集合与无序集合与排序向量
[英]set vs unordered_set vs sorted vector
问题描述
I started to wonder what is the exact performance difference between set/unordered_set/sorted vector. 
我开始怀疑set / unordered_set / sorted向量之间的确切性能差异是什么。
Thus, the testing code has been written to compare their process time, so that I can prove following statements that I believe: - Vector is the best at linear search - Unordered_set is best at search because of hashing 因此，已经编写了测试代码来比较它们的处理时间，以便我可以证明以下我认为的陈述：-向量是线性搜索中最好的-由于哈希运算，Unordered_set最适合搜索
#include <string>
#include <set>
#include <unordered_set>
#include <vector>
#include <iostream>
#include <iomanip>
#include <algorithm>
#define WIN32_LEAN_AND_MEAN
#include <Windows.h>
void PrintSep(const std::string& title = "")
{
unsigned half = (78 - title.size()) / 2;
std::cout << std::string(half, '-') << ' ' << title << ' ' << std::string(half, '-') << std::endl;
} // PrintSep
void PrintTable( const char** names, double* times, unsigned count, unsigned colspan = 20)
{
std::cout << std::setw(colspan) << "type" << std::setw(colspan) << "time" << std::endl;
for( unsigned i = 0; i < count; ++i )
std::cout << std::setw(colspan) << names[i] << std::setw(colspan) << times[i] << std::endl;
}
class PerformanceClock
{
private:
LARGE_INTEGER m_begin;
public:
void Begin()
{
QueryPerformanceCounter(&m_begin);
}
double Done()
{
LARGE_INTEGER freq;
QueryPerformanceFrequency(&freq);
LARGE_INTEGER now;
QueryPerformanceCounter(&now);
return static_cast<double>(now.QuadPart - m_begin.QuadPart) / freq.QuadPart;
}
}; // class PerformanceClock
int main()
{
// -------------------- Preparation -------------------- //
// Out inputs
const char* inputs[] = { "yxu45JRZV4tNdd1QCyna", "cnpcDiZMt7meuWlChRLz", "0A5tfP2dLXIz8koq64tL", "5P9bD9NNRtNfTujr5fio", "UZSnYM58N1meWIhY8rM0", "YQijNudHgBQwn6snPRH4", "xYI8H0Do6pi5RLZRECNY", "JRfGxQ2lDAD8gZwd6tQc", "NcCp2rwV4sP9PbiIuSEg", "i2cpej69faREswPiK7nE", "YdJAbj8E6VNQzAy9oeHo", "VNo3YDlyOeUeFA9BGiXm", "tB3D0j26nx610JPOOAIi", "pscv9tApKaxw14NSVlDv", "bFTCBs5o9mg14F6F4Plo", "f7TTZiWC2mMsvEAUGalq", "gxWkNu86l886MfPHdLzq", "tqRcYTo12xwwXVuEi2d9", "3Uz1t6tOQ7NYShZpUNuV", "aD34baQ18TMod6dfJwZA", "U1fSxmx9YuY1bsllgYar", "fhyEset0jR56qor5zjr5", "VEeQNIHipq2vy141rco7", "4LDjHmvLUe13NOr4SANN", "PoOthnu2Ke27bKEyWTDv", "NPWn9J52xHOOd4G5lrXo", "1xjnMU97qRYAxSmqi8TR", "2pj4vj4kVhwX2nkEKdK7", "Q0XJrYvEB0nzzkkFYlp9", "Uzr64OADHWHVHYWJfc77", "m0SKmbXZNiezdO77O8tZ", "kjPuw6dn4J8xwpRiSKuH", "KBaziJyAIyDlmz1Vzbas", "9qk3ZAK8VvKklXETictj", "1AYnAz8yr03j8ZAZ5iei", "SbhYkDkM63FmK3j3qsCz", "OMuqIu1ZOhBqBL6N1ytH", "2vxtMD2p8FcUVGIT0DnR", "AkrdF0Iy59gE7Dp9JNfM", "stH1IAQ0sXnSDaq1HMoW", "DcMMazqQQpbMzLyELrsU", "lJSdcCnUPhRhfzfSAXQF", "0UVIPfSSXA49eUsxe08K", "wnnfBEKK3Qp473xCFrVY", "wIX3U63r6tkWkIED9Rx5", "XLQF7G8scQrtPXPlIxfC", "FAX2XBVwqKzW8JrgJv48", "deaGGIl8KtPg16C8W3MJ", "AerQR94BvVuf5Zh09L6l", "MA4xrjmVJrDGwr8NJAjE", "liNhTpfwHCULOAGqiGGP", "bimfAY9eGu6fJBg6WV1T", "2B5m95znEnZluRif3cXk", "wGRrV7CiyVC8ibUPJpGU", "TTPxXJzvwCHYDnuTS4ze", "PSgfebaPu9X6ELwQFuhD", "6BNO39hyTDCkuVEhotFe", "HUTInCGeZzaw8os8Lj59", "5BulRf0hkaMVD70EWtW0", "Udge2C4oYujCZtJsPxYf", "4zOYA7utkNX4HAiYWJw5", "vGfHy2MLBYkvzodgN5NN", "QoEGnSP3NJEFwg90XsvP", "Z9MLyLnGBYRzoqeFfGnl", "sCKTWuio4aQAYehB6HCg", "rxzz7ct5IUDy52z0Ybid", "JzaimU3EAYScyPzLxnxO", "4EupGy8hKzovI04s9k3r", "9IyD9IyOTgHGs04AphgW", "wIPaqb92cpn3rA9G3xCJ", "NZezYsWHaSRKtZmlqKss", "K9wbueWp8R88e5imzrHt", "IltUiLOPFRNgQ0jOSt6i", "mrMxaogf1on4sfRx2wvv", "RoLK6lfBBvlE0sUT7hmc", "nJuFEfmfapBMtfxhrLLc", "8oltcyHy1WrVmLNlwhXe", "Q2wniXYZEE32fF0VO9KH", "ithGCjUE8j298nVEQ9za", "oJpwIUdXj39iZ5LEI5xP", "w9gXZxxqgEYXyHkv0E1y", "dP8vwnG0EaetT76YEoKG", "9JjVSweM2bhPQ5wfXZCl", "sCGWtGhdGpEpbC3bv35E", "wf33sMLLuWFEr9mQ6chF", "4lp8prBsejxikiyzdXKA", "zTylzgjl0CT7nO8SkXkm", "Uz0mc5OjfeXS7HkvuqeT", "VIHlV5xgEkiEZhROZ6P9", "vOM2TmFVULfdUJOUg46i", "arZEAcfaQBjfrOffogxd", "w4uBjsZ3rtLFe4PccEey", "yNT0fvxWXVfoSlkVhJwS", "Je7rcoWyxdh82fJGFkNI", "XRlbaICPD9tgHS4QiCoK", "7Vtkdx5fhGM14xRj4rEU", "Q9izPLm7IdVDP64j2XQg", "vp0IJz5UlMunNPuKc1pN", "69zhS3u7fylfFivKagx0", "lr1PwSfqVqNSucWJlGfA", "3iC5lr4tMVviJ2c2kmau", "JJQdbqP2ZjsdMJCdBkFi", "SoSUhRDhOvhArYUtRhtX", "x4fL4SEmo0QiuwAjjj4k", "oI4mbLwhg1QSWVG66SGr", "U2CTAPb1OkknT9pWXBDh", "Pk6TEh0IQmjO8EQP1agb", "o7JwwAjC2LGztObMw7qD", "UcvXFYRVJGqR0lejzvX0", "UqN6wQVfkJnPHzL4WiX6", "nMVsuJNNxXDIYzxMEfvp", "MhYxQdpTV3Ohpr5RAMTx", "HJ8KmYdSqKRh9fz6zlby", "SfeDgzAUQaxiWFiuY08K", "tgJuCx1UaaHVcKo1IPlm", "X6VUsOeAsFTkco7imijI", "yVEOPiM6DOB1UYVhhdk8", "fZRbVxqQFkSr0FRifnCN", "7Izg2Uie5JJGHlG9n7AI", "K7KTsWgcrhSHTTiRSrxt", "Kw0lhrJyE2TzQ2MoqA36", "KTZKnzmPwOmpDm9RhPL0", "XddDsauu6KYBxgR7QgOh", "x577aT0lJuj0AYFAk0TW", "dGlFYstHsmmEsnyisYek", "LLc0mK0pc92AudxCDgO7", "UFCuUiloKuVDAGBdQDnY", "icuNcxGj1xNRkackFEUJ", "WmASq7nN85SlcydJYMDe", "FuCxoPVfxvp74qXVHtdE", "aMPEltF2gFFpwhllz3NS", "Fd1YBdagkYrgcVzZ993f", "P3vEWtm49IoexbAVfWjH", "dPcjFfijFPP5RBPNfAjw", "r1KxB5TgKxbZgIh7n8Kb", "gnEGgTPg0OOtIVsTjbGz", "CDzf6PXyrdXpcG9yOb9k", "nwep76VGfJVvzWrm2ci3", "lH17zVrR57AF4eM6OQQL", "rt0hvdhbYM4MZQ2MNQCA", "XjUwspBBhyXxJ3A4sZcW", "TO66uuWsDb18XJgpZxx9", "PqoTmpxTI526jV46CeD4", "wowLbTpF002PgJeV3NOA", "fVFaW9edrWmj9DagF9Zl", "2wKCKRmuUHXl25H1vzAM", "2iko2TR11skm4CjE2iuD", "hGSyJuZdvSD882TcCx7l", "0aSM7AgV5pvxYYS011Xm", "gIKHT5wi33d2dHglU3r4", "tPuRqjFsGCEQRjVsVt4n", "s1yuSwWO1sKvvD7ijGDv", "Xy2tVRxiRhLpRQ67cgBe", "dN0ZtJWX47Ry974J8grz", "4oALvEi4rsE8q4XV9ibo", "QA3fwYSPrxewIwhl5M33", "MKxUjD5VBqOCBcOSgskP", "i4SUZJ7XjJYHuT1Myd6S", "TAmdTTSwiCTyy33nNKug", "rcRjMeBQMssJZPLTX7Eo", "YWszqu7Jk5qGznZVyRkU", "zkSXYxFFX1u2TPzzekFr", "iwpWWlMTQiin1gP1B725", "dguvfNWyX1F9Kq8CUmio", "mmweJmmGCXfzkiWvrIAf", "0jqq0zp3nI2w3iIG01ev", "I4bVHz3KajVm6f6QPAXS", "QrQtMNo3pGGZjQtYJvQm", "IZyZbFhK1ou9Vs6hU5XT", "JKjlvweHcnxdFtUVsCNu", "lGMqzOFQrq4vvRDujiCW", "zjO04wpUHtUn67bETAdg", "n7ysAW4ml7S8BhwE9ubO", "IjRGqKzqLimHeaTyffcO", "QL25AdNDTwuze9JWNjkD", "q948zpLcMQX0ImQyVaiO", "dUgKdtOzKiiLqONbOkIp", "e4X4df2DzjFzv2Qk4OXw", "d2L8oJgGpIs0qkycSMxN", "kqIYJQDnrGo22j1jA7cF", "Y7gfGAsXWmRNLqSJr0gy", "tZdaBU23aVFajefzyLOF", "qZvD1NMV1uwUD0hgawmw", "sdPIN2HTZE6t2b9Djz7s", "upAwEn0o4KSNdahAC4DW", "Sahw60orUZ8jfNg3t5tC", "otAVTH99oIm0pmLjpxuq", "5s9zcaoMQPJaxYZIizLr", "0INz5juLXNS1qz0S5ZBD", "sdfeGOkVyogYIGlZuKQR", "mrDeLJd2vhobT5pkmHUg", "X4fz8JUHXym1ReuSIfl7", "qW60yaRPSvxnEe93hxsL", "exmEIAOI9PRZFX2Q2ahQ", "PKgWxvU1QFhyrnBkzoon", "OCZBJ6WSnfHz5JN8hrSg", "BPRi6d3TmbAdC2kASDGv", "jCwBs3QNbLLL1BS8ZsWY", "VHmUgSk71PzHpsaVEQaP", "SSqA6435huQqguErI5Om", "j8EWadtp9N09Kg3TionW", "paUS1pfKLqvvRdCatNEA", "U4m0QB6bhzLwcJw8PWUd", "FzMv6nkQOZZ08rbnZzfQ", "JDX4rjAgRIj9484NnN0B", "t33jIgbYP7uK7aU4uPqf", "Jim3d7AbanwSA4dsgYTf", "s79GzWjCnNzCqMP02uXR", "pwV3gzOWRPInyIRab3hl", "KSkC3a1NysnHXmg3hz00", "48RohG5tE4mD1FW6gDxO", "edySUYmPSAWb2SNABx3i", "ZewnjFRsNF2P7FsXFG1J", "P3MKpt0pjsWjCxmzFH1k", "OM9ZkaXWStkeD2D44DQr", "5uLXwJks9bhxGbkbx3PQ", "uwyllRDSx3Rdk4tkE2XK", "CebMT43q8FUOZwC9I3hD", "OP99Uiiau2L86Jb1HLDt", "mNStmnQK57wNhY1xgiWr", "bkqIbxcsGn7a3oUsDUz9", "8B6Nh2fr32FDxa5Zk8EO", "WmoIHtvZBVbJznqn6MDY", "WAWNAksIY9TloCHPMdDp", "h0X2FSzQBGfg858Zr5lI", "U4guPLRmEiWpmwkVfXsk", "07PY0E8w0ynsJJJG6dTT", "1EwuMIgLzZ4QOLSz9KKK", "ZbgGBA5PkbWOAgKa6U3U", "2YP3z0RaIinIJHndQvJ9", "VuTVO86yXm26C1ZC42cv", "czszyFqLJelsDtkB1wGm", "JBSSs9Gq2z1ho5vxKa7b", "WxzstpP8LNFek2sNVO7I", "SdR4zJAFYIUC6Ox7F5Ao", "bqeQdAHhSqq9CMH466EU", "3osfIgWhT0YYWHLuFp6m", "OsYQp5s01CyQsAxxyJ5z", "QmdGehSItOI9ytDJx2tn", "RS7NTVDlt0ae7mG2fNu2", "b70uAiLvD8lWmD4LFhoq", "qYA1LVo2Zk9Yka5qJ69M", "2QteJBZyvfLu4QnwuXZp", "spE7TmutGb9sF3l1WdzK", "wx7fwsIzuPHCPoJMm8Zi", "UTXxyVIFT1MP3piFOj9E", "Sv6X1tpRqaIFKVvOjpy0", "zkCCginO8RH1IQ5gxP9n", "lpzHz0JOAKDEbNzWOLHi", "ga9ThbxxkMjZBISnpM4Z", "XLj9Dc3gI3zspCQUqLAy", "I4B6seBrJYopMfIJPRg8", "y7oFbP2hnfLIx7Loufzb", "qwENxA8OA4xGHB2Y7T7z", "TCJca2HMVXLoBLLTQaMm", "Nm0YLJ6zdfj5EkdYReJR", "04rQlakEagJimcZi0xZF", "5AotlztHKO5FCed44T51", "IIhf1YB3yq0MfKBMDiNJ", "gI8dJJVL8oysEkUROyFF", "ls3nHBIMOdtdd68wSJ8B", "sXt2Pgcq5GLpPRXPDEfX", "RRGLCAXtrjBMtj1UoWWP", "N6GGDjSpvxPrtPFtiBuG", "KM7aQq96bzzokQSkXy2L", "THGWpDuXfiq7ydRtYzGN", "4EDerDQt1cKbzO16436h", "76rXLODN8Ik5KjPKipo2", "k3HKxP0Ek5jSviq8F0Z9", "Tt6ax6fUn2ifsfBoLuZJ", "vuChGzc9hlKnerW0FTS7", "osXjEnlYYN2uLShpDgPa", "kyRWc0KCtFBLtFXHTYbG", "ArJSG0mJY2gUHSJ8MkXs", "nQea6CLRuer8f6clqd3T", "7WIwE0fUplMqQ8HDJyl9", "JoHJzGl8hLk1b2yiea3b", "8AW3Ip8YLf1wdRZkFr0p", "EwyYE9FdzBppUhpmEQkY", "ULpmmACM04oxA89Of4vR", "1ETapZcpVUCMkKY0AAcx", "9u8SaUc6mUethl73dyEN", "SI2EJys3uWiAf93l6G3X", "dc5sWttEbc0ixIdw1YqV", "QV3FRwytDAA3TCsy4jiQ", "KO89nRNbn1sb9QqAnalZ", "fJtl4TSxF3nkStQSZjKV", "W3Zv9VIIfVVDfHYB1MZJ", "Sru5BIe1FBt55353fZBR", "8hbYFsKp0a69zFf8XfME", "SgAxktG5TWZgdT75qlnk", "IlB4M3cfYRsEacB5mxKQ", "v2eSPv7LNCZpJvaIxhNq", "qcfHQFRTaf8hFUC1uGeM", "m309qZaNJJdKVbkqIh0p", "LPRXLy1JxXAgjOpD4SOh", "V3JDPm9ZT7xEF5TGjmQ5", "pm8asJdQlQYP3GAQGg7B", "RNg45uLlAynFdQEiAd1z", "MsBlcLHaoRvarn2Hg9cv", "sptoqa8m9MQoo0Qdv6W5", "LQBNbdGTPe8wd1RnOWL3", "AzzwJ2xV8hy3CZQrwaDJ", "ZcIsPuJn76TKGmTW2uc5", "412GgdvECB1N7g2Q136N", "XLwiWSaE956lBioeusMg", "C8Ark7jlgdKLbw79v1Ga", "Rpgw0jCzvOZywBS1R2cX", "nhXbq1ZmUSnUbBOWmCss", "0EngfF85ZVCv42Gd8LiZ", "JmCOkPve5IWSe3AaN7HM", "iHMI9zUHEucjS64Zq65T", "iRZQmbtj7mIRxYoNXNCW", "87S4t3SekcuxRFLm4Vj8", "pq0iCznEdH2yqryur0ut", "MZ8JUEXA4NvSFJVvagSo", "wYh7K2VqClA0NT2YNz0x", "lEXFwt1QvyLorSrSDxtJ", "Jo8ZBFuR4AdGAlSPrEra", "5OFujFQGmkp7yFpuetg3", "AdBtAYEvesYLPEBQeYve", "yDh3QJ34463eemMIKuI6", "JpIOLAZKKVRw4W83z45f", "0pNXAVcaEnx1xR5MuCB5", "vCj8Lf24T7KfnqDPjLw3", "YOLVtf9CAGxusaJ41VNZ", "82Y5ryW3Li729CEchqti", 