├── Lab1 ├── README.md └── src │ ├── An_example.png │ ├── ExampleInput.png │ ├── Input_file.png │ ├── Sudoku │ ├── Lab1.sh │ ├── Makefile │ ├── README │ ├── answer1 │ ├── answer1000 │ ├── answer10000 │ ├── answer_group │ ├── main.cc │ ├── mythreadpool.h │ ├── neighbor.cc │ ├── sudoku.h │ ├── sudoku_basic.cc │ ├── sudoku_dancing_links.cc │ ├── sudoku_min_arity.cc │ ├── sudoku_min_arity_cache.cc │ ├── taskqueue.h │ ├── test.cc │ ├── test1 │ ├── test1000 │ ├── test10000 │ ├── test_group │ ├── threadpool.cc │ └── threadpool.h │ ├── Sudoku_answer.png │ ├── Sudoku_puzzle.png │ ├── Wrong_Example.png │ ├── answer_group.png │ ├── test_group.png │ ├── where_ext4.png │ ├── 图2-1.png │ ├── 图2-2.png │ └── 图2-3.png ├── Lab2 ├── README.md └── src │ ├── get_404_curl.png │ ├── index.png │ ├── index_curl.png │ ├── not_implemented.png │ ├── not_implemented_curl.png │ ├── post_404_curl.png │ └── post_curl.png ├── Lab3 ├── README.md └── src │ ├── KVStoreOverview.jpg │ ├── KVStoreOverview.pptx │ ├── coordinator_sample.conf │ ├── participant_sample.conf │ └── two-phase-commit.png ├── Lab4 └── README.md └── README.md /Lab1/README.md: -------------------------------------------------------------------------------- 1 | # Lab 1: “Super-fast” Sudoku Solving 2 | 3 | Enter in the folder you have cloned from our lab git repo, and pull the latest commit. 4 | 5 | `git pull` 6 | 7 | You can find this lab1's instruction in `Lab1/README.md` 8 | 9 | All materials of lab1 are in folder `Lab1/` 10 | 11 | ## 1. Overview 12 | 13 | Implement a Sudoku solving program, using multiple threads or multiple processes, running on a single machine. Try to **utilize all your CPU cores** and make your program **run as fast as possible**! 14 | 15 | ### Goals 16 | 17 | * Practice basic parallel programming skills, such as using multiple threads/processes; 18 | * Get familiar with Unix OS environment development (eg., file I/O, get timestamp); 19 | * Get familiar with source code version control tools (git), and learn to collaborate with others using github; 20 | 21 | ## 2. Background 22 | 23 | ### 2.1 Introduction to Sudoku 24 | 25 | Sudoku (originally called Number Place) is a logic-based combinatorial number-placement puzzle. 26 | 27 | You are given a 9×9 board of 81 squares logically separated into 9 columsn, 9 rows, and 9 3×3 subsquares. The goal is, given a board with some initial numbers filled in (we call it a **Sudoku puzzle**), fill in the rest of the board so that every column, row, and subsquare have all the digits from 1 to 9 and each digit appears only once (we call it a **Sudoku solution**). 28 | 29 | 30 | An example Sudoku puzzle: 31 | 32 | Sudoku 33 | 34 | An example Sudoku solution to above puzzle: 35 | 36 | Sudoku 37 | 38 | ### 2.2 Some useful resources 39 | 40 | If you have no idea about what algorithms can be used to solve Sudoku puzzles, we suggest you read [this](https://rafal.io/posts/solving-sudoku-with-dancing-links.html). To simplify your work, we have provided a simple [implementation](src/Sudoku/) `(Lab1/src/Sudoku`) of 4 Sudoku solving algorithms (some are slow, some are fast), but without using multiple threads/processes. The two files *test1* and *test1000* contain many puzzles for you to test. 41 | 42 | Of course, you are always encouraged (not mandatory) to implement those algorithms by yourselves and even your own algorithms (if you have time). 43 | 44 | ## 3. Your Lab Task 45 | 46 | ### 3.1 Write a program 47 | 48 | Implement a program which satisfies the following requirements: 49 | 50 | #### 3.1.1 Program input and output 51 | 52 | ##### **3.1.1.1 Input** 53 | 54 | 1. Your program **must** have no arguments during start. Attention, your program must be called *sudoku_solve*, just typing `./sudoku_solve` and your program will run correctly. 55 | 2. But after start, your program should be able to read multiple strings from ***stdin***, where each string is separated by a line-break. Each string is a **name of a file**, which contains one or more Sudoku puzzles that your program is going to solve. 56 | 3. In the input file, **each line** is a Sudoku puzzle that needs to be solved. Each line contains 81 decimal digits. The 1st-9th digits are the 1st row of the 9×9 grid, and the 10th-18th digits are the 2nd row of the 9×9 grid, and so on. Digit 0 means this digit is unknown and your program needs to figure it out according to the Sudoku rules described above. 57 | 58 | **Example contents** 59 | 60 | Input file 61 | 62 | **Example input** 63 | 64 | ``` 65 | ./test1 66 | ./test2 67 | ./test3 68 | ``` 69 | 70 | ##### 3.1.1.2 Output 71 | 72 | For each test case, you just only output the Sudoku solutions. And don't forget, the output order should correspond with the input order of Sudoku puzzles. 73 | 74 | **Example output** 75 | 76 | ``` 77 | 312647985786953241945128367854379126273461859691285473437592618569814732128736594 78 | 693784512487512936125963874932651487568247391741398625319475268856129743274836159 79 | 869725413512934687374168529798246135231857946456319872683571294925483761147692358 80 | 693784512487512936125963874932651487568247391741398625319475268856129743274836159 81 | 364978512152436978879125634738651429691247385245389167923764851486512793517893246 82 | 378694512564218397291753684643125978712869453859437261435971826186542739927386145 83 | ``` 84 | 85 | **Output order requirement** 86 | 87 | In the example of input above, the order of filename entered is `./test1`, `./test2` and `./test3`. So, you should output the solutions of Sudoku puzzles in file `test1` firstly, then file `test2` and finally file `test3`. Needless to say, the solutions should be outputed in the same sequence as the puzzles are inputted in. 88 | 89 | In the example of output above, the 1st line is the solution of Sudoku puzzle in file `test1`. After that, the 2nd line and 3rd line are the solutions of 1st and 2nd Sudoku puzzles in file `test2`. Finally, the 4th line, 5th line and 6th line are the solutions of 1st, 2nd and 3rd Sudoku puzzles in file `test3`. 90 | 91 | #### 3.1.3 Implementation requirements 92 | 93 | ##### 3.1.3.1 Basic version 94 | 95 | Your program should be able to: 96 | 97 | 1. Accept **one** input file name, and the size of the input file is smaller than 100MB. 98 | 2. Successfully solve the puzzles in the input file, and output the results in the format described before. 