或者相反，你可以检查这个数字是否大于或小于所需的数字。

    public void createCard(int cardNumber, int cardStatus, int customerId) throws SQLException {
    if(cardDao.checkIfCardExists(cardNumber) == false) {
        if(cardDao.createCard(cardNumber, cardStatus, customerId) == true) {
            System.out.println("Card created successfully");
        } else {

        }
    } else {
        System.out.println("Card already exists, try with another Card Number");
        do {
            System.out.println("Enter your new Card Number: ");
            scan = new Scanner(System.in);
            int inputCardNumber = scan.nextInt();
            cardNumber = inputCardNumber;
        } while(cardNumber < 95000000);
        cardDao.createCard(cardNumber, cardStatus, customerId);
    }
}

}

出于好奇，我试着对其进行基准测试……

import org.junit.Test;
import static org.junit.Assert.*;


public class TestStack1306727 {

    @Test
    public void bench(){
        int number=1000;
        int a= String.valueOf(number).length();
        int b= 1 + (int)Math.floor(Math.log10(number));

        assertEquals(a,b);
        int i=0;
        int s=0;
        long startTime = System.currentTimeMillis();
        for(i=0, s=0; i< 100000000; i++){
            a= String.valueOf(number).length();
            s+=a;
        }
        long stopTime = System.currentTimeMillis();
        long runTime = stopTime - startTime;
        System.out.println("Run time 1: " + runTime);
        System.out.println("s: "+s);
        startTime = System.currentTimeMillis();
        for(i=0,s=0; i< 100000000; i++){
            b= number==0?1:(1 + (int)Math.floor(Math.log10(Math.abs(number))));
            s+=b;
        }
        stopTime = System.currentTimeMillis();
        runTime = stopTime - startTime;
        System.out.println("Run time 2: " + runTime);
        System.out.println("s: "+s);
        assertEquals(a,b);


    }
}

结果如下:

Run time 1: 6765
s: 400000000
Run time 2: 6000
s: 400000000

现在我想知道我的基准测试是否真的意味着什么，但我确实在基准测试本身的多次运行中得到了一致的结果(一毫秒内的变化)……:)看起来这是无用的尝试和优化…

编辑:根据ptomli的注释，我在上面的代码中用' I '替换'number'，并在5次运行的bench中得到以下结果:

Run time 1: 11500
s: 788888890
Run time 2: 8547
s: 788888890

Run time 1: 11485
s: 788888890
Run time 2: 8547
s: 788888890

Run time 1: 11469
s: 788888890
Run time 2: 8547
s: 788888890

Run time 1: 11500
s: 788888890
Run time 2: 8547
s: 788888890

Run time 1: 11484
s: 788888890
Run time 2: 8547
s: 788888890

我在看了Integer.java源代码后写了这个函数。

private static int stringSize(int x) {
    final int[] sizeTable = {9, 99, 999, 9_999, 99_999, 999_999, 9_999_999,
            99_999_999, 999_999_999, Integer.MAX_VALUE};
    for (int i = 0; ; ++i) {
        if (x <= sizeTable[i]) {
            return i + 1;
        }
    }
}

我还没有看到基于乘法的解决方案。对数、除法和基于字符串的解决方案将在数百万个测试用例中变得相当笨拙，所以这里有一个int型的解决方案:

/**
 * Returns the number of digits needed to represents an {@code int} value in 
 * the given radix, disregarding any sign.
 */
public static int len(int n, int radix) {
    radixCheck(radix); 
    // if you want to establish some limitation other than radix > 2
    n = Math.abs(n);

    int len = 1;
    long min = radix - 1;

    while (n > min) {
        n -= min;
        min *= radix;
        len++;
    }

    return len;
}

以10为基底，这是可行的，因为n本质上是与9,99,999…因为min是9,90,900…n被减去9,90,900…

不幸的是，仅仅因为溢出而替换int的每个实例是不能移植到long的。另一方面，它恰好适用于2垒和10垒(但对于大多数其他垒来说严重失败)。您将需要一个用于溢出点的查找表(或除法测试……)电子战)

/**
 * For radices 2 &le r &le Character.MAX_VALUE (36)
 */
private static long[] overflowpt = {-1, -1, 4611686018427387904L,
    8105110306037952534L, 3458764513820540928L, 5960464477539062500L,
    3948651115268014080L, 3351275184499704042L, 8070450532247928832L,
    1200757082375992968L, 9000000000000000000L, 5054470284992937710L,
    2033726847845400576L, 7984999310198158092L, 2022385242251558912L,
    6130514465332031250L, 1080863910568919040L, 2694045224950414864L,
    6371827248895377408L, 756953702320627062L, 1556480000000000000L,
    3089447554782389220L, 5939011215544737792L, 482121737504447062L,
    839967991029301248L, 1430511474609375000L, 2385723916542054400L,
    3902460517721977146L, 6269893157408735232L, 341614273439763212L,
    513726300000000000L, 762254306892144930L, 1116892707587883008L,
    1617347408439258144L, 2316231840055068672L, 3282671350683593750L,
    4606759634479349760L};

public static int len(long n, int radix) {
    radixCheck(radix);
    n = abs(n);

    int len = 1;
    long min = radix - 1;
    while (n > min) {
        len++;
        if (min == overflowpt[radix]) break;
        n -= min;
        min *= radix;

    }

    return len;
}

没有字符串API，没有utils，没有类型转换，只是纯java迭代->

public static int getNumberOfDigits(int input) {
    int numOfDigits = 1;
    int base = 1;
    while (input >= base * 10) {
        base = base * 10;
        numOfDigits++;
    }
    return numOfDigits;
 }

如果你愿意，你可以追求更大的价值。

现在还不能留言，所以我会单独回复。

基于对数的解决方案不能计算非常大的长整数的正确位数，例如:

long n = 99999999999999999L;

// correct answer: 17
int numberOfDigits = String.valueOf(n).length();

// incorrect answer: 18
int wrongNumberOfDigits = (int) (Math.log10(n) + 1); 

基于对数的解决方案在大整数中计算不正确的位数