我的面试问题是这样的:

给定一个包含40亿个整数的输入文件,提供一种算法来生成一个文件中不包含的整数。假设您有1gb内存。如果你只有10mb的内存,你会怎么做。

我的分析:

文件大小为4×109×4 bytes = 16gb。

我们可以进行外部排序,从而知道整数的范围。

我的问题是,在已排序的大整数集中检测缺失整数的最佳方法是什么?

我的理解(看完所有答案后):

假设我们讨论的是32位整数,有232 = 4*109个不同的整数。

情况1:我们有1gb = 1 * 109 * 8位= 80亿位内存。

解决方案:

如果我们用一位表示一个不同的整数,这就足够了。我们不需要排序。

实现:

int radix = 8;
byte[] bitfield = new byte[0xffffffff/radix];
void F() throws FileNotFoundException{
    Scanner in = new Scanner(new FileReader("a.txt"));
    while(in.hasNextInt()){
        int n = in.nextInt();
        bitfield[n/radix] |= (1 << (n%radix));
    }

    for(int i = 0; i< bitfield.lenght; i++){
        for(int j =0; j<radix; j++){
            if( (bitfield[i] & (1<<j)) == 0) System.out.print(i*radix+j);
        }
    }
}

情形二:10mb内存= 10 * 106 * 8bits = 8000万bits

Solution: For all possible 16-bit prefixes, there are 216 number of integers = 65536, we need 216 * 4 * 8 = 2 million bits. We need build 65536 buckets. For each bucket, we need 4 bytes holding all possibilities because the worst case is all the 4 billion integers belong to the same bucket. Build the counter of each bucket through the first pass through the file. Scan the buckets, find the first one who has less than 65536 hit. Build new buckets whose high 16-bit prefixes are we found in step2 through second pass of the file Scan the buckets built in step3, find the first bucket which doesnt have a hit. The code is very similar to above one.

结论: 我们通过增加文件传递来减少内存。


为那些迟到的人澄清一下:这个问题,正如所问的,并不是说有一个整数没有包含在文件中——至少大多数人不是这么理解的。不过,评论线程中的许多评论都是关于任务的变化。不幸的是,把它引入评论线程的评论后来被它的作者删除了,所以现在看起来它的孤儿回复只是误解了一切。这很让人困惑,抱歉。


当前回答

这是个陷阱问题,除非引用不当。只需要通读文件一次,得到最大整数n,并返回n+1。

当然,您需要一个备份计划,以防n+1导致整数溢出。

其他回答

你不需要对它们排序,只需要重复划分它们的子集。

The first step is like the first pass of a quicksort. Pick one of the integers, x, and using it make a pass through the array to put all the values less than x to its left and values more than x to its right. Find which side of x has the greatest number of available slots (integers not in the list). This is easily computable by comparing the value of x with its position. Then repeat the partition on the sub-list on that side of x. Then repeat the partition on the sub-sub list with the greatest number of available integers, etc. Total number of compares to get down to an empty range should be about 4 billion, give or take.

对于1gb RAM的变体,您可以使用位向量。你需要分配40亿比特== 500 MB字节数组。对于从输入中读取的每个数字,将相应的位设置为“1”。一旦你完成了,遍历比特,找到第一个仍然是“0”的比特。它的索引就是答案。

Surely, and speaking with limited experience (just started learning java at Uni) you can run trhough one set (barrel) of int, and if number not found dispose of barrel. This would both free up space and run a check through each unit of data. If what you are looking for is found add it to a count variable. Would take a long time but, if you made multiple variables for each section and run the check count through each variable and ensure they are exiting/disposing at the same time, the variable storage should not increase? And will speed up the check process. Just a thought.

使用BitSet。40亿个整数(假设最多2^32个整数)以每字节8个的速度打包到BitSet中,大约是2^32 / 2^3 = 2^29 = 0.5 Gb。

要添加更多的细节-每次读取一个数字时,在BitSet中设置相应的位。然后,遍历BitSet以找到第一个不存在的数字。事实上,你可以通过重复选择一个随机数并测试它是否存在来有效地做到这一点。

实际上BitSet.nextClearBit(0)会告诉你第一个非设置位。

看看BitSet API,它似乎只支持0..MAX_INT,所以你可能需要2个bitset -一个用于+ ve数字,一个用于- ve数字-但内存需求不会改变。

根据原题中目前的措辞,最简单的解决方法是:

找到文件中的最大值,然后加上1。