如何在Java中更快地计算sha256? [英] How to calculate sha256 faster in java?

问题描述

我发现在Java中计算sha256很慢.例如，它比python慢​​.我写了两个简单的基准来计算1GB零的sha256.在这两种情况下，结果都是相同且正确的，但是python时间是5653ms，而java时间是8623ms(慢53％).每次的结果都是相似的，这对我来说是一个重要的区别.

I have found out that calculating sha256 in java is slow. For example, it is slower than python. I wrote two simple benchmarks that calculate sha256 of 1GB of zeroes. In both cases the result is the same and correct, but the python time is 5653ms and the java time is 8623ms(53% slower). The result is similar every time and this is an important difference for me.

如何在Java中更快地进行计算?

How to make the calculation in java faster?

基准:

Java:

import java.security.MessageDigest;
import java.security.NoSuchAlgorithmException;

public class BenchmarkSha256 {

  public static void main(String... args) throws NoSuchAlgorithmException {
    int size = 1024 * 1024;
    byte[] bytes = new byte[size];
    MessageDigest md = MessageDigest.getInstance("SHA-256");
    long startTime = System.nanoTime();
    for (int i = 0; i < 1024; i++)
      md.update(bytes, 0, size);
    long endTime = System.nanoTime();
    System.out.println(String.format("%1$064x", new java.math.BigInteger(1, md.digest())));
    System.out.println(String.format("%d ms", (endTime - startTime) / 1000000));
  }

}

Python:

#!/usr/bin/env python

import hashlib
import time

size = 1024 * 1024
bytes = bytearray(size)
md = hashlib.sha256()
startTime = time.time()
for i in range(0, 1024):
  md.update(bytes)
endTime = time.time()
print "%s\n%d ms" % (md.hexdigest(), (endTime - startTime) * 1000)

结果:

~> java BenchmarkSha256
49bc20df15e412a64472421e13fe86ff1c5165e18b2afccf160d4dc19fe68a14
8623 ms

~> python BenchmarkSha256.py 
49bc20df15e412a64472421e13fe86ff1c5165e18b2afccf160d4dc19fe68a14
5653 ms

java和python版本:

versions of java and python:

~> java -version
java version "1.6.0_26"
Java(TM) SE Runtime Environment (build 1.6.0_26-b03)
Java HotSpot(TM) 64-Bit Server VM (build 20.1-b02, mixed mode)

~> python --version
Python 2.7

推荐答案

您是否尝试过增量输入数据?您可以将messageDigest.update()与字节一起使用，然后使用messageDigest.digest()获得最终摘要?

Have you tried feeding in the data incrementally? You can use messageDigest.update() with the bytes and then get the final digest with messageDigest.digest()?

在内存中分配1GB数组是一个相当庞大的操作.您可能会发现，较小的增量更新最终会更快.

Allocating a 1GB array in memory is a fairly chunky operation. You may find that smaller incremental updates are faster in the end.

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