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Remove Objects With Same Element From A List Java [duplicate]

In Java 8 how can I filter a collection using the Stream API by checking the distinctness of a property of each object?
For example I have a list of Person object and I want to remove people with the same name,
persons.stream().distinct();
Will use the default equality check for a Person object, so I need something like,
persons.stream().distinct(p -> p.getName());
Unfortunately the distinct() method has no such overload. Without modifying the equality check inside the Person class is it possible to do this succinctly?

Consider distinct to be a stateful filter. Here is a function that returns a predicate that maintains state about what it's seen previously, and that returns whether the given element was seen for the first time:
public static <T> Predicate<T> distinctByKey(Function<? super T, ?> keyExtractor) {
Set<Object> seen = ConcurrentHashMap.newKeySet();
return t -> seen.add(keyExtractor.apply(t));
}
Then you can write:
persons.stream().filter(distinctByKey(Person::getName))
Note that if the stream is ordered and is run in parallel, this will preserve an arbitrary element from among the duplicates, instead of the first one, as distinct() does.
(This is essentially the same as my answer to this question: Java Lambda Stream Distinct() on arbitrary key?)

An alternative would be to place the persons in a map using the name as a key:
persons.collect(Collectors.toMap(Person::getName, p -> p, (p, q) -> p)).values();
Note that the Person that is kept, in case of a duplicate name, will be the first encontered.

You can wrap the person objects into another class, that only compares the names of the persons. Afterward, you unwrap the wrapped objects to get a person stream again. The stream operations might look as follows:
persons.stream()
.map(Wrapper::new)
.distinct()
.map(Wrapper::unwrap)
...;
The class Wrapper might look as follows:
class Wrapper {
private final Person person;
public Wrapper(Person person) {
this.person = person;
}
public Person unwrap() {
return person;
}
public boolean equals(Object other) {
if (other instanceof Wrapper) {
return ((Wrapper) other).person.getName().equals(person.getName());
} else {
return false;
}
}
public int hashCode() {
return person.getName().hashCode();
}
}

Another solution, using Set. May not be the ideal solution, but it works
Set<String> set = new HashSet<>(persons.size());
persons.stream().filter(p -> set.add(p.getName())).collect(Collectors.toList());
Or if you can modify the original list, you can use removeIf method
persons.removeIf(p -> !set.add(p.getName()));

There's a simpler approach using a TreeSet with a custom comparator.
persons.stream()
.collect(Collectors.toCollection(
() -> new TreeSet<Person>((p1, p2) -> p1.getName().compareTo(p2.getName()))
));

We can also use RxJava (very powerful reactive extension library)
Observable.from(persons).distinct(Person::getName)
or
Observable.from(persons).distinct(p -> p.getName())

You can use groupingBy collector:
persons.collect(Collectors.groupingBy(p -> p.getName())).values().forEach(t -> System.out.println(t.get(0).getId()));
If you want to have another stream you can use this:
persons.collect(Collectors.groupingBy(p -> p.getName())).values().stream().map(l -> (l.get(0)));

You can use the distinct(HashingStrategy) method in Eclipse Collections.
List<Person> persons = ...;
MutableList<Person> distinct =
ListIterate.distinct(persons, HashingStrategies.fromFunction(Person::getName));
If you can refactor persons to implement an Eclipse Collections interface, you can call the method directly on the list.
MutableList<Person> persons = ...;
MutableList<Person> distinct =
persons.distinct(HashingStrategies.fromFunction(Person::getName));
HashingStrategy is simply a strategy interface that allows you to define custom implementations of equals and hashcode.
public interface HashingStrategy<E>
{
int computeHashCode(E object);
boolean equals(E object1, E object2);
}
Note: I am a committer for Eclipse Collections.

Similar approach which Saeed Zarinfam used but more Java 8 style:)
persons.collect(Collectors.groupingBy(p -> p.getName())).values().stream()
.map(plans -> plans.stream().findFirst().get())
.collect(toList());

You can use StreamEx library:
StreamEx.of(persons)
.distinct(Person::getName)
.toList()

I recommend using Vavr, if you can. With this library you can do the following:
io.vavr.collection.List.ofAll(persons)
.distinctBy(Person::getName)
.toJavaSet() // or any another Java 8 Collection

Extending Stuart Marks's answer, this can be done in a shorter way and without a concurrent map (if you don't need parallel streams):
public static <T> Predicate<T> distinctByKey(Function<? super T, ?> keyExtractor) {
final Set<Object> seen = new HashSet<>();
return t -> seen.add(keyExtractor.apply(t));
}
Then call:
persons.stream().filter(distinctByKey(p -> p.getName());

