Java 8 –在流中查找重复的元素

程序员文章站 2022-07-12 09:27:51

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本文介绍了三种在Stream中查找重复元素的算法。

Set.add()
Collectors.groupingBy
Collections.frequency

在本文的最后，我们使用JMH基准测试哪个是最快的算法。

1. Filter＆Set.add（）

如果元素已经在集合中，则Set.add()返回false；否则，返回false。让我们在文章末尾查看基准。

JavaDuplicated1.java

package com.mkyong;

import java.util.Arrays;
import java.util.HashSet;
import java.util.List;
import java.util.Set;
import java.util.stream.Collectors;

public class JavaDuplicated1 {

    public static void main(String[] args) {

        // 3, 4, 9
        List<Integer> list = Arrays.asList(5, 3, 4, 1, 3, 7, 2, 9, 9, 4);

        Set<Integer> result = findDuplicateBySetAdd(list);

        result.forEach(System.out::println);

    }

    public static <T> Set<T> findDuplicateBySetAdd(List<T> list) {

        Set<T> items = new HashSet<>();
        return list.stream()
                .filter(n -> !items.add(n)) // Set.add() returns false if the element was already in the set.
                .collect(Collectors.toSet());

    }

}

输出量

3
4
9

2. Map＆Collectors.groupingBy

2.1通过Collectors.groupingBy创建Map ，并找到计数> 1的元素。

JavaDuplicated2.java

package com.mkyong;

import java.util.*;
import java.util.function.Function;
import java.util.stream.Collectors;

public class JavaDuplicated2 {

    public static void main(String[] args) {

        // 3, 4, 9
        List<Integer> list = Arrays.asList(5, 3, 4, 1, 3, 7, 2, 9, 9, 4);

        Set<Integer> result = findDuplicateByGrouping(list);

        result.forEach(System.out::println);

    }

    public static <T> Set<T> findDuplicateByGrouping(List<T> list) {

        return list.stream()
                .collect(Collectors.groupingBy(Function.identity()
                        , Collectors.counting()))    // create a map {1=1, 2=1, 3=2, 4=2, 5=1, 7=1, 9=2}
                .entrySet().stream()                 // Map -> Stream
                .filter(m -> m.getValue() > 1)       // if map value > 1, duplicate element
                .map(Map.Entry::getKey)
                .collect(Collectors.toSet());

    }

}

输出量

3
4
9

3. Collections.frequency

它将每个项目与一个列表进行比较– Collections.frequency(list, i) 。

JavaDuplicated3.java

package com.mkyong;

import java.util.Arrays;
import java.util.Collections;
import java.util.List;
import java.util.Set;
import java.util.stream.Collectors;

public class JavaDuplicated3 {

    public static void main(String[] args) {

        // 3, 4, 9
        List<Integer> list = Arrays.asList(5, 3, 4, 1, 3, 7, 2, 9, 9, 4);

        Set<Integer> result = findDuplicateByFrequency(list);

        result.forEach(System.out::println);

    }

    public static <T> Set<T> findDuplicateByFrequency(List<T> list) {

        return list.stream().filter(i -> Collections.frequency(list, i) > 1)
                .collect(Collectors.toSet());

    }

}

输出量

3
4
9

4. JMH基准

一个针对上述三种算法的简单JMH基准，可从大小为1000的Stream中查找重复元素。

pom.xml

<dependency>
      <groupId>org.openjdk.jmh</groupId>
      <artifactId>jmh-core</artifactId>
      <version>1.23</version>
  </dependency>

  <dependency>
      <groupId>org.openjdk.jmh</groupId>
      <artifactId>jmh-generator-annprocess</artifactId>
      <version>1.23</version>
  </dependency>

BenchmarkFindDuplicate.java

package com.mkyong;

import org.openjdk.jmh.annotations.*;
import org.openjdk.jmh.infra.Blackhole;
import org.openjdk.jmh.runner.Runner;
import org.openjdk.jmh.runner.RunnerException;
import org.openjdk.jmh.runner.options.Options;
import org.openjdk.jmh.runner.options.OptionsBuilder;

import java.util.*;
import java.util.concurrent.TimeUnit;
import java.util.function.Function;
import java.util.stream.Collectors;