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"qUOpBXvkdKZe8OsRovc8", "VreNCHBV3pp12fk8Ax6I", "tlgHjVlArf2RagO3jBPZ", "kUjymJiFXv52PgpDcY9z", "5EcD56ZTtObcOq5BxZJt", "wpuNhRrKaUj5yd0QbnHZ", "AIYwGTo9Yt19mLaTkzNI", "zpaJZRLZiMHmhOQ6Jy0j", "6On0n4mUeK4Ics8Q725j", "X560iPqFqijgxv7FXiUn", "HyljDZCwDOKb71iHV2Tm", "kEzYhJ0k8KASaMamU3I4", "hfIuWLaeZtD6hUy8umMw", "87wS1xCo3wZlxPyCO1fj", "5Q6jJZvKQgaI5JgEZLjX", "vmGReyRElWHslAjFGPsp", "kSn4oUIWAfSev6MeaNym", "5ltdUwNsFaV6gHoxgCMI", "zFzljs3uCXXIOBlXTFjm", "r0cGBofX7AWMyQ80ciyC", "J0xgBJOhM1ApHj9ccP8w" };
// Our candidates
std::set<std::string> my_set(inputs, inputs + _countof(inputs));
std::unordered_set<std::string> my_unordered_set(inputs, inputs + _countof(inputs));
std::vector<std::string> my_sorted_vector(inputs, inputs + _countof(inputs));
std::sort(my_sorted_vector.begin(),my_sorted_vector.end());
// Time Utility
PerformanceClock clock;
// Output Formatting
std::cout.precision(std::numeric_limits<double>::max_digits10);
std::cout.setf(std::ios::fixed);
const char* names[] = { "set", "unordered_set", "sorted vector" };
double times[] = {0,0,0};
// -------------------- Binary/Hash Search -------------------- //
PrintSep("Binary/Hash Search");
// Find all from set
clock.Begin();
for( const char* s : inputs )
my_set.find(s);
times[0] = clock.Done();
// Find all from unordered_set
clock.Begin();
for( const char* s : inputs )
my_unordered_set.find(s);
times[1] = clock.Done();
// Find all from sorted vector
clock.Begin();
for( const char* s : inputs )
std::lower_bound(my_sorted_vector.begin(),my_sorted_vector.end(), s);
times[2] = clock.Done();
PrintTable(names,times,3);
// -------------------- Linear Search -------------------- //
PrintSep("Linear Search");
// Find all from set
clock.Begin();
for( const char* s : inputs )
std::find(my_set.begin(),my_set.end(),s);
times[0] = clock.Done();
// Find all from unordered_set
clock.Begin();
for( const char* s : inputs )
std::find(my_unordered_set.begin(), my_unordered_set.end(), s);
times[1] = clock.Done();
// Find all from sorted vector
clock.Begin();
for( const char* s : inputs )
std::find(my_sorted_vector.begin(),my_sorted_vector.end(), s);
times[2] = clock.Done();
PrintTable(names,times,3);
return 0;
} // int main()
Questions: 问题：
Do statements sounds right?
陈述听起来正确吗？ Is this testing valid?