My approach to this is to group all the objects with same property together, then cut short the groups to size of 1 and then finally collect them as a List.
List<YourPersonClass> listWithDistinctPersons = persons.stream()
//operators to remove duplicates based on person name
.collect(Collectors.groupingBy(p -> p.getName()))
.values()
.stream()
//cut short the groups to size of 1
.flatMap(group -> group.stream().limit(1))
//collect distinct users as list
.collect(Collectors.toList());

Distinct objects list can be found using:
List distinctPersons = persons.stream()
.collect(Collectors.collectingAndThen(
Collectors.toCollection(() -> new TreeSet<>(Comparator.comparing(Person:: getName))),
ArrayList::new));

I made a generic version:
private <T, R> Collector<T, ?, Stream<T>> distinctByKey(Function<T, R> keyExtractor) {
return Collectors.collectingAndThen(
toMap(
keyExtractor,
t -> t,
(t1, t2) -> t1
),
(Map<R, T> map) -> map.values().stream()
);
}
An exemple:
Stream.of(new Person("Jean"),
new Person("Jean"),
new Person("Paul")
)
.filter(...)
.collect(distinctByKey(Person::getName)) // return a stream of Person with 2 elements, jean and Paul
.map(...)
.collect(toList())

Another library that supports this is jOOλ, and its Seq.distinct(Function<T,U>) method:
Seq.seq(persons).distinct(Person::getName).toList();
Under the hood, it does practically the same thing as the accepted answer, though.

Set<YourPropertyType> set = new HashSet<>();
list
.stream()
.filter(it -> set.add(it.getYourProperty()))
.forEach(it -> ...);

While the highest upvoted answer is absolutely best answer wrt Java 8, it is at the same time absolutely worst in terms of performance. If you really want a bad low performant application, then go ahead and use it. Simple requirement of extracting a unique set of Person Names shall be achieved by mere "For-Each" and a "Set".
Things get even worse if list is above size of 10.
Consider you have a collection of 20 Objects, like this:
public static final List<SimpleEvent> testList = Arrays.asList(
new SimpleEvent("Tom"), new SimpleEvent("Dick"),new SimpleEvent("Harry"),new SimpleEvent("Tom"),
new SimpleEvent("Dick"),new SimpleEvent("Huckle"),new SimpleEvent("Berry"),new SimpleEvent("Tom"),
new SimpleEvent("Dick"),new SimpleEvent("Moses"),new SimpleEvent("Chiku"),new SimpleEvent("Cherry"),
new SimpleEvent("Roses"),new SimpleEvent("Moses"),new SimpleEvent("Chiku"),new SimpleEvent("gotya"),
new SimpleEvent("Gotye"),new SimpleEvent("Nibble"),new SimpleEvent("Berry"),new SimpleEvent("Jibble"));
Where you object SimpleEvent looks like this:
public class SimpleEvent {
private String name;
private String type;
public SimpleEvent(String name) {
this.name = name;
this.type = "type_"+name;
}
public String getName() {
return name;
}
public void setName(String name) {
this.name = name;
}
public String getType() {
return type;
}
public void setType(String type) {
this.type = type;
}
}
And to test, you have JMH code like this,(Please note, im using the same distinctByKey Predicate mentioned in accepted answer) :
#Benchmark
#OutputTimeUnit(TimeUnit.SECONDS)
public void aStreamBasedUniqueSet(Blackhole blackhole) throws Exception{
Set<String> uniqueNames = testList
.stream()
.filter(distinctByKey(SimpleEvent::getName))
.map(SimpleEvent::getName)
.collect(Collectors.toSet());
blackhole.consume(uniqueNames);
}
#Benchmark
#OutputTimeUnit(TimeUnit.SECONDS)
public void aForEachBasedUniqueSet(Blackhole blackhole) throws Exception{
Set<String> uniqueNames = new HashSet<>();
for (SimpleEvent event : testList) {
uniqueNames.add(event.getName());
}
blackhole.consume(uniqueNames);
}
public static void main(String[] args) throws RunnerException {
Options opt = new OptionsBuilder()
.include(MyBenchmark.class.getSimpleName())
.forks(1)
.mode(Mode.Throughput)
.warmupBatchSize(3)
.warmupIterations(3)
.measurementIterations(3)
.build();
new Runner(opt).run();
}
Then you'll have Benchmark results like this:
Benchmark Mode Samples Score Score error Units
c.s.MyBenchmark.aForEachBasedUniqueSet thrpt 3 2635199.952 1663320.718 ops/s
c.s.MyBenchmark.aStreamBasedUniqueSet thrpt 3 729134.695 895825.697 ops/s
And as you can see, a simple For-Each is 3 times better in throughput and less in error score as compared to Java 8 Stream.
Higher the throughput, better the performance

I would like to improve Stuart Marks answer. What if the key is null, it will through NullPointerException. Here I ignore the null key by adding one more check as keyExtractor.apply(t)!=null.
public static <T> Predicate<T> distinctByKey(Function<? super T, ?> keyExtractor) {
Set<Object> seen = ConcurrentHashMap.newKeySet();
return t -> keyExtractor.apply(t)!=null && seen.add(keyExtractor.apply(t));
}

