Java 数组，查找重复项

鼻子回答..

duplicates=false;
for (j=0;j<zipcodeList.length;j++)
  for (k=j+1;k<zipcodeList.length;k++)
    if (k!=j && zipcodeList[k] == zipcodeList[j])
      duplicates=true;

编辑以切换回，因为我读到您正在使用的地方，这在最初的问题中并不清楚。还要设置 ，将执行时间减半，但它仍然是 O（n²）。.equals()==intk=j+1

更快（在极限内）的方式

下面是一种基于哈希的方法。你必须为自动装箱付费，但它是O（n）而不是O（n²）。一个有进取心的灵魂会去找一个原始的基于int的哈希集（我认为Apache或Google Collections有这样的东西。

boolean duplicates(final int[] zipcodelist)
{
  Set<Integer> lump = new HashSet<Integer>();
  for (int i : zipcodelist)
  {
    if (lump.contains(i)) return true;
    lump.add(i);
  }
  return false;
}

向惠乐鞠躬

请参阅HuyLe的答案以获取或多或少的O（n）解决方案，我认为这需要几个添加步骤：

static boolean duplicates(final int[] zipcodelist)
{
   final int MAXZIP = 99999;
   boolean[] bitmap = new boolean[MAXZIP+1];
   java.util.Arrays.fill(bitmap, false);
   for (int item : zipcodeList)
     if (!bitmap[item]) bitmap[item] = true;
     else return true;
   }
   return false;
}

或者只是为了紧凑

static boolean duplicates(final int[] zipcodelist)
{
   final int MAXZIP = 99999;
   boolean[] bitmap = new boolean[MAXZIP+1];  // Java guarantees init to false
   for (int item : zipcodeList)
     if (!(bitmap[item] ^= true)) return true;
   return false;
}

这重要吗？

好吧，所以我运行了一个小基准测试，它到处都是不可靠的，但这是代码：

import java.util.BitSet;

class Yuk
{
  static boolean duplicatesZero(final int[] zipcodelist)
  {
    boolean duplicates=false;
    for (int j=0;j<zipcodelist.length;j++)
      for (int k=j+1;k<zipcodelist.length;k++)
        if (k!=j && zipcodelist[k] == zipcodelist[j])
          duplicates=true;

    return duplicates;
  }


  static boolean duplicatesOne(final int[] zipcodelist)
  {
    final int MAXZIP = 99999;
    boolean[] bitmap = new boolean[MAXZIP + 1];
    java.util.Arrays.fill(bitmap, false);
    for (int item : zipcodelist) {
      if (!(bitmap[item] ^= true))
        return true;
    }
    return false;
  }

  static boolean duplicatesTwo(final int[] zipcodelist)
  {
    final int MAXZIP = 99999;

    BitSet b = new BitSet(MAXZIP + 1);
    b.set(0, MAXZIP, false);
    for (int item : zipcodelist) {
      if (!b.get(item)) {
        b.set(item, true);
      } else
        return true;
    }
    return false;
  }

  enum ApproachT { NSQUARED, HASHSET, BITSET};

  /**
   * @param args
   */
  public static void main(String[] args)
  {
    ApproachT approach = ApproachT.BITSET;

    final int REPS = 100;
    final int MAXZIP = 99999;

    int[] sizes = new int[] { 10, 1000, 10000, 100000, 1000000 };
    long[][] times = new long[sizes.length][REPS];

    boolean tossme = false;

    for (int sizei = 0; sizei < sizes.length; sizei++) {
      System.err.println("Trial for zipcodelist size= "+sizes[sizei]);
      for (int rep = 0; rep < REPS; rep++) {
        int[] zipcodelist = new int[sizes[sizei]];
        for (int i = 0; i < zipcodelist.length; i++) {
          zipcodelist[i] = (int) (Math.random() * (MAXZIP + 1));
        }
        long begin = System.currentTimeMillis();
        switch (approach) {
        case NSQUARED :
          tossme ^= (duplicatesZero(zipcodelist));
          break;
        case HASHSET :
          tossme ^= (duplicatesOne(zipcodelist));
          break;
        case BITSET :
          tossme ^= (duplicatesTwo(zipcodelist));
          break;

        }
        long end = System.currentTimeMillis();
        times[sizei][rep] = end - begin;


      }
      long avg = 0;
      for (int rep = 0; rep < REPS; rep++) {
        avg += times[sizei][rep];
      }
      System.err.println("Size=" + sizes[sizei] + ", avg time = "
            + avg / (double)REPS + "ms");
    }
  }

}

使用 NSQUARED：

Trial for size= 10
Size=10, avg time = 0.0ms
Trial for size= 1000
Size=1000, avg time = 0.0ms
Trial for size= 10000
Size=10000, avg time = 100.0ms
Trial for size= 100000
Size=100000, avg time = 9923.3ms

使用哈希集

Trial for zipcodelist size= 10
Size=10, avg time = 0.16ms
Trial for zipcodelist size= 1000
Size=1000, avg time = 0.15ms
Trial for zipcodelist size= 10000
Size=10000, avg time = 0.0ms
Trial for zipcodelist size= 100000
Size=100000, avg time = 0.16ms
Trial for zipcodelist size= 1000000
Size=1000000, avg time = 0.0ms

使用位集

Trial for zipcodelist size= 10
Size=10, avg time = 0.0ms
Trial for zipcodelist size= 1000
Size=1000, avg time = 0.0ms
Trial for zipcodelist size= 10000
Size=10000, avg time = 0.0ms
Trial for zipcodelist size= 100000
Size=100000, avg time = 0.0ms
Trial for zipcodelist size= 1000000
Size=1000000, avg time = 0.0ms

比塞特赢了！

但只有一根头发... .15ms 在 的误差范围内，我的基准测试中存在一些巨大的漏洞。请注意，对于任何长度超过 100000 的列表，您都可以简单地返回，因为会有重复项。实际上，如果列表是随机的，则可以为更短的列表返回真正的WHP。寓意是什么？在限制中，最有效的实现是：currentTimeMillis()true

 return true;

而且你不会经常犯错。

让我们看看你的算法是如何工作的：

an array of unique values:

[1, 2, 3]

check 1 == 1. yes, there is duplicate, assigning duplicate to true.
check 1 == 2. no, doing nothing.
check 1 == 3. no, doing nothing.
check 2 == 1. no, doing nothing.
check 2 == 2. yes, there is duplicate, assigning duplicate to true.
check 2 == 3. no, doing nothing.
check 3 == 1. no, doing nothing.
check 3 == 2. no, doing nothing.
check 3 == 3. yes, there is duplicate, assigning duplicate to true.

更好的算法：

for (j=0;j<zipcodeList.length;j++) {
    for (k=j+1;k<zipcodeList.length;k++) {
        if (zipcodeList[k]==zipcodeList[j]){ // or use .equals()
            return true;
        }
    }
}
return false;