that match the given predicate.
Your stream is coincidentally ordered, but takeWhile doesn't know that it is. As such, it is returning 2nd condition - the subset. Your takeWhile is just acting like a filter.
If you add a call to sorted before takeWhile, you'll see the result you expect:
Arrays.stream(strArray)
.flatMap(indStream -> Arrays.stream(indStream))
.sorted()
.takeWhile(ele -> !ele.equalsIgnoreCase("Sample4"))
.forEach(ele -> System.out.println(ele));
The reason for that is the flatMap operation also being an intermediate operations with which (one of) the stateful short-circuiting intermediate operation takeWhile is used.
The behavior of flatMap as pointed by Holger in this answer is certainly a reference one shouldn't miss out to understand the unexpected output for such short-circuiting operations.
Your expected result can be achieved by splitting these two intermediate operations by introducing a terminal operation to deterministically use an ordered stream further and performing them for a sample as :
List<String> sampleList = Arrays.stream(strArray).flatMap(Arrays::stream).collect(Collectors.toList());
sampleList.stream().takeWhile(ele -> !ele.equalsIgnoreCase("Sample4"))
.forEach(System.out::println);
Also, there seems to be a related Bug#JDK-8075939 to trace this behavior already registered.
Edit: This can be tracked further at JDK-8193856 accepted as a bug.
This question already has answers here:
In Java, how do I efficiently and elegantly stream a tree node's descendants?
(5 answers)
Closed 6 years ago.
I was asked to retrieve every leaf node that is a descandant of a tree node. I quickly got the idea that I could do this job in one line!
public Set<TreeNode<E>> getLeaves() {
return getChildrenStream().flatMap(n -> n.getChildrenStream()).collect(toSet());
}
It was good at the first glance, but quickly it ran into a StackOverflowExcepetionif the tree depth reaches ~10, something that I can't accept. Later I developed a implementation without recursion and stream (but with my brain roasted), but I'm still wondering if there is a way to do recursive flatMaps with stream, because I found it impossible to do so without touching the stream internals. It'll need a new Op, like RecursiveOps to do that, or I will have to collect all results into a Set every step, and operate on that Set later:
Set<TreeNode<E>> prev = new HashSet<>();
prev.add(this);
while (!prev.isEmpty()) {
prev = prev.stream().flatMap(n -> n.getChildrenStream()).collect(toSet());
}
return prev;
Not good as it seems to be. Streams are meant to be a pipeline. Its result and intermediate results are not computed until a terminal op is added. The above approach appearently violates that principle. It's not as easy to parellelize as streams, too. Can I recursively flatMap without manually computing all intermediate results?
PS1: the TreeNode declaration:
public class TreeNode<E> {
// ...
/**
* Get a stream of children of the current node.
*
*/
public Stream<TreeNode<E>> getChildrenStream(){
// ...
}
public Set<TreeNode<E>> getLeaves() {
// main concern
}
}f
Not entirely sure if this would be something that you would be interested in:
public static Set<TreeNode<String>> getAllLeaves(TreeNode<String> treeNode) {
final Stream<TreeNode<String>> childrenStream = treeNode.getChildrenStream();
if (childrenStream == null) {
return new HashSet<>();
}
Set<TreeNode<String>> ownLeaves = treeNode.getLeaves();
ownLeaves.addAll(childrenStream.flatMap(stringTreeNode -> getAllLeaves(stringTreeNode).parallelStream())
.collect(Collectors.toSet()));
return ownLeaves;
}
Out of the box I see a few inconvenients with this method. It does return an empty Set for the last iteration and It's creating streams as it does the flatMap. However I believe this is what you are looking for, since you are thinking about using flatMap from where you want to get a joined Set created recursively where no stream was created in the first place. Btw, I've tried this with a -1000 level and it still works quite fast and with no problem.