This works like a charm:
Grouping the data by unique key to form a map.
Returning the first object from every value of the map (There could be multiple person having same name).
persons.stream()
.collect(groupingBy(Person::getName))
.values()
.stream()
.flatMap(values -> values.stream().limit(1))
.collect(toList());

The easiest way to implement this is to jump on the sort feature as it already provides an optional Comparator which can be created using an element’s property. Then you have to filter duplicates out which can be done using a statefull Predicate which uses the fact that for a sorted stream all equal elements are adjacent:
Comparator<Person> c=Comparator.comparing(Person::getName);
stream.sorted(c).filter(new Predicate<Person>() {
Person previous;
public boolean test(Person p) {
if(previous!=null && c.compare(previous, p)==0)
return false;
previous=p;
return true;
}
})./* more stream operations here */;
Of course, a statefull Predicate is not thread-safe, however if that’s your need you can move this logic into a Collector and let the stream take care of the thread-safety when using your Collector. This depends on what you want to do with the stream of distinct elements which you didn’t tell us in your question.

There are lot of approaches, this one will also help - Simple, Clean and Clear
List<Employee> employees = new ArrayList<>();
employees.add(new Employee(11, "Ravi"));
employees.add(new Employee(12, "Stalin"));
employees.add(new Employee(23, "Anbu"));
employees.add(new Employee(24, "Yuvaraj"));
employees.add(new Employee(35, "Sena"));
employees.add(new Employee(36, "Antony"));
employees.add(new Employee(47, "Sena"));
employees.add(new Employee(48, "Ravi"));
List<Employee> empList = new ArrayList<>(employees.stream().collect(
Collectors.toMap(Employee::getName, obj -> obj,
(existingValue, newValue) -> existingValue))
.values());
empList.forEach(System.out::println);
// Collectors.toMap(
// Employee::getName, - key (the value by which you want to eliminate duplicate)
// obj -> obj, - value (entire employee object)
// (existingValue, newValue) -> existingValue) - to avoid illegalstateexception: duplicate key
Output - toString() overloaded
Employee{id=35, name='Sena'}
Employee{id=12, name='Stalin'}
Employee{id=11, name='Ravi'}
Employee{id=24, name='Yuvaraj'}
Employee{id=36, name='Antony'}
Employee{id=23, name='Anbu'}

Here is the example
public class PayRoll {
private int payRollId;
private int id;
private String name;
private String dept;
private int salary;
public PayRoll(int payRollId, int id, String name, String dept, int salary) {
super();
this.payRollId = payRollId;
this.id = id;
this.name = name;
this.dept = dept;
this.salary = salary;
}
}
import java.util.ArrayList;
import java.util.Comparator;
import java.util.List;
import java.util.Map;
import java.util.Optional;
import java.util.stream.Collector;
import java.util.stream.Collectors;
public class Prac {
public static void main(String[] args) {
int salary=70000;
PayRoll payRoll=new PayRoll(1311, 1, "A", "HR", salary);
PayRoll payRoll2=new PayRoll(1411, 2 , "B", "Technical", salary);
PayRoll payRoll3=new PayRoll(1511, 1, "C", "HR", salary);
PayRoll payRoll4=new PayRoll(1611, 1, "D", "Technical", salary);
PayRoll payRoll5=new PayRoll(711, 3,"E", "Technical", salary);
PayRoll payRoll6=new PayRoll(1811, 3, "F", "Technical", salary);
List<PayRoll>list=new ArrayList<PayRoll>();
list.add(payRoll);
list.add(payRoll2);
list.add(payRoll3);
list.add(payRoll4);
list.add(payRoll5);
list.add(payRoll6);
Map<Object, Optional<PayRoll>> k = list.stream().collect(Collectors.groupingBy(p->p.getId()+"|"+p.getDept(),Collectors.maxBy(Comparator.comparingInt(PayRoll::getPayRollId))));
k.entrySet().forEach(p->
{
if(p.getValue().isPresent())
{
System.out.println(p.getValue().get());
}
});
}
}
Output:
PayRoll [payRollId=1611, id=1, name=D, dept=Technical, salary=70000]
PayRoll [payRollId=1811, id=3, name=F, dept=Technical, salary=70000]
PayRoll [payRollId=1411, id=2, name=B, dept=Technical, salary=70000]
PayRoll [payRollId=1511, id=1, name=C, dept=HR, salary=70000]

Late to the party but I sometimes use this one-liner as an equivalent:
((Function<Value, Key>) Value::getKey).andThen(new HashSet<>()::add)::apply
The expression is a Predicate<Value> but since the map is inline, it works as a filter. This is of course less readable but sometimes it can be helpful to avoid the method.