@BenchmarkMode(Mode.AverageTime)
@OutputTimeUnit(TimeUnit.MILLISECONDS)
@State(Scope.Benchmark)
@Fork(value = 2, jvmArgs = {"-Xms4G", "-Xmx4G"})
public class BenchmarkFindDuplicate {

    private List<Integer> DATA_FOR_TESTING;

    @Setup
    public void init() {
        // random 1000 size
        DATA_FOR_TESTING = new Random().ints(1000, 1, 1000)
                .boxed()
                .collect(Collectors.toList());
    }

    public static void main(String[] args) throws RunnerException {

        Options opt = new OptionsBuilder()
                .include(BenchmarkFindDuplicate.class.getSimpleName())
                .forks(1)
                .build();

        new Runner(opt).run();

    }

    @Benchmark
    public void setAdd(Blackhole bh) {

        Set<Integer> items = new HashSet<>();
        Set<Integer> collect = DATA_FOR_TESTING.stream()
                .filter(n -> !items.add(n))
                .collect(Collectors.toSet());

        bh.consume(collect);

    }

    @Benchmark
    public void groupingBy(Blackhole bh) {

        Set<Integer> collect = DATA_FOR_TESTING.stream()
                .collect(Collectors.groupingBy(Function.identity(), Collectors.counting()))
                .entrySet()
                .stream()
                .filter(m -> m.getValue() > 1)
                .map(Map.Entry::getKey)
                .collect(Collectors.toSet());

        bh.consume(collect);

    }

    @Benchmark
    public void frequency(Blackhole bh) {

        Set<Integer> collect = DATA_FOR_TESTING.stream()
                .filter(i -> Collections.frequency(DATA_FOR_TESTING, i) > 1)
                .collect(Collectors.toSet());

        bh.consume(collect);

    }

}

输出量

# JMH version: 1.23
# VM version: JDK 11.0.6, OpenJDK 64-Bit Server VM, 11.0.6+10
# VM invoker: /usr/lib/jvm/adoptopenjdk-11-hotspot-amd64/bin/java
# VM options: -Xms4G -Xmx4G
# Warmup: 5 iterations, 10 s each
# Measurement: 5 iterations, 10 s each
# Timeout: 10 min per iteration
# Threads: 1 thread, will synchronize iterations
# Benchmark mode: Average time, time/op
# Benchmark: com.mkyong.BenchmarkFindDuplicate.frequency

# Run progress: 0.00% complete, ETA 00:05:00
# Fork: 1 of 1
# Warmup Iteration   1: 0.827 ms/op
# Warmup Iteration   2: 0.821 ms/op
# Warmup Iteration   3: 0.812 ms/op
# Warmup Iteration   4: 0.822 ms/op
# Warmup Iteration   5: 0.822 ms/op
Iteration   1: 0.814 ms/op
Iteration   2: 0.810 ms/op
Iteration   3: 0.779 ms/op
Iteration   4: 0.776 ms/op
Iteration   5: 0.814 ms/op


Result "com.mkyong.BenchmarkFindDuplicate.frequency":
  0.799 ±(99.9%) 0.075 ms/op [Average]
  (min, avg, max) = (0.776, 0.799, 0.814), stdev = 0.019
  CI (99.9%): [0.724, 0.874] (assumes normal distribution)


# JMH version: 1.23
# VM version: JDK 11.0.6, OpenJDK 64-Bit Server VM, 11.0.6+10
# VM invoker: /usr/lib/jvm/adoptopenjdk-11-hotspot-amd64/bin/java
# VM options: -Xms4G -Xmx4G
# Warmup: 5 iterations, 10 s each
# Measurement: 5 iterations, 10 s each
# Timeout: 10 min per iteration
# Threads: 1 thread, will synchronize iterations
# Benchmark mode: Average time, time/op
# Benchmark: com.mkyong.BenchmarkFindDuplicate.groupingBy

# Run progress: 33.33% complete, ETA 00:03:20
# Fork: 1 of 1
# Warmup Iteration   1: 0.040 ms/op
# Warmup Iteration   2: 0.038 ms/op
# Warmup Iteration   3: 0.037 ms/op
# Warmup Iteration   4: 0.036 ms/op
# Warmup Iteration   5: 0.039 ms/op
Iteration   1: 0.039 ms/op
Iteration   2: 0.039 ms/op
Iteration   3: 0.039 ms/op
Iteration   4: 0.039 ms/op
Iteration   5: 0.039 ms/op