99 | 3. Use multiple threads/processes to make use of most of your machine's CPU cores. 100 | 101 | \[Tips\]: 1) Use event queue to dispatch tasks and merge results to/from worker threads. 2) Dynamically detect how many CPU cores are there on your machine, in order to decide how many threads/processes your program uses. 3) Be careful about the contention among multiple threads/processes 102 | 103 | ##### 3.1.3.2 Advanced version 104 | 105 | Your program should be able to: 106 | 107 | 1. Complete all the requirements in the basic version. 108 | 2. Accept **any number of** input file names, and the size of input file can be **any large** (as long as it can be stored on your disk) 109 | 3. When the program is solving puzzles in the previously input file(s), the program can **meanwhile accept more input file names from *stdin***. 110 | 111 | \[Tips\]: 1) Use a dedicated thread to accept input; 2) To avoid consuming all the memory, read different parts of the file into memory and solve them one by one; 3) You are encouraged to try more optimizations such as cache coherency processing. 112 | 113 | ### 3.2. Test script 114 | 115 | You can test your program using the script (Lab1.sh) that comes with this Lab. 116 | 117 | ##### 3.2.1 Notes 118 | 119 | 1. You can use the script on most Linux environments 120 | 121 | 2. Requires support for the **screen** command 122 | 123 | ​ You can use "***which screen***" to see if the screen command is already installed, if not you can refer to the following command download: 124 | 125 | ```shell 126 | ubuntu: apt-get install screen 127 | 128 | centos: yum install screen 129 | ``` 130 | 131 | 3. The executable file can only be named **sudoku_solve** 132 | 133 | 4. sudoku_solve executable file, Lab1.sh script should be placed in the same directory 134 | 135 | 5. If your file system is not in **ext4** format, the performance test may not succeed and only the basic test can be performed. 136 | 137 | ​ You can see which path mounted ext4 disks in the following way: 138 | 139 | ```shell 140 | df -h --type=ext4 141 | ``` 142 | 143 | Sudoku 144 | 145 | 6. The script will generate a subfolder with Basic(Advanced)\_Result and Basic(Advanced)_Answer, Result is your output and Answer is the reference output. At each run, the script will delete the two files , so if you need this data, please copy it first before running the script. 146 | 147 | 7. The time taken for script presentation is relative, each time there will be a relatively fixed processing time. For example, your program used 1300ms to solve the sudoku problem, but the script preparation took 800ms. eventually, the script will show 2100ms. Also everyone's configuration and performance is different, resulting in different times, which means you only need to keep optimizing on your machine, not comparing it with others. Please be assured that the same environment will be used for the final scoring. 148 | 149 | 8. (**Very important**) If you want to get a high score (script test), it is better to flush the data in the buffer in time. 150 | 151 | ##### 3.2.2 Script Usage 152 | 153 | ```shell 154 | sudo ./Lab1.sh test_group answer_group 155 | ``` 156 | 157 | Parameter explanation： 158 | 159 | ​ The script takes two parameters 160 | 161 | ​ Para1(For example: test_group ) : A file that create by yourself. This file is placed in the path of the different test files. For example, if the test file group contains: . /test1 . /test1000 two input test files, the structure is as follows： 162 | 163 | Sudoku 164 | 165 | ​ Para2(For example: answer_group) : A file like parameter 1 but with the path to the answer to the test file. For example, if the test file group contains: . /test1 . /test1000 two input test files, the answer file group contains: . /answer1 . /answer1000 , and the structure is as follows： 166 | 167 | Sudoku 168 | 169 | You can create your own test files and put in the combinations you want. 170 | 171 | Note that this output below means that you are missing a line break at the end of your test file, which will not be recognized. Of course, the path of your answer file should be in the same order as the test path. 172 | 173 | Sudoku 174 | 175 | An example： 176 | 177 | Sudoku 178 | 179 | ## 4. Lab submission 180 | 181 | Please put all your code in folder `Lab1` and write a `Makefile` so that we **can compile your code in one single command** `make`. The compiled runnable executable binary should be named `sudoku_solve` and located in folder `Lab1`. If you do not know how to write `Makefile`, you can find a simple example in `Lab1/src/Sudoku`. Please carefully following above rules so that TAs can automatically test your code!!! 182 | 183 | Please submit your lab program and performance test report following the guidance in the [Overall Lab Instructions](../README.md) (`../README.md`) 184 | 185 | ## 5. Grading standards 186 | 187 | 1. You can get 38 points if you can: 1) finish all the requirements of the basic version, and 2) your performance test report has finished the two requirements described before. If you missed some parts, you will get part of the points depending how much you finished 188 | 2. You can get 40 points (full score) if you can: 1) finish all the requirements of the advanced version, and 2) your performance test report has finished the two requirements described before. If you missed some parts, you will get part of the points depending how much you finished. 189 | 190 | -------------------------------------------------------------------------------- /Lab1/src/An_example.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/lxthnu/CloudComputingLabs/74dcd2c1e4dd5d97615173a6aaedc7927bac9c07/Lab1/src/An_example.png -------------------------------------------------------------------------------- /Lab1/src/ExampleInput.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/lxthnu/CloudComputingLabs/74dcd2c1e4dd5d97615173a6aaedc7927bac9c07/Lab1/src/ExampleInput.png -------------------------------------------------------------------------------- /Lab1/src/Input_file.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/lxthnu/CloudComputingLabs/74dcd2c1e4dd5d97615173a6aaedc7927bac9c07/Lab1/src/Input_file.png -------------------------------------------------------------------------------- /Lab1/src/Sudoku/Lab1.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #~/test_data/advanced_test (include test1 test1000) 3 | if [ $# != 2 ] ; then 4 | echo "参数数量不对" 5 | echo "参数1:包含测试文件组的文件 例如 \"test_group\" (其中可能包含 ./test1 ./test1000) " 6 | echo "参数2:包含测试文件组的文件 例如 \"answer_group\" (其中可能包含 ./answer1 ./answer1000) " 7 | echo "完整命令列如 : $0 test_group" 8 | exit 1; 9 | fi 10 | 11 | test_data_txt=$1 12 | answer_date_txt=$2 13 | GROUP_NAME="group1" 14 | Current_Folder=$(cd `dirname $0`; pwd) 15 | Record_Time="${test_data_txt}_Folder/Record_Time.csv" 16 | Error_Teams="${test_data_txt}_Folder/Error_Teams.csv" 17 | 18 | if [ -e ${test_data_txt}_Folder ];then 19 | echo "${test_data_txt}_Folder 无需创建，已存在" 20 | else 21 | mkdir ${test_data_txt}_Folder 22 | echo "创建${test_data_txt}_Folder" 23 | fi 24 | 25 | touch ${Record_Time} 26 | 27 | echo "Team_Name,Use_Time(ms),Creat_Time,Modify_Time" > ${Record_Time} 28 | 29 | #$1 team_name $2 Result_name $3 ${Answer_Line} $4 diff_line 30 | Cul_Run_Time(){ 31 | # stat $2 32 | 33 | INODE=$(ls -i $2 |awk '{print $1}') 34 | FILENAME=$2 35 | 36 | string=$(pwd) 37 | array=(${string//\// }) 38 | root_Directory=${array[0]}; 39 | 40 | DISK=$(df -h |grep ${root_Directory} |awk '{print $1}') 41 | 42 | # 文件系统非ext4则退出 43 | [[ "`df -T | grep ${DISK} |awk '{print $2}'`" != "ext4" ]] && { echo ${DISK} is not mount on type ext4! Only ext4 file system support!;exit 2; } 44 | 45 | Create_Time_t=$(sudo debugfs -R "stat <${INODE}>" ${DISK} | grep "crtime:" | awk '{printf $7}') 46 | 47 | Access_Time_t=$(stat $2 | grep "Access: 2" | awk '{printf $3}') 48 | Modify_Time_t=$(stat $2 | grep Modify | awk '{printf $3}') 49 | # echo "Access_Time_t:$Access_Time_t Modify_Time_t:$Modify_Time_t" 50 | echo "Create_Time_t:$Create_Time_t Modify_Time_t:$Modify_Time_t" 51 | # Access_Time=$(date -d ${Access_Time_t} +%s%N) 52 | Create_Time_t=$(date -d ${Create_Time_t} +%s%N) 53 | Modify_Time=$(date -d ${Modify_Time_t} +%s%N) 54 | # echo "$1 A is $Access_Time M is $Modify_Time" 55 | # Use_Time=`echo $Modify_Time $Access_Time | awk '{ print ($1 - $2) / 1000000}'` 56 | echo "$1 Cr is $Create_Time_t M is $Modify_Time" 57 | Use_Time=`echo $Modify_Time $Create_Time_t | awk '{ print ($1 - $2) / 1000000}'` 58 | # Check_Answer $1 $2 $3 59 | echo -e "\033[32m $1 Use_Time: $Use_Time ms \033[0m" 60 | 61 | Team_Answer=$(cat $2 | wc -l) 62 | if [[ ${Team_Answer} -ge $3 ]];then 63 | echo -e "\033[32m Up to standard Team_Answer:${Team_Answer} Answer_Line:$3 \033[0m" 64 | else 65 | echo -e "\033[31m Not up to standard Team_Answer:${Team_Answer} Answer_Line:$3 \033[0m" 66 | echo "$1 Not up to standard Team_Answer:${Team_Answer} Answer_Line:$3" >> ${Error_Teams} 67 | fi 68 | 69 | right_rate=$(echo "scale=2;1 - $4 / $3" | bc) 70 | # echo "$1,${right_rate},$Use_Time,${Team_Answer},$3,,$Access_Time_t,$Modify_Time_t" 71 | # echo "$1,${right_rate},$Use_Time,${Team_Answer},$3,,$Access_Time_t,$Modify_Time_t" >> ${Record_Time} 72 | } 73 | 74 | Basic_Test(){ 75 | # $1 team_name $2 test_data_file_name $3 answer_date_file_name 76 | test_data=$(cat $2) # ./test1 kml 77 | Answer_Line=0 78 | Exe_Prog="" 79 | cd ${Current_Folder} 80 | Result="${test_data_txt}_Folder/Basic_Result" 81 | Answer="${test_data_txt}_Folder/Basic_Answer" 82 | 83 | if [[ -e sudoku_solve ]];then 84 | echo "找到执行文件sudoku_solve" 85 | Exe_Prog='sudoku_solve' 86 | elif [[ -e sudoku ]];then 87 | echo "找到执行文件sudoku" 88 | Exe_Prog='sudoku' 89 | else 90 | echo "未找到命名为sudoku或sudoku_solve的执行文件" 91 | echo "进行编译" 92 | make 93 | if [[ -e sudoku_solve ]];then 94 | echo "找到执行文件sudoku_solve" 95 | Exe_Prog='sudoku_solve' 96 | elif [[ -e sudoku ]];then 97 | echo "找到执行文件sudoku" 98 | Exe_Prog='sudoku' 99 | else 100 | echo "编译后仍未找到相应执行文件" 101 | exit 1; 102 | fi 103 | fi 104 | 105 | if [[ -e ./${Answer} ]];then 106 | rm ./${Answer} 107 | touch ./${Answer} 108 | else 109 | touch ./${Answer} 110 | fi 111 | sudo chmod 777 ./${Answer} 112 | screen -S $1 -X quit 113 | screen -dmS $1 114 | 115 | if [[ -e ./${Result} ]];then 116 | rm ./${Result} 117 | touch ./${Result} 118 | else 119 | touch ./${Result} 120 | fi 121 | 122 | screen -S $1 -X stuff "stdbuf -oL ./${Exe_Prog} > ./${Result}^M" 123 | while read -r test_data 124 | do 125 | Answer_Line=`expr ${Answer_Line} + $(cat ${test_data} | wc -l)` 126 | screen -S $1 -X stuff "${test_data}^M" 127 | done < $2 128 | 129 | while read -r answer_data 130 | do 131 | cat ${Current_Folder}/${answer_data} >> ${Current_Folder}/${Answer} 132 | done < $3 133 | 134 | sleep 30 135 | screen -S $1 -X stuff "^C^M" 136 | screen -S $1 -X quit 137 | 138 | diff_line=$(diff -ab ./${Result} ./${Answer} | wc -l) 139 | echo -e "\033[32m 错误个数:$diff_line / ${Answer_Line} \033[0m" 140 | Cul_Run_Time $1 ${Current_Folder}/${Result} ${Answer_Line} ${diff_line} 141 | } 142 | 143 | Advanced_Test(){ 144 | # $1 team_name $2 test_data_file_name 145 | test_data=$(cat $2) # ./test10000 146 | Answer_Line=0 147 | Exe_Prog="" 148 | cd ${Current_Folder} 149 | Result="${test_data_txt}_Folder/Advanced_Result" 150 | Answer="${test_data_txt}_Folder/Advanced_Answer" 151 | 152 | if [[ -e sudoku_solve ]];then 153 | echo "找到执行文件sudoku_solve" 154 | Exe_Prog='sudoku_solve' 155 | elif [[ -e sudoku ]];then 156 | echo "找到执行文件sudoku" 157 | Exe_Prog='sudoku' 158 | else 159 | echo "未找到命名为sudoku或sudoku_solve的执行文件" 160 | echo "进行编译" 161 | make 162 | if [[ -e sudoku_solve ]];then 163 | echo "找到执行文件sudoku_solve" 164 | Exe_Prog='sudoku_solve' 165 | elif [[ -e sudoku ]];then 166 | echo "找到执行文件sudoku" 167 | Exe_Prog='sudoku' 168 | else 169 | echo "编译后仍未找到相应执行文件" 170 | exit 1; 171 | fi 172 | fi 173 | 174 | if [[ -e ./${Answer} ]];then 175 | rm ./${Answer} 176 | touch ./${Answer} 177 | else 178 | touch ./${Answer} 179 | fi 180 | sudo chmod 777 ./${Answer} 181 | screen -S $1 -X quit 182 | screen -dmS $1 183 | 184 | if [[ -e ./${Result} ]];then 185 | rm ./${Result} 186 | touch ./${Result} 187 | else 188 | touch ./${Result} 189 | fi 190 | 191 | screen -S $1 -X stuff "stdbuf -oL ./${Exe_Prog} > ./${Result}^M" 192 | while read -r test_data 193 | do 194 | Answer_Line=`expr ${Answer_Line} + $(cat ${test_data} | wc -l)` 195 | screen -S $1 -X stuff "${test_data}^M" 196 | done < $2 197 | 198 | while read -r