Building on #josketres's answer, I created a generic utility method:
You could make this more Java 8-friendly by creating a Collector.
public static <T> Set<T> removeDuplicates(Collection<T> input, Comparator<T> comparer) {
return input.stream()
.collect(toCollection(() -> new TreeSet<>(comparer)));
}
#Test
public void removeDuplicatesWithDuplicates() {
ArrayList<C> input = new ArrayList<>();
Collections.addAll(input, new C(7), new C(42), new C(42));
Collection<C> result = removeDuplicates(input, (c1, c2) -> Integer.compare(c1.value, c2.value));
assertEquals(2, result.size());
assertTrue(result.stream().anyMatch(c -> c.value == 7));
assertTrue(result.stream().anyMatch(c -> c.value == 42));
}
#Test
public void removeDuplicatesWithoutDuplicates() {
ArrayList<C> input = new ArrayList<>();
Collections.addAll(input, new C(1), new C(2), new C(3));
Collection<C> result = removeDuplicates(input, (t1, t2) -> Integer.compare(t1.value, t2.value));
assertEquals(3, result.size());
assertTrue(result.stream().anyMatch(c -> c.value == 1));
assertTrue(result.stream().anyMatch(c -> c.value == 2));
assertTrue(result.stream().anyMatch(c -> c.value == 3));
}
private class C {
public final int value;
private C(int value) {
this.value = value;
}
}

Maybe will be useful for somebody. I had a little bit another requirement. Having list of objects A from 3rd party remove all which have same A.b field for same A.id (multiple A object with same A.id in list). Stream partition answer by Tagir Valeev inspired me to use custom Collector which returns Map<A.id, List<A>>. Simple flatMap will do the rest.
public static <T, K, K2> Collector<T, ?, Map<K, List<T>>> groupingDistinctBy(Function<T, K> keyFunction, Function<T, K2> distinctFunction) {
return groupingBy(keyFunction, Collector.of((Supplier<Map<K2, T>>) HashMap::new,
(map, error) -> map.putIfAbsent(distinctFunction.apply(error), error),
(left, right) -> {
left.putAll(right);
return left;
}, map -> new ArrayList<>(map.values()),
Collector.Characteristics.UNORDERED)); }

I had a situation, where I was suppose to get distinct elements from list based on 2 keys.
If you want distinct based on two keys or may composite key, try this
class Person{
int rollno;
String name;
}
List<Person> personList;
Function<Person, List<Object>> compositeKey = personList->
Arrays.<Object>asList(personList.getName(), personList.getRollno());
Map<Object, List<Person>> map = personList.stream().collect(Collectors.groupingBy(compositeKey, Collectors.toList()));
List<Object> duplicateEntrys = map.entrySet().stream()`enter code here`
.filter(settingMap ->
settingMap.getValue().size() > 1)
.collect(Collectors.toList());

A variation of the top answer that handles null:
public static <T, K> Predicate<T> distinctBy(final Function<? super T, K> getKey) {
val seen = ConcurrentHashMap.<Optional<K>>newKeySet();
return obj -> seen.add(Optional.ofNullable(getKey.apply(obj)));
}
In my tests:
assertEquals(
asList("a", "bb"),
Stream.of("a", "b", "bb", "aa").filter(distinctBy(String::length)).collect(toList()));
assertEquals(
asList(5, null, 2, 3),
Stream.of(5, null, 2, null, 3, 3, 2).filter(distinctBy(x -> x)).collect(toList()));
val maps = asList(
hashMapWith(0, 2),
hashMapWith(1, 2),
hashMapWith(2, null),
hashMapWith(3, 1),
hashMapWith(4, null),
hashMapWith(5, 2));
assertEquals(
asList(0, 2, 3),
maps.stream()
.filter(distinctBy(m -> m.get("val")))
.map(m -> m.get("i"))
.collect(toList()));

In my case I needed to control what was the previous element. I then created a stateful Predicate where I controled if the previous element was different from the current element, in that case I kept it.
public List<Log> fetchLogById(Long id) {
return this.findLogById(id).stream()
.filter(new LogPredicate())
.collect(Collectors.toList());
}
public class LogPredicate implements Predicate<Log> {
private Log previous;
public boolean test(Log atual) {
boolean isDifferent = previouws == null || verifyIfDifferentLog(current, previous);
if (isDifferent) {
previous = current;
}
return isDifferent;
}
private boolean verifyIfDifferentLog(Log current, Log previous) {
return !current.getId().equals(previous.getId());
}
}

My solution in this listing:
List<HolderEntry> result ....
List<HolderEntry> dto3s = new ArrayList<>(result.stream().collect(toMap(
HolderEntry::getId,
holder -> holder, //or Function.identity() if you want
(holder1, holder2) -> holder1
)).values());
In my situation i want to find distinct values and put their in List.

