\u66f4\u590d\u6742\u7684\u6536\u96c6\u5668\u4f7f\u7528\u573a\u666f\u901a\u5e38\u6d89\u53ca\u5230\u591a\u4e2a\u6536\u96c6\u5668\u7684\u7ec4\u5408\u3001\u81ea\u5b9a\u4e49\u6536\u96c6\u5668\u7684\u521b\u5efa\u4ee5\u53ca\u5904\u7406\u590d\u6742\u6570\u636e\u7ed3\u6784\u7684\u9700\u6c42\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u66f4\u52a0\u590d\u6742\u7684\u6536\u96c6\u5668\u4f7f\u7528\u793a\u4f8b：<\/p>\n
\u5047\u8bbe\u4f60\u6709\u4e00\u4e2a\u5305\u542b\u5458\u5de5\u4fe1\u606f\u7684\u5217\u8868，\u5e76\u5e0c\u671b\u5148\u6309\u90e8\u95e8\u5206\u7ec4，\u7136\u540e\u518d\u6309\u85aa\u8d44\u6c34\u5e73（\u4f8b\u5982\u662f\u5426\u9ad8\u4e8e\u67d0\u4e2a\u9608\u503c）\u8fdb\u4e00\u6b65\u5206\u7ec4\u3002<\/p>\n
Map<String, Map<Boolean, List<Employee>>> complexGrouping = employees.stream()
\n .collect(Collectors.groupingBy(Employee::getDepartment,
\n Collectors.partitioningBy(employee -> employee.getSalary() > 6500)));<\/p>\n
\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d，\u6211\u4eec\u9996\u5148\u901a\u8fc7 groupingBy \u6309\u7167\u90e8\u95e8\u8fdb\u884c\u5206\u7ec4，\u7136\u540e\u901a\u8fc7 partitioningBy \u6839\u636e\u85aa\u8d44\u662f\u5426\u9ad8\u4e8e\u67d0\u4e2a\u9608\u503c\u8fdb\u4e00\u6b65\u7ec6\u5206\u3002<\/p>\n
\u9664\u4e86\u7b80\u5355\u7684\u8ba1\u6570\u5916，\u8fd8\u53ef\u4ee5\u8ba1\u7b97\u6bcf\u4e2a\u90e8\u95e8\u7684\u5e73\u5747\u5de5\u8d44\u3001\u6700\u9ad8\u548c\u6700\u4f4e\u5de5\u8d44\u7b49\u8be6\u7ec6\u7edf\u8ba1\u4fe1\u606f\u3002<\/p>\n
Map<String, DoubleSummaryStatistics> salaryStatsPerDept = employees.stream()
\n .collect(Collectors.groupingBy(Employee::getDepartment,
\n Collectors.summarizingDouble(Employee::getSalary)));<\/p>\n
salaryStatsPerDept.forEach((department, stats) ->
\n System.out.println(department + ": avg=" + stats.getAverage() + ", count=" + stats.getCount()));<\/p>\n
\u8fd9\u91cc，\u6211\u4eec\u4f7f\u7528\u4e86 summarizingDouble \u6536\u96c6\u5668\u6765\u83b7\u53d6\u8be6\u7ec6\u7684\u7edf\u8ba1\u4fe1\u606f，\u5305\u62ec\u603b\u548c\u3001\u5e73\u5747\u503c\u3001\u6700\u5927\u503c\u3001\u6700\u5c0f\u503c\u548c\u5143\u7d20\u6570\u91cf\u3002<\/p>\n
\u6709\u65f6\u5185\u7f6e\u7684\u6536\u96c6\u5668\u53ef\u80fd\u4e0d\u8db3\u4ee5\u6ee1\u8db3\u7279\u5b9a\u9700\u6c42\u3002\u8fd9\u65f6\u53ef\u4ee5\u901a\u8fc7\u5b9e\u73b0\u81ea\u5b9a\u4e49\u6536\u96c6\u5668\u6765\u5b8c\u6210\u590d\u6742\u4efb\u52a1\u3002\u4f8b\u5982，\u5047\u8bbe\u6211\u4eec\u9700\u8981\u521b\u5efa\u4e00\u4e2a\u5c06\u5458\u5de5\u6309\u7167\u59d3\u6c0f\u9996\u5b57\u6bcd\u5206\u7c7b，\u5e76\u8ba1\u7b97\u6bcf\u4e2a\u7c7b\u522b\u4e0b\u7684\u5e73\u5747\u85aa\u8d44\u7684\u6620\u5c04：<\/p>\n