answer_data 199 | do 200 | cat ${Current_Folder}/${answer_data} >> ${Current_Folder}/${Answer} 201 | done < $3 202 | 203 | sleep 30 204 | screen -S $1 -X stuff "^C^M" 205 | screen -S $1 -X quit 206 | 207 | diff_line=$(diff -ab ./${Result} ./${Answer} | wc -l) 208 | echo -e "\033[32m 错误个数:$diff_line / ${Answer_Line} \033[0m" 209 | Cul_Run_Time $1 ${Current_Folder}/${Result} ${Answer_Line} ${diff_line} 210 | } 211 | 212 | 213 | if [ -e ${test_data_txt} ];then 214 | Running_Version=$(cat ${test_data_txt} | wc -l) 215 | echo "测试样例：$Running_Version 个" 216 | cat ${test_data_txt} 217 | if [[ $Running_Version == 1 ]];then 218 | echo -e "\033[32m --------------${GROUP_NAME} is running Basic_Test-------------- \033[0m" 219 | Basic_Test ${GROUP_NAME} ${test_data_txt} ${answer_date_txt} 220 | elif [[ $Running_Version == 0 ]];then 221 | echo "请检查输入格式，确保文件末尾有一个换行,参照实验指导书" 222 | else 223 | echo -e "\033[32m --------------${GROUP_NAME} is running Advanced_Test--------------\033[0m" 224 | Advanced_Test ${GROUP_NAME} ${test_data_txt} ${answer_date_txt} 225 | fi 226 | else 227 | echo "文件$1不存在" 228 | exit 1; 229 | fi 230 | 231 | -------------------------------------------------------------------------------- /Lab1/src/Sudoku/Makefile: -------------------------------------------------------------------------------- 1 | CXXFLAGS+=-O2 -ggdb -DDEBUG 2 | CXXFLAGS+=-Wall -Wextra 3 | 4 | all: sudoku 5 | 6 | sudoku: main.cc neighbor.cc sudoku_basic.cc sudoku_min_arity.cc sudoku_min_arity_cache.cc sudoku_dancing_links.cc 7 | g++ -O2 -o $@ $^ 8 | -------------------------------------------------------------------------------- /Lab1/src/Sudoku/README: -------------------------------------------------------------------------------- 1 | A backtracking sudoku solver, four algorithms are shown. 2 | 3 | test cases are from http://people.csse.uwa.edu.au/gordon/sudokumin.php 4 | -------------------------------------------------------------------------------- /Lab1/src/Sudoku/answer1: -------------------------------------------------------------------------------- 1 | 693784512487512936125963874932651487568247391741398625319475268856129743274836159 2 | -------------------------------------------------------------------------------- /Lab1/src/Sudoku/answer_group: -------------------------------------------------------------------------------- 1 | ./answer1 2 | ./answer1000 3 | ./answer1000 4 | ./answer10000 5 | -------------------------------------------------------------------------------- /Lab1/src/Sudoku/main.cc: -------------------------------------------------------------------------------- 1 | #include 2 | #include 3 | #include 4 | #include 5 | #include 6 | 7 | #include "sudoku.h" 8 | 9 | int64_t now() 10 | { 11 | struct timeval tv; 12 | gettimeofday(&tv, NULL); 13 | return tv.tv_sec * 1000000 + tv.tv_usec; 14 | } 15 | 16 | int main(int argc, char* argv[]) 17 | { 18 | init_neighbors(); 19 | 20 | FILE* fp = fopen(argv[1], "r"); 21 | char puzzle[128]; 22 | int total_solved = 0; 23 | int total = 0; 24 | bool (*solve)(int) = solve_sudoku_basic; 25 | if (argv[2] != NULL) 26 | if (argv[2][0] == 'a') 27 | solve = solve_sudoku_min_arity; 28 | else if (argv[2][0] == 'c') 29 | solve = solve_sudoku_min_arity_cache; 30 | else if (argv[2][0] == 'd') 31 | solve = solve_sudoku_dancing_links; 32 | int64_t start = now(); 33 | while (fgets(puzzle, sizeof puzzle, fp) != NULL) { 34 | if (strlen(puzzle) >= N) { 35 | ++total; 36 | input(puzzle); 37 | init_cache(); 38 | //if (solve_sudoku_min_arity_cache(0)) { 39 | //if (solve_sudoku_min_arity(0)) 40 | //if (solve_sudoku_basic(0)) { 41 | if (solve(0)) { 42 | ++total_solved; 43 | if (!solved()) 44 | assert(0); 45 | } 46 | else { 47 | printf("No: %s", puzzle); 48 | } 49 | } 50 | } 51 | int64_t end = now(); 52 | double sec = (end-start)/1000000.0; 53 | printf("%f sec %f ms each %d\n", sec, 1000*sec/total, total_solved); 54 | 55 | return 0; 56 | } 57 | 58 | -------------------------------------------------------------------------------- /Lab1/src/Sudoku/mythreadpool.h: -------------------------------------------------------------------------------- 1 | #ifndef MYTHREADPOOL_H 2 | #define MYTHREADPOOL_H 3 | 4 | #include 5 | #include 6 | #include 7 | #include 8 | #include 9 | #include 10 | #include 11 | #include 12 | #include 13 | #include 14 | #include "taskqueue.h" 15 | 16 | // 定义任务结构体 17 | using namespace std; 18 | namespace mythreadpool{ 19 | class ThreadPool 20 | { 21 | public: 22 | ThreadPool( int maxnum){ 23 | // 实例化任务队列 24 | m_taskQ = new taskqueue::TaskQueue; 25 | do { 26 | // 初始化线程池 27 | 28 | m_maxNum = maxnum; 29 | m_busyNum = 0; 30 | m_aliveNum = 0; 31 | 32 | // 根据线程的最大上限给线程数组分配内存 33 | m_threadIDs = new pthread_t[maxnum]; 34 | if (m_threadIDs == nullptr) 35 | { 36 | cout << "malloc thread_t[] 失败...." << endl;; 37 | break; 38 | } 39 | // 初始化 40 | memset(m_threadIDs, 0, sizeof(pthread_t) * maxNum); 41 | // 初始化互斥锁,条件变量 42 | if (pthread_mutex_init(&m_lock, NULL) != 0 || 43 | pthread_cond_init(&m_notEmpty, NULL) != 0) 44 | { 45 | cout << "init mutex or condition fail..." << endl; 46 | break; 47 | } 48 | 49 | /////////////////// 创建线程 ////////////////// 50 | // 根据最小线程个数, 创建线程 51 | for (int i = 0; i < minNum; ++i) 52 | { 53 | pthread_create(&m_threadIDs[i], NULL, worker, this); 54 | cout << "创建子线程, ID: " << to_string(m_threadIDs[i]) << endl; 55 | } 56 | // 创建管理者线程, 1个 57 | pthread_create(&m_managerID, NULL, manager, this); 58 | } while (0); 59 | } 60 | ~ThreadPool(); 61 | 62 | // 添加任务 63 | void addTask(taskqueue::Task task){ 64 | if(m_shutdown) return; 65 | m_taskQ->addTask(task); 66 | pthread_cond_signal(&m_notEmpty); 67 | 68 | } 69 | // 获取忙线程的个数 70 | int getBusyNumber(); 71 | // 获取活着的线程个数 72 | int getAliveNumber(); 73 | 74 | private: 75 | // 工作的线程的任务函数 76 | static void* worker(void* arg){ 77 | ThreadPool* pool = (ThreadPool*)arg; 78 | while (true) 79 | { 80 | pthread_mutex_lock(&pool->m_lock); 81 | //任务为空且还在运行，阻塞线程 82 | while (pool->m_taskQ->taskNumber()==0&& !pool->m_shutdown) 83 | { 84 | pthread_cond_wait(&pool->m_notEmpty,&pool->m_lock); 85 | if(pool->m_exitNum>0){//有线程退出 86 | pool->m_exitNum--; 87 | pthread_mutex_unlock(&pool->m_lock); 88 | pool->threadExit();//单个线程退出 89 | } 90 | } 91 | 92 | if(pool->m_shutdown){ 93 | pthread_mutex_unlock(&pool->m_lock); 94 | pool->threadExit(); 