check if two lists of objects have the same value of an attribute

I have two lists of objects
localList and remotList, both lists have a consent attribute
I want to check the value of the consent attribute if the same for both lists
If Not, I want to remove all objects from localList don't have same consent value that exists in remotList and add all objects have same consent value that exist in remotList and not in localList
I implemented this solution but I want to improve it
Java Example
class Customer{
private Long id;
private String name;
private Integer consent;
public Customer(Long id, String name, Integer consent) {
this.id = id;
this.name = name;
this.consent = consent;
}
public Integer getConsent() {
return consent;
}
#java.lang.Override
public java.lang.String toString() {
return "Customer{" +
"id=" + id +
", name='" + name + '\'' +
", consent=" + consent +
'}';
}
}
public static void main(String[] args) {
List<Customer> localList = new ArrayList<>();
localList.add(new Customer(1L, "name1", 12));
localList.add(new Customer(2L, "name2", 13));
localList.add(new Customer(3L, "name3", 14));
localList.add(new Customer(4L, "name4", 15));
List<Customer> remoteList = new ArrayList<>();
remoteList.add(new Customer(10L, "name1", 12));
remoteList.add(new Customer(11L, "name2", 11));
remoteList.add(new Customer(12L, "name3", 14));
remoteList.add(new Customer(13L, "name4", 16));
Map<Integer, Customer> map = remoteList.stream()
.collect(Collectors.toMap(s -> s.getConsent() , s -> s));
Map<Integer, Customer> map2 = localList.stream()
.collect(Collectors.toMap(s -> s.getConsent() , s -> s));
List<Customer> remove = new ArrayList<>();
localList.forEach(e -> {
if(map.get(e.getConsent()) == null ) {
remoteList.add(e);
}
});
remoteList.forEach(e -> {
if(map2.get(e.getConsent()) == null ) {
remove.add(e);
}
});
remove.forEach(e -> remoteList.remove(e));
remoteList.forEach(System.out::println);
the remoteList
Customer{id=10, name='name1', consent=12}
Customer{id=11, name='name2', consent=11}
Customer{id=12, name='name3', consent=14}
Customer{id=13, name='name4', consent=16}
the localList
Customer{id=1, name='name1', consent=12}
Customer{id=2, name='name2', consent=13}
Customer{id=3, name='name3', consent=14}
Customer{id=4, name='name4', consent=15}
Result
Customer{id=10, name='name1', consent=12}
Customer{id=12, name='name3', consent=14}
Customer{id=2, name='name2', consent=13}
Customer{id=4, name='name4', consent=15}

For the first part, you can create a map for the remoteList mapping each customer by name. We are doing this for being able to search the remote customers faster.
Map<String, Customer> customerByName = remoteList.stream()
.collect(Collectors.toMap(Customer::getName, customer -> customer));
localList.removeIf(customer -> !Objects.equals(customer.getConsent(),
customerByName.get(customer.getName()).getConsent()));
Please note, the Customer class would require a getter for the name.
For the second part, we can also create a map for the localList as we've done previously. We iterate through the remoteList and filter each element which does not exist in the localList (at least I believe this is what you would want to accomplish).
Map<String, Customer> localCustomerByName = localList.stream()
.collect(Collectors.toMap(Customer::getName, customer -> customer));
localList.addAll(remoteList.stream()
.filter(customer -> !localCustomerByName.containsKey(customer.getName()))
.collect(Collectors.toList()));

Map<Integer, Customer> map = remoteList.stream()
.collect(Collectors.toMap(s -> s.getConsent() , s -> s));
List<Customer> hasDiffLastItem = localList.stream()
.filter(s -> !map.get(getConsent).getConsent().equals(s.getConsent()))
.collect(Collectors.toList());

Here is one way. I used a linked list since they are more efficient at deleting items.
first, create a comparator for a set. The tree set will take a comparator in place of an equals implementation.
then iterate over the remote list, removing items if they appear in the local set.
then iterate over the local list, removing items if they don't appear in the remote set.
Set<Customer> remoteSet = new TreeSet<>(comp);
Set<Customer> localSet = new TreeSet<>(comp);
remoteSet.addAll(remoteList);
localSet.addAll(localList);
Iterator<Customer> iter = localList.iterator();
while(iter.hasNext()) {
Customer s = iter.next();
if (remoteSet.contains(s)) {
iter.remove();
}
}
iter = remoteList.iterator();
while(iter.hasNext()) {
Customer s = iter.next();
if (!localSet.contains(s)) {
iter.remove();
}
}
You can combine the lists however you want but here are the results back to back.
localList.forEach(System.out::println);
remoteList.forEach(System.out::println);
prints
Customer{id=2, name='name2', consent=13}
Customer{id=4, name='name4', consent=15}
Customer{id=10, name='name1', consent=12}
Customer{id=12, name='name3', consent=14}
I tried different values using both your and my methods and the output was the same. I would recommend you check it yourself as I wasn't completely certain how you wanted this to work.

