在Java中异常对性能有什么影响?

问:Java中的异常处理真的很慢吗?

传统观点以及大量谷歌结果表明，不应该将异常逻辑用于Java中的正常程序流。通常会给出两个原因，

它真的很慢——甚至比普通代码慢一个数量级(给出的原因各不相同)，

and

它很混乱，因为人们只希望在异常代码中处理错误。

这个问题是关于第一条的。

As an example, this page describes Java exception handling as "very slow" and relates the slowness to the creation of the exception message string - "this string is then used in creating the exception object that is thrown. This is not fast." The article Effective Exception Handling in Java says that "the reason for this is due to the object creation aspect of exception handling, which thereby makes throwing exceptions inherently slow". Another reason out there is that the stack trace generation is what slows it down.

My testing (using Java 1.6.0_07, Java HotSpot 10.0, on 32 bit Linux), indicates that exception handling is no slower than regular code. I tried running a method in a loop that executes some code. At the end of the method, I use a boolean to indicate whether to return or throw. This way the actual processing is the same. I tried running the methods in different orders and averaging my test times, thinking it may have been the JVM warming up. In all my tests, the throw was at least as fast as the return, if not faster (up to 3.1% faster). I am completely open to the possibility that my tests were wrong, but I haven't seen anything out there in the way of the code sample, test comparisons, or results in the last year or two that show exception handling in Java to actually be slow.

引导我走上这条路的是我需要使用的一个API，它将抛出异常作为正常控制逻辑的一部分。我想纠正它们的用法，但现在我可能做不到。我是否应该赞美他们的前瞻思维?

在论文《即时编译中的高效Java异常处理》中，作者建议，即使没有抛出异常，仅异常处理程序的存在就足以阻止JIT编译器正确优化代码，从而降低代码的速度。我还没有测试过这个理论。

当前回答

我已经扩展了@Mecki和@incarnate给出的答案，没有为Java填充stacktrace。

在Java 7+中，我们可以使用Throwable(String message, Throwable cause, boolean enableSuppression,boolean writableStackTrace)。但是对于Java6，请参阅我对这个问题的回答

// This one will regularly throw one
public void method4(int i) throws NoStackTraceThrowable {
    value = ((value + i) / i) << 1;
    // i & 1 is equally fast to calculate as i & 0xFFFFFFF; it is both
    // an AND operation between two integers. The size of the number plays
    // no role. AND on 32 BIT always ANDs all 32 bits
    if ((i & 0x1) == 1) {
        throw new NoStackTraceThrowable();
    }
}

// This one will regularly throw one
public void method5(int i) throws NoStackTraceRuntimeException {
    value = ((value + i) / i) << 1;
    // i & 1 is equally fast to calculate as i & 0xFFFFFFF; it is both
    // an AND operation between two integers. The size of the number plays
    // no role. AND on 32 BIT always ANDs all 32 bits
    if ((i & 0x1) == 1) {
        throw new NoStackTraceRuntimeException();
    }
}

public static void main(String[] args) {
    int i;
    long l;
    Test t = new Test();

    l = System.currentTimeMillis();
    t.reset();
    for (i = 1; i < 100000000; i++) {
        try {
            t.method4(i);
        } catch (NoStackTraceThrowable e) {
            // Do nothing here, as we will get here
        }
    }
    l = System.currentTimeMillis() - l;
    System.out.println( "method4 took " + l + " ms, result was " + t.getValue() );


    l = System.currentTimeMillis();
    t.reset();
    for (i = 1; i < 100000000; i++) {
        try {
            t.method5(i);
        } catch (RuntimeException e) {
            // Do nothing here, as we will get here
        }
    }
    l = System.currentTimeMillis() - l;
    System.out.println( "method5 took " + l + " ms, result was " + t.getValue() );
}

输出与Java 1.6.0_45，在Core i7, 8GB RAM:

method1 took 883 ms, result was 2
method2 took 882 ms, result was 2
method3 took 32270 ms, result was 2 // throws Exception
method4 took 8114 ms, result was 2 // throws NoStackTraceThrowable
method5 took 8086 ms, result was 2 // throws NoStackTraceRuntimeException

因此，返回值的方法仍然比引发异常的方法更快。恕我直言，我们不能仅仅为成功流和错误流使用返回类型来设计一个清晰的API。在没有stacktrace的情况下抛出异常的方法比普通异常快4-5倍。

谢谢@Greg

public class NoStackTraceThrowable extends Throwable { 
    public NoStackTraceThrowable() { 
        super("my special throwable", null, false, false);
    }
}

2014-08-15 09:59:49

其他回答

关于异常性能的好文章是:

https://shipilev.net/blog/2014/exceptional-performance/

实例化vs重用现有的，有堆栈跟踪和没有，等等:

Benchmark                            Mode   Samples         Mean   Mean error  Units

dynamicException                     avgt        25     1901.196       14.572  ns/op
dynamicException_NoStack             avgt        25       67.029        0.212  ns/op
dynamicException_NoStack_UsedData    avgt        25       68.952        0.441  ns/op
dynamicException_NoStack_UsedStack   avgt        25      137.329        1.039  ns/op
dynamicException_UsedData            avgt        25     1900.770        9.359  ns/op
dynamicException_UsedStack           avgt        25    20033.658      118.600  ns/op

plain                                avgt        25        1.259        0.002  ns/op
staticException                      avgt        25        1.510        0.001  ns/op
staticException_NoStack              avgt        25        1.514        0.003  ns/op
staticException_NoStack_UsedData     avgt        25        4.185        0.015  ns/op
staticException_NoStack_UsedStack    avgt        25       19.110        0.051  ns/op
staticException_UsedData             avgt        25        4.159        0.007  ns/op
staticException_UsedStack            avgt        25       25.144        0.186  ns/op

根据堆栈跟踪的深度:

Benchmark        Mode   Samples         Mean   Mean error  Units

exception_0000   avgt        25     1959.068       30.783  ns/op
exception_0001   avgt        25     1945.958       12.104  ns/op
exception_0002   avgt        25     2063.575       47.708  ns/op
exception_0004   avgt        25     2211.882       29.417  ns/op
exception_0008   avgt        25     2472.729       57.336  ns/op
exception_0016   avgt        25     2950.847       29.863  ns/op
exception_0032   avgt        25     4416.548       50.340  ns/op
exception_0064   avgt        25     6845.140       40.114  ns/op
exception_0128   avgt        25    11774.758       54.299  ns/op
exception_0256   avgt        25    21617.526      101.379  ns/op
exception_0512   avgt        25    42780.434      144.594  ns/op
exception_1024   avgt        25    82839.358      291.434  ns/op

有关其他详细信息(包括来自JIT的x64汇编程序)，请阅读原始博客文章。

这意味着Hibernate/Spring/etc-EE-shit因为异常(xD)而变慢。

通过重写应用程序控制流，避免异常(返回错误作为返回)，提高应用程序的性能10 -100倍，这取决于你抛出它们的频率))

2018-03-21 19:38:56

HotSpot非常能够删除系统生成的异常代码，只要它是内联的。但是，显式创建的异常和其他未删除的异常要花费大量时间来创建堆栈跟踪。重写fillInStackTrace以查看这会如何影响性能。

2008-11-18 16:07:25

我认为第一篇文章提到遍历调用堆栈和创建堆栈跟踪是最昂贵的部分，虽然第二篇文章没有这样说，但我认为这是对象创建中最昂贵的部分。John Rose在一篇文章中描述了加速异常的不同技术。(预分配和重用异常，没有堆栈跟踪的异常，等等)

但我仍然认为这应该被认为是一种必要的邪恶，一种最后的手段。John这样做的原因是为了模拟JVM中(还)没有的其他语言的特性。你不应该养成对控制流使用异常的习惯。尤其是因为性能原因!正如您自己在第2条中提到的，这样做可能会掩盖代码中的严重错误，而且对于新程序员来说，维护起来会更加困难。

Java中的微基准测试出奇地难以正确(有人告诉过我)，特别是在进入JIT领域时，因此我真的怀疑在现实生活中使用异常是否比“返回”更快。例如，我怀疑您在测试中有2到5个堆栈帧?现在假设您的代码将由JBoss部署的JSF组件调用。现在您可能有一个数页长的堆栈跟踪。

也许您可以发布您的测试代码?

2008-11-18 15:54:50

供你参考，我扩展了Mecki做的实验:

method1 took 1733 ms, result was 2
method2 took 1248 ms, result was 2
method3 took 83997 ms, result was 2
method4 took 1692 ms, result was 2
method5 took 60946 ms, result was 2
method6 took 25746 ms, result was 2

前3个和Mecki的一样(我的笔记本电脑明显慢一些)。

method4和method3是一样的，除了它创建了一个新的Integer(1)而不是抛出一个新的Exception()。

method5类似于method3，除了它创建了新的Exception()而不抛出它。

Method6和method3很像，只是它会抛出一个预先创建的异常(一个实例变量)，而不是创建一个新异常。

在Java中，抛出异常的大部分开销是收集堆栈跟踪所花费的时间，这发生在创建异常对象时。抛出异常的实际成本虽然很大，但比创建异常的成本要小得多。

2011-11-05 23:14:35