此测试有效吗？ will the test be affected by compiler setting?(under visual studio) Will the testing be affected by compiler reordering, optimizing instructions? 测试会受到编译器设置的影响吗？（在Visual Studio中）测试会受到编译器重新排序，优化指令的影响吗？ What other test cases needed to be considered other than binary search and linear search?
除了二进制搜索和线性搜索，还需要考虑其他哪些测试用例？
2 个解决方案
解决方案1
6 已采纳 2014-10-23 06:53:01
Do statements sounds right?
- Vector is the best at linear search
- Unordered_set is best at search because of hashing
Yes, vector's best at linear search due to contiguous memory usage / better cache utilisation, less pointer chasing. 是的，由于连续的内存使用/更好的缓存使用率，更少的指针追踪，向量在线性搜索中表现最佳。 It's also best at binary and interpolation (also called extrapolation) searching for those reasons plus support for having the fastest possible random access (ie [n] ), but getting/keeping the elements sorted beforehand can be more expensive than with many other containers. 由于这些原因，它在二进制和内插法（也称为外推法）搜索上再加上最好的随机访问（即[n] ）支持也是最佳的选择，但是事先获得/保持元素的排序可能比使用许多其他容器昂贵。
unordered_set requires hashing keys, key value equality checks, and can have nasty worst-case behaviour for poor hash functions or maliciously engineered data sets, but in general - and increasingly so as the number of elements grows - it is better at searching for a specific value than a vector . unordered_set需要散列键，键值相等性检查，并且对于不良的散列功能或恶意设计的数据集可能具有令人讨厌的最坏情况的行为，但是总的来说-随着元素数量的增加，这种情况也越来越好-搜索特定的比vector 。
Is this testing valid?
No. There are lots of issues with it... for example, QueryPerformanceCounter isn't reliable on most Windows PCs unless you bind the process to a specific core, it doesn't discount time your process is suspended while other code runs (if you pick the wrong core to pin yourself to - system housekeeping, drivers, interrupt handlers as well as other processes). 否。它存在很多问题……例如， QueryPerformanceCounter在大多数Windows PC上都是不可靠的，除非您将进程绑定到特定的内核，否则不会减少进程在其他代码运行时挂起的时间（如果您选择了错误的核心来固定自己-系统管理，驱动程序，中断处理程序以及其他进程）。 Further, there can be cache warming effects so it's a good idea to repeat benchmarks in different orders before trusting the results. 此外，可能会有缓存预热的影响，因此最好在信任结果之前以不同的顺序重复基准测试。 Results can also reflect things about the specific key types, container sizes etc. that make the results inapplicable to other data types/sets. 结果还可以反映有关特定键类型，容器大小等的信息，从而使结果不适用于其他数据类型/集。
will the test be affected by compiler setting?(under visual studio) Will the testing be affected by compiler reordering, optimizing instructions?
Of course. 当然。
What other test cases needed to be considered other than binary search and linear search?
Sorted vectors allow interpolation searches, which can very occasionally be usefully faster (eg 2-3x). 排序后的向量允许插值搜索，这有时会非常有用（例如2-3x）。 Insertion times, erase times etc. may or may not be relevant depending on your needs. 根据您的需要，插入时间，擦除时间等可能无关紧要。 Thread safety. 线程安全。 Data types and hash functions (including whether you need resistance to maliciously collision prone keys). 数据类型和哈希函数（包括是否需要抵抗容易发生冲突的恶意密钥）。 All depends on the totality of what your program's doing with the data. 所有这些都取决于程序对数据进行处理的总体情况。
解决方案2
4 2014-10-23 06:43:10
First, the loops in your code have no side effects, so the compiler is allowed to optimize them out completely, though it didn't happen for me on VS2013U3. 首先，代码中的循环没有副作用，因此尽管在VS2013U3上对我而言，这没有发生，但允许编译器对其进行完全优化。 You should add some side effect which doesn't affect performance much, for example like this: 您应该添加一些不会对性能产生太大影响的副作用，例如：
size_t len = 0;
clock.Begin();
for (const char* s : inputs)
len += my_set.find(s)->length();
times[0] = clock.Done();
std::cout << len << std::endl;
Second, the dataset used is too little, so the measurements can be inaccurate. 其次，使用的数据集太少，因此测量可能不准确。 You should either make dataset bigger or repeat the search more times (and you may probably want to do both because the effect of these actions is different). 您应该使数据集更大或重复搜索更多次（并且您可能想要同时执行这两项操作，因为这些操作的效果不同）。
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