Merge list of Objects by property

I have been searching around different groupBy and stream threads but cannot find the answer to my problem. Basically I have this object:
public class Object {
string name;
string type;
}
And I return a list of these from the database. What I would like to then do is iterate through the list of objects and remove duplicate names and save a list of the second properties under one object, in a new object that looks like this:
public class NewObject {
String name;
List<String> types;
}

You can do it like this.
use groupingBy to create a map of name, List of type
use the entryset of the map to create the new object.
I added the appropriate constructors and getters in the classes.
List<OldObject> list = ...
List<NewObject> newList = list.stream()
.collect(Collectors.groupingBy(OldObject::getName,
Collectors.mapping(OldObject::getType,
Collectors.toList())))
.entrySet().stream()
.map(e -> new NewObject(e.getKey(), e.getValue()))
.toList();
}
class OldObject {
String name;
String type;
public String getName() {
return name;
}
public String getType() {
return type;
}
}
class NewObject {
String name;
List<String> types = new ArrayList<>();
public NewObject(String name, List<String> types) {
this.types = types;
this.name = name;
}
}
For your added enjoyment, I thought I would also offer the following:
create the map
conditionally create a new object if the name key is not present
in either case, add the type to the list instance of the NewObject instance in the map which is returned by the computeIfAbsent method.
When finished, just assign the values to your Collection.
Map<String, NewObject> map = new HashMap<>();
for (OldObject ob : list) {
map.computeIfAbsent(ob.getName(),
v -> new NewObject(ob.getName(),
new ArrayList<>()))
.add(ob.getType());
}
Collection<NewObject> newLista = map.values();
Caveats:
values returns a Collection, not a list so you would need to use that or pass the Collection to a list constructor of some sort (e.g. ArrayList).
the requires the addition of a add method in the NewObject class.
you could also have a getter that returns the type list directly and do.
map.computeIfAbsent(ob.getName(),
v -> new NewObject(ob.getName(),
new ArrayList<>()))
.getTypeList().add(ob.getType());
Check out these additions to the Map interface

I understand you don't want to remove duplicates but actually merge them.
I replaced your Object class name with OldObject to avoid confusion with the actual Java Object class.
Collecting to Map<String, List<String>> and then converting to List<NewObject>
You could write your own Collector (see later in the answer), but the easiest way of writing what you need would be to use the current groupingBy and toList Collectors and then using the resulting Map and create your newObject instance based on it to then again collect to a new List:
oldObjectList.stream().collect(Collectors.groupingBy(OldObject::getName, Collectors.mapping(OldObject::getType, Collectors.toList())))
.entrySet().stream()
// Assuming a NewObject constructor that receives a String name and a List<String> types
.map(e -> new NewObject(e.getKey(), e.getValue()))
.collect(Collectors.toList());
Custom Collectors
If you are interested in learning how to make your own Collector, I made an example using a custom Collector as well:
oldObjectList.stream().collect(Collector.of(
// Supplier
() -> new ConcurrentHashMap<String, NewObject>(),
// Accumulator
(map, oldObject) -> {
// Assuming a NewObject constructor that gets a name and creates a new empty List as types.
map.computeIfAbsent(oldObject.getName(), name -> new NewObject(name)).getTypes().add(oldObject.getType());
},
// Combiner
(map1, map2) -> {
map2.forEach((k, v) -> map1.merge(k, v, (v1, v2) -> {
v1.getTypes().addAll(v2.getTypes());
return v1;
}));
return map1;
},
// Finisher
map -> new ArrayList<>(map.values())
));
You can even combine groupingBy and a custom Collector as a merge function:
new ArrayList<>(oldObjectList.stream().collect(Collectors.groupingBy(OldObject::getName, Collector.of(
// Supplier
// Assuming a NewObject constructor with no arguments that creates a new empty List as types.
NewObject::new,
// Accumulator
(newObject, oldObject) -> {
newObject.setName(oldObject.getName());
newObject.getTypes().add(oldObject.getType());
},
// Combiner
(newObject1, newObject2) -> {
newObject1.getTypes().addAll(newObject2.getTypes());
return newObject1;
}
))).values());

