Java 8: how to perform stream reduce and collection operations

Java 8: how to perform stream reduce and collection operations

The Java 8 JDK contains many aggregate operations such as average, sum, minimum, maximum, and count. The aggregation result of a stream is returned. These aggregate operations are called aggregate operations. In addition to the aggregation operation that returns a single value, JDK also returns a collection instance for many aggregation operations. Many reduce operations perform specific tasks, such as averaging or grouping by category.

General aggregation operations provided by JDK: Stream. reduce, Stream. collection

Note: In this document, function operations are translated as aggregation operations because function operations are usually used for aggregation statistics.

Differences between the two:

Stream. reduce. Common methods include average, sum, min, max, and count. Return a single result value. Each time a reduce operation processes an element, a new value is always created.

Stream. collection is different from stream. reduce. Stream. collect modifies the existing value, instead of creating a new value for each element processed.

 
 

  
  
Package lambda;
  
  

  
  
Import java. util. Arrays;
  
  
Import java. util. List;
  
  
Import java. util. Map;
  
  
Import java. util. stream. Collectors;
  
  

  
  
Public class LambdaMapReduce {
  
  
Private static List <User> users = Arrays. asList (
  
  
New User (1, "Zhang San", 12, User. Sex. MALE ),
  
  
New User (2, "Li Si", 21, User. Sex. FEMALE ),
  
  
New User (3, "Wang Wu", 32, User. Sex. MALE ),
  
  
New User (4, "Zhao six", 32, User. Sex. FEMALE ));
  
  

  
  
Public static void main (String [] args ){
  
  
Performanceavg ();
  
  
ReduceSum ();
  
  

  
  

  
  
// Unlike the stream. reduce method, Stream. collect modifies the existing value, instead of creating a new value for each element processed.
  
  
// Obtain the average age of all male users
  
  
Averager averageCollect = users. parallelStream ()
  
  
. Filter (p-> p. getGender () = User. Sex. MALE)
  
  
. Map (User: getAge)
  
  
. Collect (Averager: new, Averager: accept, Averager: combine );
  
  

  
  
System. out. println ("Average age of male members :"
  
  
+ AverageCollect. average ());
  
  

  
  
// Obtain the list of users older than 12
  
  
List <User> list = users. parallelStream (). filter (p-> p. age> 12)
  
  
. Collect (Collectors. toList ());
  
  
System. out. println (list );
  
  

  
  
// Count the number of users by gender
  
  
Map <User. Sex, Integer> map = users. parallelStream (). collect (
  
  
Collectors. groupingBy (User: getGender,
  
  
Collectors. summingInt (p-> 1 )));
  
  
System. out. println (map );
  
  

  
  
// Obtain the user name by gender
  
  
Map <User. Sex, List <String> map2 = users. stream ()
  
  
. Collect (
  
  
Collectors. groupingBy (
  
  
User: getGender,
  
  
Collectors. mapping (User: getName,
  
  
Collectors. toList ())));
  
  
System. out. println (map2 );
  
  

  
  
// Calculate the total age by gender
  
  
Map <User. Sex, Integer> map3 = users. stream (). collect (
  
  
Collectors. groupingBy (User: getGender,
  
  
Collectors. cing (0, User: getAge, Integer: sum )));
  
  

  
  
System. out. println (map3 );
  
  

  
  
// Calculate the average age by gender
  
  
Map <User. Sex, Double> map4 = users. stream (). collect (
  
  
Collectors. groupingBy (User: getGender,
  
  
Collectors. averagingInt (User: getAge )));
  
  
System. out. println (map4 );
  
  

  
  
}
  
  

  
  
// Note: each time a reduce operation processes an element, a new value is always created,
  
  
// Stream. reduce is applicable when a single result value is returned.
  
  
// Obtain the average age of all users
  
  
Private static void performanceavg (){
  
  
// The pipeline of mapToInt can be followed by average, max, min, count, sum
  
  
Double avg = users. parallelStream (). mapToInt (User: getAge)
  
  
. Average (). getAsDouble ();
  
  

  
  
System. out. println ("performanceavg User Age:" + avg );
  
  
}
  
  

  
  
// Obtain the total age of all users
  
  
Private static void reduceSum (){
  
  
Double sum = users. parallelStream (). mapToInt (User: getAge)
  
  
. Reduce (0, (x, y)-> x + y); // can be abbreviated as. sum ()
  
  

  
  
System. out. println ("reduceSum User Age:" + sum );
  
  
}
  
  
}
 
 

Iii. References

Http://docs.oracle.com/javase/tutorial/collections/streams/reduction.html

Link: http://my.oschina.net/cloudcoder/blog/215169