import java.util.*;
\nimport java.util.function.BiConsumer;
\nimport java.util.function.BinaryOperator;
\nimport java.util.function.Function;
\nimport java.util.function.Supplier;
\nimport java.util.stream.Collector;<\/p>\n
public class CustomCollectorExample {<\/p>\n
public static void main(String[] args) {
\n List<Employee> employees = Arrays.asList(
\n new Employee("Alice", "HR", 5000),
\n new Employee("Bob", "IT", 7000),
\n new Employee("Charlie", "IT", 8000),
\n new Employee("David", "HR", 6000)
\n );<\/p>\n
Map<Character, Double> result = employees.stream()
\n .collect(new InitialLetterSalaryAverager());<\/p>\n
result.forEach((letter, avgSalary) ->
\n System.out.println(letter + ": " + avgSalary));
\n }<\/p>\n
private static class InitialLetterSalaryAverager implements Collector<Employee, Map<Character, Tuple>, Map<Character, Double>> {<\/p>\n
@Override
\n public Supplier<Map<Character, Tuple>> supplier() {
\n return HashMap::new;
\n }<\/p>\n
@Override
\n public BiConsumer<Map<Character, Tuple>, Employee> accumulator() {
\n return (map, employee) -> {
\n char firstLetter = employee.getName().charAt(0);
\n map.computeIfAbsent(firstLetter, k -> new Tuple()).add(employee.getSalary());
\n };
\n }<\/p>\n
@Override
\n public BinaryOperator<Map<Character, Tuple>> combiner() {
\n return (map1, map2) -> {
\n map2.forEach((key, value) -> map1.merge(key, value, Tuple::merge));
\n return map1;
\n };
\n }<\/p>\n
@Override
\n public Function<Map<Character, Tuple>, Map<Character, Double>> finisher() {
\n return map -> map.entrySet().stream()
\n .collect(Collectors.toMap(Map.Entry::getKey, entry -> entry.getValue().average()));
\n }<\/p>\n
@Override
\n public Set<Characteristics> characteristics() {
\n return EnumSet.of(Characteristics.IDENTITY_FINISH);
\n }<\/p>\n
private static class Tuple {
\n private int count = 0;
\n private double totalSalary = 0;<\/p>\n
public void add(double salary) {
\n count++;
\n totalSalary += salary;
\n }<\/p>\n
public Tuple merge(Tuple other) {
\n this.count += other.count;
\n this.totalSalary += other.totalSalary;
\n return this;
\n }<\/p>\n
public double average() {
\n return totalSalary \/ count;
\n }
\n }
\n }
\n}<\/p>\n