It may be possible to use Collectors.toMap to create NewObject instances immediately and append types as necessary within the merge function.
Assuming that there NewObject has custom constructor and overridden toString method:
class NewObject {
String name;
List<String> types = new ArrayList<>();
public NewObject(String name, String type) {
this.name = name;
this.types.add(type);
}
#Override
public String toString() {
return "{ name: " + name + "; types: " + types + "}";
}
}
and that there are helper methods to create an instance of NewObject from OldObject and merge types of two NewObject instances:
// MyClass
public static NewObject createNewObject(OldObject oo) {
return new NewObject(oo.getName(), oo.getType());
}
public static NewObject mergeTypes(NewObject no1, NewObject no2) {
no1.getTypes().addAll(no2.getTypes());
return no1;
}
The transformation may be implemented as follows:
List<OldObject> input = Arrays.asList(
new OldObject("n1", "type1"), new OldObject("n1", "type2"),
new OldObject("n2", "type1"), new OldObject("n3", "type2"),
new OldObject("n1", "type3"), new OldObject("n2", "type2")
);
List<NewObject> result = new ArrayList<>(
input
.stream()
.collect(Collectors.toMap(
OldObject::getName,
MyClass::createNewObject,
MyClass::mergeTypes,
LinkedHashMap::new // keep insertion order
))
.values());
result.forEach(System.out::println);
Output:
{ name: n1; types: [type1, type2, type3]}
{ name: n2; types: [type1, type2]}
{ name: n3; types: [type2]}

Filter only parameters that are present in the request

There are lots of articles that are about Java 8 lambda operations however I couldn't find what I need until now. I tried to convert them to my approach unfortunately I couldn't succeed
Imagine that you have request that comes in POJO such as ;
public class DummyRequest {
private String name;
private String surname;
private String country;
public String getName() {
return name;
}
public void setName(String name) {
this.name = name;
}
public String getSurname() {
return surname;
}
public void setSurname(String surname) {
this.surname = surname;
}
public String getCountry() {
return country;
}
public void setCountry(String country) {
this.country= country;
}
}
During REST/SOAP request surname variable will be assigned as null.
List<Person> persons = Arrays.asList(
new Person("maria", "gambert", "italy"),
new Person("jack", "johson", "usa"),
new Person("johnson", "jack", "usa"),
new Person("kate", "julia", "spain"),
new Person("jack","bob","uk");
DummyRequest dr = new DummyRequest();
dr.setName("jack");
dr.setCountry("usa");
If I knew in advance that the surname field would be null, I could manage to filter the list like this, ignoring that field:
List<Person> result4 = persons.stream().
filter(x -> dummyRequest.getName().equals(x.getName())).
filter( x-> dummyRequest.getCountry().equals(x.getCountry())).
collect(Collectors.toList());
However I don't know which fields will be null and which will not. How could I instead filter my data according to non-null request parameters only?

If you want to only apply the filter for which the dummyRequest contains a non-null value, you would have to dynamically build your stream for the most efficient solution.
This could easily be done by implementing a helper method that conditionally applies a filter:
public static <T, V> Stream<T> filterIfNotNull(Stream<T> stream, V filterValue, Function<T, V> property) {
if (filterValue == null) {
return stream;
}
return stream.filter(t -> filterValue.equals(property.apply(t)));
}
(in your example T would always be Person and V would always be String, but this generic version allows more reusability without additional complexity at the call site)
Then the stream/collect can be implemented like this:
Stream<Person> personStream = persons.stream();
personStream = filterIfNotNull(personStream, dummyRequest.getName(), Person::getName);
personStream = filterIfNotNull(personStream, dummyRequest.getSurname(), Person::getSurname);
personStream = filterIfNotNull(personStream, dummyRequest.getCountry(), Person::getCountry);
List<Person> result4 = personStream.collect(Collectors.toList());
This technique guarantees that the null-check on the request's properties is only applied once.

I would define a static method for that, since you are duplicating the code so many times:
private static boolean nullableOrEqual(String left, String right) {
return left == null || left.equals(right);
}
And then the usage would be:
List<Person> result = persons.stream()
.filter(x -> nullableOrEqual(dr.getSurname(), x.getSurname()))
.filter(x -> nullableOrEqual(dr.getCountry(), x.getCountry()))
.filter(x -> nullableOrEqual(dr.getName(), x.getName()))
.collect(Collectors.toList());

If you want to filter only by the non-null properties of dummyRequest, you can simply add a null check to each Predicate:
List<Person> result4 =
persons.stream()
.filter(x -> dummyRequest.getSurname() == null || dummyRequest.getSurname().equals(x.getSurname()))
.filter(x -> dummyRequest.getName() == null || dummyRequest.getName().equals(x.getName()))
.filter(x -> dummyRequest.getCountry() == null || dummyRequest.getCountry().equals(x.getCountry()))
.collect(Collectors.toList());

You could create a checkNonNullProperties helper method that returns a Predicate<Person> that only checks for equality of non-null properties of your DummyRequest instance. You could use it as follows:
Predicate<Person> condition = checkNonNullProperties(
Arrays.asList(
dr.getCountry(),
dr.getName(),
dr.getSurname()),
Arrays.asList(
Person::getCountry,
Person::getName,
Person::getSurname));
List<Person> result = people.stream()
.filter(condition)
.collect(Collectors.toList());
The helper method:
private static <T> Predicate<T> checkNonNullProperties(
List<?> values,
List<Function<T, ?>> extractors) {
return IntStream.range(0, values.size()).mapToObj(i ->
(Predicate<T>) t -> {
Object value = values.get(i);
Object property = extractors.get(i).apply(t);
return value == null || value.equals(property);
})
.reduce(t -> true, Predicate::and);
}
The checkNonNullProperties method receives a list of values to check for equality and a list of functions that will extract the properties from the argument of the returned predicate. The extracted properties will be checked for equality against their corresponding values only for those values that are non-null.
I'm using an IntStream to drive iteration over both lists. In the mapToObj method I'm mapping the stream's int value to a predicate that returns true when the provided value is null or when it's equal to the extracted property.
In the end, these predicates are reduced to a final predicate via the Predicate::and operator. In the reduce call, I'm providing the identity predicate for the AND operator, which is t -> true (always returns true).