95 | } 96 | taskqueue::Task task=pool->m_taskQ->takeTask(); 97 | pool->m_busyNum++; 98 | pthread_mutex_unlock(&pool->m_lock); 99 | printf("thread %ld start working\n",pthread_self()); 100 | 101 | 102 | task.fun(task.arg); 103 | delete task.arg; 104 | task.arg=nullptr; 105 | 106 | printf("thread %ld end working\n",pthread_self()); 107 | 108 | pthread_mutex_lock(&pool->m_lock); 109 | pool->m_busyNum--; 110 | pthread_mutex_unlock(&pool->m_lock); 111 | 112 | } 113 | return; 114 | 115 | } 116 | 117 | // 管理者线程的任务函数 118 | static void* manager(void* arg); 119 | void threadExit(){ 120 | pthread_t tid = pthread_self(); 121 | for(int i=0;i 2 | #include 3 | #include 4 | 5 | #include "sudoku.h" 6 | 7 | #include 8 | 9 | int neighbors[N][NEIGHBOR]; 10 | 11 | static void mark_adjacent(bool adjacent[ROW][COL], int row, int col) 12 | { 13 | for (int i = 0; i < NUM; ++i) { 14 | adjacent[row][i] = true; 15 | adjacent[i][col] = true; 16 | } 17 | int top = (row/3)*3; 18 | int left = (col/3)*3; 19 | adjacent[top][left] = true; 20 | adjacent[top][left+1] = true; 21 | adjacent[top][left+2] = true; 22 | adjacent[top+1][left] = true; 23 | adjacent[top+1][left+1] = true; 24 | adjacent[top+1][left+2] = true; 25 | adjacent[top+2][left] = true; 26 | adjacent[top+2][left+1] = true; 27 | adjacent[top+2][left+2] = true; 28 | } 29 | 30 | static void collect_neighbors(const bool adjacent[ROW][COL], int row, int col, int myneighbors[NEIGHBOR]) 31 | { 32 | int n = 0; 33 | for (int y = 0; y < ROW; ++y) { 34 | for (int x = 0; x < COL; ++x) { 35 | if (adjacent[y][x] && !(y == row && x == col)) { 36 | assert(n < NEIGHBOR); 37 | myneighbors[n++] = y*COL + x; 38 | } 39 | } 40 | } 41 | assert(n == NEIGHBOR); 42 | } 43 | 44 | static void print_neighbors(const bool adjacent[ROW][COL], int row, int col, int myneighbors[NEIGHBOR]) 45 | { 46 | for (int y = 0; y < ROW; ++y) { 47 | for (int x = 0; x < COL; ++x) { 48 | if (y == row && x == col) 49 | putchar('X'); 50 | else 51 | putchar(adjacent[y][x] ? 'o' : '.'); 52 | } 53 | printf("\n"); 54 | } 55 | for (int i = 0; i < NEIGHBOR; ++i) { 56 | printf("%2d, ", myneighbors[i]); 57 | } 58 | puts("\n"); 59 | } 60 | 61 | /*public*/ void init_neighbors() 62 | { 63 | for (int row = 0; row < ROW; ++row) { 64 | for (int col = 0; col < COL; ++col) { 65 | bool adjacent[ROW][COL]; 66 | bzero(adjacent, sizeof adjacent); 67 | mark_adjacent(adjacent, row, col); 68 | 69 | int me = row*COL + col; 70 | collect_neighbors(adjacent, row, col, neighbors[me]); 71 | 72 | if (DEBUG_MODE) 73 | print_neighbors(adjacent, row, col, neighbors[me]); 74 | } 75 | } 76 | } 77 | 78 | bool solved() 79 | { 80 | for (int row = 0; row < ROW; ++row) { 81 | // check row 82 | int occurs[10] = { 0 }; 83 | for (int col = 0; col < COL; ++col) { 84 | int val = chess[row][col]; 85 | assert(1 <= val && val <= NUM); 86 | ++occurs[val]; 87 | } 88 | 89 | if (std::count(occurs, occurs+10, 1) != NUM) 90 | return false; 91 | } 92 | 93 | for (int col = 0; col < COL; ++col) { 94 | int occurs[10] = { 0 }; 95 | for (int row = 0; row < ROW; ++row) { 96 | int val = chess[row][col]; 97 | // assert(1 <= val && val <= NUM); 98 | ++occurs[val]; 99 | } 100 | 101 | if (std::count(occurs, occurs+10, 1) != NUM) 102 | return false; 103 | } 104 | 105 | for (int row = 0; row < ROW; row += 3) { 106 | for (int col = 0; col < COL; col += 3) { 107 | int occurs[10] = { 0 }; 108 | ++occurs[chess[row ][col]]; 109 | ++occurs[chess[row ][col+1]]; 110 | ++occurs[chess[row ][col+2]]; 111 | ++occurs[chess[row+1][col]]; 112 | ++occurs[chess[row+1][col+1]]; 113 | ++occurs[chess[row+1][col+2]]; 114 | ++occurs[chess[row+2][col]]; 115 | ++occurs[chess[row+2][col+1]]; 116 | ++occurs[chess[row+2][col+2]]; 117 | 118 | if (std::count(occurs, occurs+10, 1) != NUM) 119 | return false; 120 | } 121 | } 122 | return true; 123 | } 124 | -------------------------------------------------------------------------------- /Lab1/src/Sudoku/sudoku.h: -------------------------------------------------------------------------------- 1 | #ifndef SUDOKU_H 2 | #define SUDOKU_H 3 | 4 | const bool DEBUG_MODE = false; 5 | enum { ROW=9, COL=9, N = 81, NEIGHBOR = 20 }; 6 | const int NUM = 9; 7 | 8 | extern int neighbors[N][NEIGHBOR]; 9 | extern int board[N]; 10 | extern int spaces[N]; 11 | extern int nspaces; 12 | extern int (*chess)[COL]; 13 | 14 | void init_neighbors(); 15 | void input(const char in[N]); 16 | void init_cache(); 17 | 18 | bool available(int guess, int cell); 19 | 20 | bool solve_sudoku_basic(int which_space); 21 | bool solve_sudoku_min_arity(int which_space); 22 | bool solve_sudoku_min_arity_cache(int which_space); 23 | bool solve_sudoku_dancing_links(int unused); 24 | bool solved(); 25 | #endif 26 | -------------------------------------------------------------------------------- /Lab1/src/Sudoku/sudoku_basic.cc: -------------------------------------------------------------------------------- 1 | #include 2 | #include 3 | 4 | #include 5 | 6 | #include "sudoku.h" 7 | 8 | int board[N]; 9 | int spaces[N]; 10 | int nspaces; 11 | int (*chess)[COL] = (int (*)[COL])board; 12 | 13 | static void find_spaces() 14 | { 15 | nspaces = 0; 16 | for (int cell = 0; cell < N; ++cell) { 17 | if (board[cell] == 0) 18 | spaces[nspaces++] = cell; 19 | } 20 | } 21 | 22 | void input(const char in[N]) 23 | { 24 | for (int cell = 0; cell < N; ++cell) { 25 | board[cell] = in[cell] - '0'; 26 | assert(0 <= board[cell] && board[cell] <= NUM); 27 | } 28 | find_spaces(); 29 | } 30 | 31 | bool available(int guess, int cell) 32 | { 33 | for (int i = 0; i < NEIGHBOR; ++i) { 34 | int neighbor = neighbors[cell][i]; 35 | if (board[neighbor] == guess) { 36 | return false; 37 | } 38 | } 39 | return true; 40 | } 41 | 42 | bool solve_sudoku_basic(int which_space) 43 | { 44 | if (which_space >= nspaces) { 45 | return true; 46 | } 47 | 48 | // find_min_arity(which_space); 49 | int cell = spaces[which_space]; 50 | 51 | for (int guess = 1; guess <= NUM; ++guess) { 52 | if (available(guess, cell)) { 53 | // hold 54 | assert(board[cell] == 0); 55 | board[cell] = guess; 56 | 57 | // try 58 | if (solve_sudoku_basic(which_space+1)) { 59 | return true; 60 | } 61 | 62 | // unhold 63 | assert(board[cell] == guess); 64 | board[cell] = 0; 65 | } 66 | } 67 | return false; 68 | } 69 | -------------------------------------------------------------------------------- /Lab1/src/Sudoku/sudoku_dancing_links.cc: -------------------------------------------------------------------------------- 1 | #include 2 | #include 3 | #include 4 | #include 5 | 6 | #include "sudoku.h" 7 | using namespace std; 8 | 9 | struct Node; 10 | typedef Node Column; 11 | struct Node 12 | { 13 | Node* left; 14 | Node* right; 15 | Node* up; 16 | Node* down; 17 | Column* col; 18 | int name; 19 | int size; 20 | }; 21 | 22 | const int kMaxNodes = 1 + 81*4 + 9*9*9*4; 23 | const int kMaxColumns = 400; 24 | const int kRow = 100, kCol = 200, kBox = 300; 25 | 26 | 27 | struct Dance 28 | { 29 | Column* root_; 30 | int* inout_; 31 | Column* columns_[400]; 32 | vector stack_; 33 | Node nodes_[kMaxNodes]; 34 | int cur_node_; 35 | 36 | Column* new_column(int n = 0) 37 | { 38 | assert(cur_node_ < kMaxNodes); 39 | Column* c = &nodes_[cur_node_++]; 40 | memset(c, 0, sizeof(Column)); 41 | c->left = c; 42 | c->right = c; 43 | c->up = c; 44 | c->down = c; 45 | c->col = c; 46 | c->name = n; 47 | return c; 48 | } 49 | 50 | void append_column(int n) 51 | { 52 | assert(columns_[n] == NULL); 53 | 54 | Column* c = new_column(n); 55 | put_left(root_, c); 56 | columns_[n] = c; 57 | } 58 | 59 | Node* new_row(int col) 60 | { 61 | assert(columns_[col] != NULL); 62 | assert(cur_node_ < kMaxNodes); 63 | 64 | Node* r = &nodes_[cur_node_++]; 65 | 66 | //Node* r = new Node; 67 | memset(r, 0, sizeof(Node)); 68 | r->left = r; 69 | r->right = r; 70 | r->up = r; 71 | r->down = r; 72 | r->name = col; 73 | r->col = columns_[col]; 74 | put_up(r->col, r); 75 | return r; 76 | } 77 | 78 | int get_row_col(int row, int val) 79 | { 80 | return kRow+row*10+val; 81 | } 82 | 83 | int get_col_col(int col, int val) 84 | { 85 | return kCol+col*10+val; 86 | } 87 | 88 | int get_box_col(int box, int val) 89 | { 90 | return kBox+box*10+val; 91 | } 92 | 93 | Dance(int inout[81]) : inout_(inout), cur_node_(0) 94 | { 95 | stack_.reserve(100); 96 | 97 | root_ = new_column(); 98 | root_->left = root_->right = root_; 99 | memset(columns_, 0, sizeof(columns_)); 100 | 101 | bool rows[N][10] = {false}; 102 | bool cols[N][10] = {false}; 103 | bool boxes[N][10] = {false}; 104 | 105 | for (int i = 0; i < N; ++i) { 106 | int row = i / 9; 107 | int col = i % 9; 108 | int box = row/3*3 + col/3; 109 | int val = inout[i]; 110 | rows[row][val] = true; 111 | cols[col][val] = true; 112 | boxes[box][val] = true; 113 | } 114 | 115 | for (int i = 0; i < N; ++i) { 116 | if (inout[i] == 0) { 117 | append_column(i); 118 | } 119 | } 120 | 121 | for (int i = 0; i < 9; ++i) { 122 | for (int v = 1; v < 10; ++v) { 123 | if (!rows[i][v]) 124 | append_column(get_row_col(i, v)); 125 | if (!cols[i][v]) 126 | append_column(get_col_col(i, v)); 127 | if (!boxes[i][v]) 128 | append_column(get_box_col(i, v)); 129 | } 130 | } 131 | 132 | for (int i = 0; i < N; ++i) { 133 | if (inout[i] == 0) { 134 | int row = i / 9; 135 | int col = i % 9; 136 | int box = row/3*3 + col/3; 137 | //int val = inout[i]; 138 | for (int v = 1; v < 10; ++v) { 139 | if (!(rows[row][v] || cols[col][v] || boxes[box][v])) { 140 | Node* n0 = new_row(i); 141 | Node* nr = new_row(get_row_col(row, v)); 142 | Node* nc = new_row(get_col_col(col, v)); 143 | Node* nb = new_row(get_box_col(box, v)); 144 | put_left(n0, nr); 145 | put_left(n0, nc); 146 | put_left(n0, nb); 147 | } 148 | } 149 | } 150 | } 151 | } 152 | 153 | Column* get_min_column() 154 | { 155 | Column* c = root_->right; 156 | int min_size = c->size; 157 | if (min_size > 1) { 158 | for (Column* cc = c->right; cc != root_; cc = cc->right) { 159 | if (min_size > cc->size) { 160 | c = cc; 161 | min_size = cc->size; 162 | if (min_size <= 1) 163 | break; 164 | } 165 | } 166 | } 167 | return c; 168 | } 169 | 170 | void cover(Column* c) 171 | { 172 | c->right->left = c->left; 173 | c->left->right = c->right; 174 | for (Node* row = c->down; row != c; row = row->down) { 175 | for (Node* j = row->right; j != row; j = j->right) { 176 | j->down->up = j->up; 177 | j->up->down = j->down; 178 | j->col->size--; 179 | } 180 | } 181 | } 182 | 183 | void uncover(Column* c) 184 | { 185 | for (Node* row = c->up; row != c; row = row->up) { 186 | for (Node* j = row->left; j != row; j = j->left) { 187 | j->col->size++; 188 | j->down->up = j; 189 | j->up->down = j; 190 | } 191 | } 192 | c->right->left = c; 193 | c->left->right = c; 194 | } 195 | 196 | bool solve() 197 | { 198 | if (root_->left == root_) { 199 | for (size_t i = 0; i < stack_.size(); ++i) { 200 | Node* n = stack_[i]; 201 | int cell = -1; 202 | int val = -1; 203 | while (cell == -1 || val == -1) { 204 | if (n->name < 100) 205 | cell = n->name; 206 | else 207 | val = n->name % 10; 208 | n = n->right; 209 | } 210 | 211 | //assert(cell != -1 && val != -1); 212 | inout_[cell] = val; 213 | } 214 | return true; 215 | } 216 | 217 | Column* const col = get_min_column(); 218 | cover(col); 219 | for (Node* row = col->down; row != col; row = row->down) { 220 | stack_.push_back(row); 221 | for (Node* j = row->right; j != row; j = j->right) { 222 | cover(j->col); 223 | } 224 | if (solve()) { 225 | return true; 226 | } 227 | stack_.pop_back(); 228 | for (Node* j = row->left; j != row; j = j->left) { 229 | uncover(j->col); 230 | } 231 | } 232 | uncover(col); 233 | return false; 234 | } 235 | 236 | void put_left(Column* old, Column* nnew) 237 | { 238 | nnew->left = old->left; 239 | nnew->right = old; 240 | old->left->right = nnew; 241 | old->left = nnew; 242 | } 243 | 244 | void put_up(Column* old, Node* nnew) 245 | { 246 | nnew->up = old->up; 247 | nnew->down = old; 248 | old->up->down = nnew; 249 | old->up = nnew; 250 | old->size++; 251 | nnew->col = old; 252 | } 253 | }; 254 | 255 | bool solve_sudoku_dancing_links(int unused) 256 | { 257 | Dance d(board); 258 | return d.solve(); 259 | } 260 | -------------------------------------------------------------------------------- /Lab1/src/Sudoku/sudoku_min_arity.cc: -------------------------------------------------------------------------------- 1 | #include 2 | 3 | #include 4 | 5 | #include "sudoku.h" 6 | 7 | static int arity(int cell) 8 | { 9 | bool occupied[10] = {false}; 10 | for (int i = 0; i < NEIGHBOR; ++i) { 11 | int neighbor = neighbors[cell][i]; 12 | occupied[board[neighbor]] = true; 13 | } 14 | return