\u8fd9\u4e2a\u81ea\u5b9a\u4e49\u6536\u96c6\u5668\u5b9e\u73b0\u4e86 Collector \u63a5\u53e3，\u5b83\u6839\u636e\u5458\u5de5\u540d\u5b57\u7684\u7b2c\u4e00\u4e2a\u5b57\u6bcd\u5bf9\u4ed6\u4eec\u8fdb\u884c\u5206\u7ec4，\u5e76\u8ba1\u7b97\u6bcf\u4e2a\u5b57\u6bcd\u5f00\u5934\u7684\u540d\u5b57\u5bf9\u5e94\u7684\u5e73\u5747\u85aa\u8d44\u3002\u8fd9\u79cd\u65b9\u6cd5\u867d\u7136\u6bd4\u76f4\u63a5\u4f7f\u7528\u5185\u7f6e\u6536\u96c6\u5668\u590d\u6742\u5f97\u591a，\u4f46\u5b83\u5c55\u793a\u4e86\u5982\u4f55\u5728 Java \u4e2d\u7075\u6d3b\u5730\u5b9a\u5236\u6d41\u7684\u884c\u4e3a\u4ee5\u9002\u5e94\u5177\u4f53\u7684\u9700\u6c42\u3002<\/p>\n
\u6709\u65f6\u5019\u9700\u8981\u5bf9\u6570\u636e\u8fdb\u884c\u591a\u5c42\u6b21\u7684\u6c47\u603b\u3002\u4f8b\u5982，\u4f60\u53ef\u80fd\u60f3\u8981\u5148\u6309\u90e8\u95e8\u5206\u7ec4，\u7136\u540e\u5bf9\u6bcf\u4e2a\u90e8\u95e8\u5185\u7684\u5458\u5de5\u8fdb\u884c\u4e00\u4e9b\u5176\u4ed6\u7684\u7edf\u8ba1\u5206\u6790（\u5982\u8ba1\u7b97\u6bcf\u4e2a\u90e8\u95e8\u5185\u6240\u6709\u5458\u5de5\u7684\u5de5\u8d44\u603b\u548c）\u3002<\/p>\n
Map<String, Integer> totalSalaryPerDept = employees.stream()
\n .collect(Collectors.groupingBy(Employee::getDepartment,
\n Collectors.summingInt(Employee::getSalary)));<\/p>\n
\u8fd9\u4f1a\u7ed9\u4f60\u4e00\u4e2a Map<String, Integer>，\u5176\u4e2d\u952e\u662f\u90e8\u95e8\u540d\u79f0，\u503c\u662f\u8be5\u90e8\u95e8\u6240\u6709\u5458\u5de5\u7684\u5de5\u8d44\u603b\u548c\u3002<\/p>\n
\u901a\u8fc7\u8fd9\u4e9b\u9ad8\u7ea7\u7528\u6cd5，\u4f60\u53ef\u4ee5\u5145\u5206\u5229\u7528 Stream API \u7684\u7075\u6d3b\u6027\u6765\u5904\u7406\u5404\u79cd\u590d\u6742\u7684\u6570\u636e\u8f6c\u6362\u548c\u805a\u5408\u4efb\u52a1\u3002\u65e0\u8bba\u662f\u591a\u7ea7\u5206\u7ec4\u3001\u8be6\u7ec6\u7edf\u8ba1\u5206\u6790\u8fd8\u662f\u521b\u5efa\u81ea\u5b9a\u4e49\u6536\u96c6\u5668，\u90fd\u80fd\u5e2e\u52a9\u4f60\u7f16\u5199\u51fa\u7b80\u6d01\u800c\u5f3a\u5927\u7684\u4ee3\u7801\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"
\u6587\u7ae0\u6d4f\u89c8\u9605\u8bfb617\u6b21\uff0c\u70b9\u8d5e10\u6b21\uff0c\u6536\u85cf3\u6b21\u3002\u6709\u65f6\u5185\u7f6e\u7684\u6536\u96c6\u5668\u53ef\u80fd\u4e0d\u8db3\u4ee5\u6ee1\u8db3\u7279\u5b9a\u9700\u6c42\u3002\u8fd9\u65f6\u53ef\u4ee5\u901a\u8fc7\u5b9e\u73b0\u81ea\u5b9a\u4e49\u6536\u96c6\u5668\u6765\u5b8c\u6210\u590d\u6742\u4efb\u52a1\u3002<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[99,81,149,190],"topic":[],"class_list":["post-53500","post","type-post","status-publish","format-standard","hentry","category-server","tag-java","tag-python","tag-windows","tag-190"],"yoast_head":"\n