The groupingBy collector of Stream in Java 8 supports multiple grouping methods. ① Group by field: For example, group by city, use Collectors.groupingBy(Person::getCity); ② Multi-level grouping: For example, group by city first and then by age, use nested groupingBy; ③ Customize downstream operations: For example, use Collectors.counting() to count the quantity, use Collectors.averagingInt() to calculate the average; ④ Merge data after grouping: For example, if the names are spliced ??into strings, use Collectors.mapping() to cooperate with Collectors.joining().
In Java 8, Stream
's collect()
method combined with Collectors.groupingBy()
can easily group the collection data. It is similar to GROUP BY
in SQL, but is more flexible and suitable for handling complex data structures.

Basic usage: Group by field
The easiest way to use it is to group by a certain attribute. For example, you have a Person
class with name
and city
fields. You want to group people by city:
Map<String, List<Person>> peopleByCity = people.stream() .collect(Collectors.groupingBy(Person::getCity));
This will return a Map
, the key is the city name and the value is the Person
list of the city.

Note: If the grouped field may be null, an exception will be thrown. You need to make sure the fields are not empty or use a custom classifier to handle.
Multi-level grouping: nested grouping
Sometimes we want to group by multiple conditions, such as by city first, and then by age:

Map<String, Map<Integer, List<Person>>> grouped = people.stream() .collect(Collectors.groupingBy(Person::getCity, Collectors.groupingBy(Person::getAge)));
This way of writing is called "multi-level grouping", and the result is a nested Map
where you can continue to add hierarchies as needed.
Custom downstream operations: not just List
By default, groupingBy
returns a list of elements under each group. But many times we do not need complete objects, but rather statistical information, such as quantity, sum, average, etc.:
// Count the number of people in each city Map<String, Long> countByCity = people.stream() .collect(Collectors.groupingBy(Person::getCity, Collectors.counting())); // Average age for each city Map<String, Double> avgAgeByCity = people.stream() .collect(Collectors.groupingBy(Person::getCity, Collectors.averagingInt(Person::getAge)));
Common downstream collectors include:
-
counting()
: counting the number -
summingInt()
/summingDouble()
: sum -
averagingInt()
: Find the average -
mapping()
: Map into another type and then aggregate
Merge data after grouping: use toList/toSet/joining, etc.
If you want to turn the grouped data into strings or other formats, you can use Collectors.mapping()
or Collectors.joining()
:
// The names of each city are spliced ??into string Map<String, String> namesByCity = people.stream() .collect(Collectors.groupingBy(Person::getCity, Collectors.mapping(Person::getName, Collectors.joining(", "))));
The output result is similar to:
{ Beijing=[Zhang San, Li Si], Shanghai=[Wang Wu] }
Basically these common uses. Although groupingBy
in Java Stream looks simple, it is very powerful after combining different collectors. The key is to understand the concept of "downstream collectors". By mastering this, you can flexibly respond to various data grouping needs.
The above is the detailed content of How to use Java Stream collect() with groupingBy?. For more information, please follow other related articles on the PHP Chinese website!

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