Find the most common attribute value from a List of objects using Stream

I have two classes that are structured like this:
public class Company {
private List<Person> person;
...
public List<Person> getPerson() {
return person;
}
...
}
public class Person {
private String tag;
...
public String getTag() {
return tag;
}
...
}
Basically the Company class has a List of Person objects, and each Person object can get a Tag value.
If I get the List of the Person objects, is there a way to use Stream from Java 8 to find the one Tag value that is the most common among all the Person objects (in case of a tie, maybe just a random of the most common)?
String mostCommonTag;
if(!company.getPerson().isEmpty) {
mostCommonTag = company.getPerson().stream() //How to do this in Stream?
}

String mostCommonTag = getPerson().stream()
// filter some person without a tag out
.filter(it -> Objects.nonNull(it.getTag()))
// summarize tags
.collect(Collectors.groupingBy(Person::getTag, Collectors.counting()))
// fetch the max entry
.entrySet().stream().max(Map.Entry.comparingByValue())
// map to tag
.map(Map.Entry::getKey).orElse(null);
AND the getTag method appeared twice, you can simplify the code as further:
String mostCommonTag = getPerson().stream()
// map person to tag & filter null tag out
.map(Person::getTag).filter(Objects::nonNull)
// summarize tags
.collect(Collectors.groupingBy(Function.identity(), Collectors.counting()))
// fetch the max entry
.entrySet().stream().max(Map.Entry.comparingByValue())
// map to tag
.map(Map.Entry::getKey).orElse(null);

You could collect the counts to a Map, then get the key with the highest value
List<String> foo = Arrays.asList("a","b","c","d","e","e","e","f","f","f","g");
Map<String, Long> f = foo
.stream()
.collect(Collectors.groupingBy(v -> v, Collectors.counting()));
String maxOccurence =
Collections.max(f.entrySet(), Comparator.comparing(Map.Entry::getValue)).getKey();
System.out.println(maxOccurence);

This should work for you:
private void run() {
List<Person> list = Arrays.asList(() -> "foo", () -> "foo", () -> "foo",
() -> "bar", () -> "bar");
Map<String, Long> commonness = list.stream()
.collect(Collectors.groupingBy(Person::getTag, Collectors.counting()));
Optional<String> mostCommon = commonness.entrySet().stream()
.max(Map.Entry.comparingByValue())
.map(Map.Entry::getKey);
System.out.println(mostCommon.orElse("no elements in list"));
}
public interface Person {
String getTag();
}
The commonness map contains the information which tag was found how often. The variable mostCommon contains the tag that was found most often. Also, mostCommon is empty, if the original list was empty.

If you are open to using a third-party library, you can use Collectors2 from Eclipse Collections with a Java 8 Stream to create a Bag and request the topOccurrences, which will return a MutableList of ObjectIntPair which is the tag value and the count of the number of occurrences.
MutableList<ObjectIntPair<String>> topOccurrences = company.getPerson()
.stream()
.map(Person::getTag)
.collect(Collectors2.toBag())
.topOccurrences(1);
String mostCommonTag = topOccurrences.getFirst().getOne();
In the case of a tie, the MutableList will have more than one result.
Note: I am a committer for Eclipse Collections.

This is helpful for you,
Map<String, Long> count = persons.stream().collect(
Collectors.groupingBy(Person::getTag, Collectors.counting()));
Optional<Entry<String, Long>> maxValue = count .entrySet()
.stream().max((entry1, entry2) -> entry1.getValue() > entry2.getValue() ? 1 : -1).get().getKey();
maxValue.get().getValue();

One More solution by abacus-common
// Comparing the solution by jdk stream,
// there is no "collect(Collectors.groupingBy(Person::getTag, Collectors.counting())).entrySet().stream"
Stream.of(company.getPerson()).map(Person::getTag).skipNull() //
.groupBy(Fn.identity(), Collectors.counting()) //
.max(Comparators.comparingByValue()).map(e -> e.getKey()).orNull();
// Or by multiset
Stream.of(company.getPerson()).map(Person::getTag).skipNull() //
.toMultiset().maxOccurrences().map(e -> e.getKey()).orNull();