std::count(occupied+1, occupied+10, false); 15 | } 16 | 17 | static void find_min_arity(int space) 18 | { 19 | int cell = spaces[space]; 20 | int min_space = space; 21 | int min_arity = arity(cell); 22 | 23 | for (int sp = space+1; sp < nspaces && min_arity > 1; ++sp) { 24 | int cur_arity = arity(spaces[sp]); 25 | if (cur_arity < min_arity) { 26 | min_arity = cur_arity; 27 | min_space = sp; 28 | } 29 | } 30 | 31 | if (space != min_space) { 32 | std::swap(spaces[min_space], spaces[space]); 33 | } 34 | } 35 | 36 | bool solve_sudoku_min_arity(int which_space) 37 | { 38 | if (which_space >= nspaces) { 39 | return true; 40 | } 41 | 42 | find_min_arity(which_space); 43 | int cell = spaces[which_space]; 44 | 45 | for (int guess = 1; guess <= NUM; ++guess) { 46 | if (available(guess, cell)) { 47 | // hold 48 | assert(board[cell] == 0); 49 | board[cell] = guess; 50 | 51 | // try 52 | if (solve_sudoku_min_arity(which_space+1)) { 53 | return true; 54 | } 55 | 56 | // unhold 57 | assert(board[cell] == guess); 58 | board[cell] = 0; 59 | } 60 | } 61 | return false; 62 | } 63 | -------------------------------------------------------------------------------- /Lab1/src/Sudoku/sudoku_min_arity_cache.cc: -------------------------------------------------------------------------------- 1 | #include 2 | #include 3 | 4 | #include 5 | 6 | #include "sudoku.h" 7 | 8 | static bool occupied[N][NUM+1]; 9 | static int arity[N]; 10 | 11 | static void find_min_arity(int space) 12 | { 13 | int cell = spaces[space]; 14 | int min_space = space; 15 | int min_arity = arity[cell]; 16 | 17 | for (int sp = space+1; sp < nspaces && min_arity > 1; ++sp) { 18 | int cur_arity = arity[spaces[sp]]; 19 | if (cur_arity < min_arity) { 20 | min_arity = cur_arity; 21 | min_space = sp; 22 | } 23 | } 24 | 25 | if (space != min_space) { 26 | std::swap(spaces[min_space], spaces[space]); 27 | } 28 | } 29 | 30 | void init_cache() 31 | { 32 | bzero(occupied, sizeof(occupied)); 33 | std::fill(arity, arity + N, NUM); 34 | for (int cell = 0; cell < N; ++cell) { 35 | occupied[cell][0] = true; 36 | int val = board[cell]; 37 | if (val > 0) { 38 | occupied[cell][val] = true; 39 | for (int n = 0; n < NEIGHBOR; ++n) { 40 | int neighbor = neighbors[cell][n]; 41 | if (!occupied[neighbor][val]) { 42 | occupied[neighbor][val] = true; 43 | --arity[neighbor]; 44 | } 45 | } 46 | } 47 | } 48 | } 49 | 50 | bool solve_sudoku_min_arity_cache(int which_space) 51 | { 52 | if (which_space >= nspaces) { 53 | return true; 54 | } 55 | 56 | find_min_arity(which_space); 57 | int cell = spaces[which_space]; 58 | 59 | for (int guess = 1; guess <= NUM; ++guess) { 60 | if (!occupied[cell][guess]) { 61 | // hold 62 | assert(board[cell] == 0); 63 | board[cell] = guess; 64 | occupied[cell][guess] = true; 65 | 66 | // remember changes 67 | int modified[NEIGHBOR]; 68 | int nmodified = 0; 69 | for (int n = 0; n < NEIGHBOR; ++n) { 70 | int neighbor = neighbors[cell][n]; 71 | if (!occupied[neighbor][guess]) { 72 | occupied[neighbor][guess] = true; 73 | --arity[neighbor]; 74 | modified[nmodified++] = neighbor; 75 | } 76 | } 77 | 78 | // try 79 | if (solve_sudoku_min_arity_cache(which_space+1)) { 80 | return true; 81 | } 82 | 83 | // unhold 84 | occupied[cell][guess] = false; 85 | assert(board[cell] == guess); 86 | board[cell] = 0; 87 | 88 | // undo changes 89 | for (int i = 0; i < nmodified; ++i) { 90 | int neighbor = modified[i]; 91 | assert(occupied[neighbor][guess]); 92 | occupied[neighbor][guess] = false; 93 | ++arity[neighbor]; 94 | } 95 | } 96 | } 97 | return false; 98 | } 99 | -------------------------------------------------------------------------------- /Lab1/src/Sudoku/taskqueue.h: -------------------------------------------------------------------------------- 1 | #ifndef TASKQUEUE_H 2 | #define TASKQUEUE_H 3 | 4 | #include 5 | #include 6 | #include 7 | #include 8 | #include 9 | #include 10 | #include 11 | #include 12 | #include 13 | #include 14 | 15 | // 定义任务结构体 16 | namespace taskqueue{ 17 | struct Task 18 | { 19 | void*(*fun)(void*) ;//函数指针 20 | void* arg;//函数参数 21 | Task() 22 | { 23 | fun = nullptr; 24 | arg = nullptr; 25 | } 26 | Task(void*(*f)(void*) , void* arg) 27 | { 28 | fun = f; 29 | this->arg = arg; 30 | } 31 | 32 | }; 33 | 34 | // 任务队列 35 | class TaskQueue 36 | { 37 | public: 38 | TaskQueue() 39 | { 40 | pthread_mutex_init(&m_mutex, NULL); 41 | } 42 | 43 | ~TaskQueue() 44 | { 45 | pthread_mutex_destroy(&m_mutex); 46 | } 47 | 48 | // 添加任务 49 | void addTask(Task& task) 50 | { 51 | pthread_mutex_lock(&m_mutex); 52 | myqueue.push_back(task); 53 | pthread_mutex_unlock(&m_mutex); 54 | } 55 | 56 | void addTask(void*(*f)(void*) , void* arg); 57 | void addTask(void*(*f)(void*), void* arg) 58 | { 59 | pthread_mutex_lock(&m_mutex); 60 | Task task; 61 | task.fun = f; 62 | task.arg = arg; 63 | myqueue.push_back(task); 64 | pthread_mutex_unlock(&m_mutex); 65 | } 66 | 67 | // 取出一个任务 68 | Task takeTask() 69 | { 70 | Task t; 71 | pthread_mutex_lock(&m_mutex); 72 | if (myqueue.size() > 0) 73 | { 74 | t = myqueue.front(); 75 | myqueue.pop_front(); 76 | } 77 | pthread_mutex_unlock(&m_mutex); 78 | return t; 79 | } 80 | 81 | // 获取当前队列中任务个数 82 | inline int taskNumber() 83 | { 84 | return myqueue.size(); 85 | } 86 | 87 | private: 88 | pthread_mutex_t m_mutex; // 互斥锁 89 | std::deque myqueue; // 任务队列 90 | }; 91 | } 92 | #endif -------------------------------------------------------------------------------- /Lab1/src/Sudoku/test.cc: -------------------------------------------------------------------------------- 1 | // main.c 2 | #include 3 | 4 | #include "threadpool.h" 5 | #include 6 | #include 7 | #include 8 | using namespace mythreadpool; 9 | void printString(const std::string &str) { 10 | std::cout << str << std::endl; 11 | usleep(100 * 100); 12 | } 13 | 14 | void test(int maxSize) { 15 | ThreadPool pool("pool"); 16 | pool.setqSize(maxSize); 17 | pool.start(5); 18 | for (int i = 0; i < 100; ++i) { 19 | std::string buf = "task" + std::to_string(i); 20 | pool.run(std::bind(printString, buf)); 21 | } 22 | pool.stop(); 23 | std::cout << "Done" << std::endl; 24 | } 25 | 26 | int main() { 27 | test(10); 28 | std::cout << "Hello, World!" << std::endl; 29 | return 0; 30 | } 31 | -------------------------------------------------------------------------------- /Lab1/src/Sudoku/test1: 