Result "com.mkyong.BenchmarkFindDuplicate.groupingBy":
  0.039 ±(99.9%) 0.001 ms/op [Average]
  (min, avg, max) = (0.039, 0.039, 0.039), stdev = 0.001
  CI (99.9%): [0.038, 0.040] (assumes normal distribution)


# JMH version: 1.23
# VM version: JDK 11.0.6, OpenJDK 64-Bit Server VM, 11.0.6+10
# VM invoker: /usr/lib/jvm/adoptopenjdk-11-hotspot-amd64/bin/java
# VM options: -Xms4G -Xmx4G
# Warmup: 5 iterations, 10 s each
# Measurement: 5 iterations, 10 s each
# Timeout: 10 min per iteration
# Threads: 1 thread, will synchronize iterations
# Benchmark mode: Average time, time/op
# Benchmark: com.mkyong.BenchmarkFindDuplicate.setAdd

# Run progress: 66.67% complete, ETA 00:01:40
# Fork: 1 of 1
# Warmup Iteration   1: 0.027 ms/op
# Warmup Iteration   2: 0.028 ms/op
# Warmup Iteration   3: 0.026 ms/op
# Warmup Iteration   4: 0.026 ms/op
# Warmup Iteration   5: 0.027 ms/op
Iteration   1: 0.026 ms/op
Iteration   2: 0.027 ms/op
Iteration   3: 0.028 ms/op
Iteration   4: 0.028 ms/op
Iteration   5: 0.028 ms/op


Result "com.mkyong.BenchmarkFindDuplicate.setAdd":
  0.027 ±(99.9%) 0.003 ms/op [Average]
  (min, avg, max) = (0.026, 0.027, 0.028), stdev = 0.001
  CI (99.9%): [0.024, 0.031] (assumes normal distribution)


# Run complete. Total time: 00:05:01

REMEMBER: The numbers below are just data. To gain reusable insights, you need to follow up on
why the numbers are the way they are. Use profilers (see -prof, -lprof), design factorial
experiments, perform baseline and negative tests that provide experimental control, make sure
the benchmarking environment is safe on JVM/OS/HW level, ask for reviews from the domain experts.
Do not assume the numbers tell you what you want them to tell.

Benchmark                          Mode  Cnt  Score   Error  Units
BenchmarkFindDuplicate.frequency   avgt    5  0.799 ± 0.075  ms/op
BenchmarkFindDuplicate.groupingBy  avgt    5  0.039 ± 0.001  ms/op
BenchmarkFindDuplicate.setAdd      avgt    5  0.027 ± 0.003  ms/op

Process finished with exit code 0

在Java 8 Stream中，使用Set.Add()过滤是查找重复元素的最快算法，因为它仅循环一次。

Set<T> items = new HashSet<>();
  return list.stream()
        .filter(n -> !items.add(n))
        .collect(Collectors.toSet());

Collections.frequency最慢，因为它会将每个项目与一个列表进行比较– Collections.frequency(list, i) 。如果我们增加列表的大小，性能将会变慢。

return list.stream().filter(i -> Collections.frequency(list, i) > 1)
        .collect(Collectors.toSet());

参考文献

标签：基准收集者重复通过 Java 8 JMH 流组

From: https://mkyong.com/java8/java-8-find-duplicate-elements-in-a-stream/

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Java 8 –在流中查找重复的元素

1. Filter＆Set.add（）

2. Map＆Collectors.groupingBy

3. Collections.frequency

4. JMH基准

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Java 8 –在流中查找重复的元素

1. Filter＆Set.add（）

2. Map＆Collectors.groupingBy

3. Collections.frequency

4. JMH基准

参考文献

解析PHP函数array_flip()在重复数组元素删除中的作用

在Java8中如何风骚走位的避开空指针异常

JAVA 8 lambda 表达式实现按某个属性值查找集合中符合条件的所有对象并求和

给定一个整数数组 nums 和一个目标值 target，请你在该数组中找出和为目标值的 两个 整数。 你可以假设每种输入只会对应一个答案。但是，你不能重复利用这个数组中同样的元素

java 去除数组中重复的元素

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查找数组中的重复元素

快速在数组中查找重复和遗失的元素

查找Set中重复的元素

给定一个整数数组 nums 和一个目标值 target，请你在该数组中找出和为目标值的两个整数。你可以假设每种输入只会对应一个答案。但是，你不能重复利用这个数组中同样的元素