In Java 8, there is Stream.collect which allows aggregations on collections. In Kotlin, this does not exist in the same way, other than maybe as a collection of extension functions in the stdlib. But it isn't clear what the equivalences are for different use cases.
For example, at the top of the JavaDoc for Collectors are examples written for Java 8, and when porting them to Kolin you can't use the Java 8 classes when on a different JDK version, so likely they should be written differently.
In terms of resources online showing examples of Kotlin collections, they are typically trivial and don't really compare to the same use cases. What are good examples that really match the cases such as documented for Java 8 Stream.collect? The list there is:
With details in the JavaDoc linked above.
Note: this question is intentionally written and answered by the author (Self-Answered Questions), so that the idiomatic answers to commonly asked Kotlin topics are present in SO. Also to clarify some really old answers written for alphas of Kotlin that are not accurate for current-day Kotlin.
There are functions in the Kotlin stdlib for average, count, distinct, filtering, finding, grouping, joining, mapping, min, max, partitioning, slicing, sorting, summing, to/from arrays, to/from lists, to/from maps, union, co-iteration, all the functional paradigms, and more. So you can use those to create little 1-liners and there is no need to use the more complicated syntax of Java 8.
I think the only thing missing from the built-in Java 8 Collectors class is summarization (but in another answer to this question is a simple solution).
One thing missing from both is batching by count, which is seen in another Stack Overflow answer and has a simple answer as well. Another interesting case is this one also from Stack Overflow: Idiomatic way to split sequence into three lists using Kotlin. And if you want to create something like Stream.collect for another purpose, see Custom Stream.collect in Kotlin
EDIT 2017-08-11: Chunked/windowed collection operations were added in Kotlin 1.2 M2, see https://blog.jetbrains.com/kotlin/2017/08/kotlin-1-2-m2-is-out/
It is always good to explore the API Reference for kotlin.collections as a whole before creating new functions that might already exist there.
Here are some conversions from Java 8 Stream.collect examples to the equivalent in Kotlin:
Accumulate names into a List
// Java:
List<String> list = people.stream().map(Person::getName).collect(Collectors.toList());
// Kotlin:
val list = people.map { it.name } // toList() not needed
Convert elements to strings and concatenate them, separated by commas
// Java:
String joined = things.stream()
.map(Object::toString)
.collect(Collectors.joining(", "));
// Kotlin:
val joined = things.joinToString(", ")
Compute sum of salaries of employee
// Java:
int total = employees.stream()
.collect(Collectors.summingInt(Employee::getSalary)));
// Kotlin:
val total = employees.sumBy { it.salary }
Group employees by department
// Java:
Map<Department, List<Employee>> byDept
= employees.stream()
.collect(Collectors.groupingBy(Employee::getDepartment));
// Kotlin:
val byDept = employees.groupBy { it.department }
Compute sum of salaries by department
// Java:
Map<Department, Integer> totalByDept
= employees.stream()
.collect(Collectors.groupingBy(Employee::getDepartment,
Collectors.summingInt(Employee::getSalary)));
// Kotlin:
val totalByDept = employees.groupBy { it.dept }.mapValues { it.value.sumBy { it.salary }}
Partition students into passing and failing
// Java:
Map<Boolean, List<Student>> passingFailing =
students.stream()
.collect(Collectors.partitioningBy(s -> s.getGrade() >= PASS_THRESHOLD));
// Kotlin:
val passingFailing = students.partition { it.grade >= PASS_THRESHOLD }
Names of male members
// Java:
List<String> namesOfMaleMembers = roster
.stream()
.filter(p -> p.getGender() == Person.Sex.MALE)
.map(p -> p.getName())
.collect(Collectors.toList());
// Kotlin:
val namesOfMaleMembers = roster.filter { it.gender == Person.Sex.MALE }.map { it.name }
Group names of members in roster by gender
// Java:
Map<Person.Sex, List<String>> namesByGender =
roster.stream().collect(
Collectors.groupingBy(
Person::getGender,
Collectors.mapping(
Person::getName,
Collectors.toList())));
// Kotlin:
val namesByGender = roster.groupBy { it.gender }.mapValues { it.value.map { it.name } }
Filter a list to another list
// Java:
List<String> filtered = items.stream()
.filter( item -> item.startsWith("o") )
.collect(Collectors.toList());
// Kotlin:
val filtered = items.filter { it.startsWith('o') }
Finding shortest string a list
// Java:
String shortest = items.stream()
.min(Comparator.comparing(item -> item.length()))
.get();
// Kotlin:
val shortest = items.minBy { it.length }
Counting items in a list after filter is applied
// Java:
long count = items.stream().filter( item -> item.startsWith("t")).count();
// Kotlin:
val count = items.filter { it.startsWith('t') }.size
// but better to not filter, but count with a predicate
val count = items.count { it.startsWith('t') }
and on it goes... In all cases, no special fold, reduce, or other functionality was required to mimic Stream.collect. If you have further use cases, add them in comments and we can see!
If you want to lazy process a chain, you can convert to a Sequence using asSequence() before the chain. At the end of the chain of functions, you usually end up with a Sequence as well. Then you can use toList(), toSet(), toMap() or some other function to materialize the Sequence at the end.
// switch to and from lazy
val someList = items.asSequence().filter { ... }.take(10).map { ... }.toList()
// switch to lazy, but sorted() brings us out again at the end
val someList = items.asSequence().filter { ... }.take(10).map { ... }.sorted()
You will notice the Kotlin examples do not specify the types. This is because Kotlin has full type inference and is completely type safe at compile time. More so than Java because it also has nullable types and can help prevent the dreaded NPE. So this in Kotlin:
val someList = people.filter { it.age <= 30 }.map { it.name }
is the same as:
val someList: List<String> = people.filter { it.age <= 30 }.map { it.name }
Because Kotlin knows what people is, and that people.age is Int therefore the filter expression only allows comparison to an Int, and that people.name is a String therefore the map step produces a List<String> (readonly List of String).
Now, if people were possibly null, as-in a List<People>? then:
val someList = people?.filter { it.age <= 30 }?.map { it.name }
Returns a List<String>? that would need to be null checked (or use one of the other Kotlin operators for nullable values, see this Kotlin idiomatic way to deal with nullable values and also Idiomatic way of handling nullable or empty list in Kotlin)