java8自定义收集器
案例：接收参数int n，并将前n个自然数分为质数和非质数。
第一种方式自定义收集器第一步：实现收集器接口，重写收集器方法，以及定义业务逻辑方法
package com.java8.CustomCollector;
import java.util.*;
import java.util.function.*;
import java.util.stream.Collector;
public class PrimeNumbersCollector implements Collector<Integer,Map<Boolean,List<Integer>>,Map<Boolean,List<Integer>>>{
/**
* 作用：创建结果容器
* @return
*/
@Override
public Supplier<Map<Boolean,List<Integer>>> supplier() {
return () -> new HashMap<Boolean,List<Integer>>(){{
put(true,new ArrayList<>());
put(false,new ArrayList<>());
}};
}
/**
* 作用：将元素添加到结果容器
* @return
*/
@Override
public BiConsumer<Map<Boolean,List<Integer>>,Integer> accumulator() {
return (Map<Boolean,List<Integer>> acc,Integer candidate) ->{
acc.get(isPrime(acc.get(true)
,candidate)
).add(candidate);
};
}
/**
* 对结果容器进行转换
* @return
*/
@Override
public BinaryOperator<Map<Boolean,List<Integer>>> combiner() {
return (Map<Boolean,List<Integer>> map1,
Map<Boolean,List<Integer>> map2) ->{
map1.get(true).addAll(map2.get(true));
map1.get(false).addAll(map2.get(false));
return map1;
};
}
/**
* 作用:当为并行流时，合并两个或多个结果容器
* @return
*/
@Override
public Function<Map<Boolean,List<Integer>>,Map<Boolean,List<Integer>>> finisher() {
return Function.identity();
}
/**
* 作用：返回一个不可变的 Characteristics 集合
* @return
*/
@Override
public Set<Characteristics> characteristics() {
return Collections.unmodifiableSet(EnumSet.of(Collector.Characteristics.IDENTITY_FINISH));
}
/**
* 行为参数化方法，
* @param list
* @param p
* @param <A>
* @return
*/
public static <A> List<A> takeWhile(List<A> list, Predicate<A> p){
int i = 0;
for(A item : list){
if(!p.test(item)){
return list.subList(0,i);
}
i++;
}
return list;
}
/**
* 主要判断逻辑（）判断是否是质数
* @param primes
* @param candidate
* @return
*/
public static boolean isPrime(List<Integer> primes,int candidate){
int candidateRoot = (int)Math.sqrt((double)candidate);
return takeWhile(primes,i -> i <= candidateRoot).stream().noneMatch(p ->candidate % p == 0);
}
}
第二步：应用方法与java8内置收集归约函数做对比
package com.java8.CustomCollector;
import java.util.List;
import java.util.Map;
import java.util.stream.IntStream;
import static java.util.stream.Collectors.partitioningBy;
public class Test {
public static void main(String[] arg){
long fastest = Long.MAX_VALUE;
for(int i = 0; i < 10 ;i++){
long start = System.nanoTime();
partitionPrimes(1000000);
long duration = (System.nanoTime() - start) / 1000000;
if (duration < fastest ) fastest = duration;
}
System.out.println("Fastest execution done in " + fastest +" msecs");
for(int i = 0; i < 10 ;i++){
long start = System.nanoTime();
partitionPaimesWithCustomCollector(1000000);
long duration = (System.nanoTime() - start) / 1000000;
if (duration < fastest ) fastest = duration;
}
System.out.println("CustomCollector Fastest execution done in " + fastest +" msecs");
}
/**
* 自定义收集器调用
* @param n
* @return
*/
public static Map<Boolean,List<Integer>> partitionPaimesWithCustomCollector(int n){
return IntStream.rangeClosed(2,n).boxed().collect(new PrimeNumbersCollector());
}
/**
*采用系统分区函数
* @param n
* @return
*/
public static Map<Boolean,List<Integer>> partitionPrimes(int n){
return IntStream.rangeClosed(2,n).
boxed().
collect(partitioningBy(candidate -> isPrime(candidate)));
}
/**
*判断是否为质数
* @param candidate
* @return
*/
public static boolean isPrime(int candidate){
int candidateRoot = (int)Math.sqrt((double)candidate);
return IntStream.rangeClosed(2,candidateRoot).boxed().noneMatch(i -> candidate % i == 0);
}
}
函数输出（提高了55%） Fastest execution done in 865 msecs
CustomCollector Fastest execution done in 382 msecs
第二种方式实现自定义收集器把实现核心逻辑的三个函数传给collect方法的重载版本来获得同样的结果。
package com.java8.CustomCollector;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.function.Predicate;
import java.util.stream.IntStream;
import static java.util.stream.Collectors.partitioningBy;
public class Test {
public static void main(String[] arg){
long fastest = Long.MAX_VALUE;
for(int i = 0; i < 10 ;i++){
long start = System.nanoTime();
partitionPaimesWithCustomCollector(1000000);
long duration = (System.nanoTime() - start) / 1000000;
if (duration < fastest ) fastest = duration;
}
System.out.println("CustomCollector Fastest execution done in " + fastest +" msecs");
}
/**
* 自定义收集器调用
* @param n
* @return
*/
public static Map<Boolean,List<Integer>> partitionPaimesWithCustomCollector(int n){
return IntStream.rangeClosed(2,n).boxed().collect(
()->new HashMap<Boolean,List<Integer>>(){{
put(true,new ArrayList<>());
put(false,new ArrayList<>());
}},
(acc,candidate) ->{
acc.get(isPrime(acc.get(true)
,candidate)
).add(candidate);
},
(map1,map2) ->{
map1.get(true).addAll(map2.get(true));
map1.get(false).addAll(map2.get(false));
});
}
public static <A> List<A> takeWhile(List<A> list, Predicate<A> p){
int i = 0;
for(A item : list){
if(!p.test(item)){
return list.subList(0,i);
}
i++;
}
return list;
}
public static boolean isPrime(List<Integer> primes,int candidate){
int candidateRoot = (int)Math.sqrt((double)candidate);
return takeWhile(primes,i -> i <= candidateRoot).stream().noneMatch(p ->candidate % p == 0);
}
}
收获：可以自己需要的时候开发自己的收集器 （虽然比较麻烦），可以用于追求性能的优化
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