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000000201500300000000070000000500030020004000076000000000000350000021000800000400 988 | 000000201600300000700000000008540000020000030000600700010082000500000060000000000 989 | 000000201730000000600040000000060030008000500200000000001200000000508000060000070 990 | 000000201800000900000400000000610030270000000900000000090072000001000040000800000 991 | 000000203006400000000000500100600070820000000000830000000059000050002000000000040 992 | 000000203010700000000000000000023400090060000800000000000800019600900070200000000 993 | 000000203080700000000000100005000040300010000000000600000407060100000080200500000 994 | 000000203800600000000000700002000100040800000000300060000027040300000005000010000 995 | 000000204000001000000080000020400500000030700000000080100200006806000010000700000 996 | 000000204001000000050000000006500080200009000000000010000150700940000300000800000 997 | 000000204050030000000000690000850010206000000900000000000206000130000000000400000 998 | 000000204050700000680000000300000090000014000000020000201000000000800050000600700 999 | 000000204100900000000000007670300000000100830040000000000025000500000090000040000 1000 | 000000204100900000000000008680700000000100730040000000000025000500000090000040000 1001 | -------------------------------------------------------------------------------- /Lab1/src/Sudoku/test_group: -------------------------------------------------------------------------------- 1 | ./test1 2 | ./test1000 3 | ./test1000 4 | ./test10000 5 | -------------------------------------------------------------------------------- /Lab1/src/Sudoku/threadpool.cc: -------------------------------------------------------------------------------- 1 | #include "threadpool.h" 2 | 3 | #include 4 | #include 5 | #include 6 | #include 7 | #include 8 | 9 | using namespace mythreadpool; 10 | 11 | void ThreadPool::start(int numThreads) 12 | { 13 | //assert(threads_.empty()); 14 | running = true; 15 | mythreads.reserve(numThreads);//更改vector的容量,为最大线程个数 16 | for (int i = 0; i < numThreads; ++i)//循环创建线程 17 | { 18 | pthread_create (&mythreads[i], NULL,runInThread,NULL); 19 | } 20 | 21 | } 22 | 23 | /*销毁线程池，等待队列中的任务不会再被执行，但是正在运行的线程会一直 24 | 把任务运行完后再退出*/ 25 | void ThreadPool::stop() 26 | { 27 | 28 | if (!running)return ;/*防止两次调用*/ 29 | 30 | /*唤醒所有等待线程，线程池要销毁了*/ 31 | pthread_mutex_lock(&_mutex); 32 | running=false; 33 | void * thread_result; 34 | 35 | pthread_cond_broadcast (¬empty); 36 | pthread_cond_broadcast (¬full); 37 | pthread_mutex_unlock(&_mutex); 38 | 39 | //阻塞主线程，等待其它线程执行结束 40 | for (int i = 0; i < mythreads.size(); ++i){ 41 | pthread_join (mythreads[i], &thread_result); 42 | //输出获取到的线程的返回值 43 | printf("%s\n", (char*)thread_result); 44 | } 45 | /*销毁等待队列*/ 46 | mythreads.clear(); 47 | /*条件变量和互斥量也别忘了销毁*/ 48 | pthread_mutex_destroy(&_mutex); 49 | pthread_cond_destroy(¬full); 50 | pthread_cond_destroy(¬empty); 51 | 52 | } 53 | 54 | 55 | int ThreadPool::queueSize() 56 | { 57 | pthread_mutex_lock(&_mutex); 58 | return myqueue.size(); 59 | pthread_mutex_unlock(&_mutex); 60 | } 61 | 62 | void ThreadPool::run(Task task) 63 | { 64 | if (mythreads.empty())//如果线程池当中的线程是空的 65 | { 66 | task();//那么就直接执行任务，不进行在线程池中添加任务 67 | } 68 | else 69 | { 70 | pthread_mutex_lock(&_mutex); 71 | 72 | while (isFull()&&running) 73 | { 74 | pthread_cond_wait (¬full, &_mutex); 75 | } 76 | if (!running) return; 77 | myqueue.push_back(std::move(task));//在任务队列中添加任务 78 | pthread_cond_signal(¬empty); 79 | pthread_mutex_unlock(&_mutex); 80 | 81 | } 82 | } 83 | 84 | ThreadPool::Task ThreadPool::take() 85 | { 86 | pthread_mutex_lock(&_mutex); 87 | while (myqueue.empty() && running)//如果任务队列中的任务是空的，且处于运行状态 88 | { 89 | pthread_cond_wait (¬empty, &_mutex);//需要等待任务 90 | 91 | 92 | } 93 | //否则说明有任务 94 | Task task; 95 | if (!myqueue.empty()) 96 | { 97 | task = myqueue.front();//取出任务,queue，先进先出 98 | myqueue.pop_front();//删除任务 99 | if (maxq > 0) 100 | { 101 | pthread_cond_signal(¬full); 102 | } 103 | } 104 | pthread_mutex_unlock(&_mutex); 105 | return task; 106 | } 107 | 108 | 109 | 110 | 111 | void* ThreadPool::runInThread(void *arg) 112 | { 113 | while (running)//如果线程队列在运行 114 | { 115 | Task task(take());//取出一个任务 116 | if (task) 117 | { 118 | task(); 119 | } 120 | 121 | } -------------------------------------------------------------------------------- /Lab1/src/Sudoku/threadpool.h: -------------------------------------------------------------------------------- 1 | #ifndef THREADPOOL_H 2 | #define THREADPOOL_H 3 | 4 | #include 5 | #include 6 | #include 7 | #include 8 | #include 9 | #include 10 | #include 11 | #include 12 | #include 13 | #include 14 | 15 | 16 | using namespace std; 17 | namespace mythreadpool 18 | { 19 | /*线程池结构*/ 20 | class ThreadPool 21 | { 22 | public: 23 | 24 | //explicit禁止编译器执行非预期 (往往也不被期望) 的类型转换 25 | explicit ThreadPool(string name ){ 26 | myname=name; 27 | running=false; 28 | maxq=0; 29 | 30 | pthread_mutex_init (&_mutex, NULL); 31 | pthread_cond_init (¬full, NULL); 32 | pthread_cond_init (¬empty, NULL); 33 | 34 | } 35 | ~ThreadPool(){ 36 | if (running){ 37 | stop(); 38 | } 39 | } 40 | 41 | typedef std::function Task; 42 | 43 | 44 | void start(int numThreads); 45 | void stop(); 46 | void run(Task t); //运行任务，往线程池中的任务队列添加任务 47 | bool isFull() { 48 | return maxq <= myqueue.size(); 49 | } 50 | 51 | 52 | void setqSize(int num) { maxq = num; } 53 | std::string name() { return myname; } 54 | int queueSize(); 55 | 56 | bool running;//线程池是否运行 57 | int shutdown; 58 | int cur_queue_size; 59 | 60 | 61 | private: 62 | 63 | 64 | Task take();//获取任务函数 65 | static void* runInThread(void *arg); 66 | 67 | pthread_mutex_t _mutex;//条件变量使用锁 68 | pthread_cond_t notfull;//线程池非满条件变量 69 | pthread_cond_t notempty;//线程池非空条件变量 70 | 71 | string myname; 72 | Task threadtask; 73 | std::vector mythreads; 74 | std::deque myqueue; 75 | 76 | // 任务队列的最大大小 77 | int maxq; 78 | 79 | }; 80 | } 81 | #endif 82 | 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-------------------------------------------------------------------------------- 1 | # Lab2: Your Own HTTP Server 2 | 3 | *Some materials are from Homework 2 of CS162 2019 at UC Berkeley.* *Thanks to CS162!* 4 | 5 | Enter in the folder you have cloned from our lab git repo, and pull the latest commit. 6 | 7 | `git pull` 8 | 9 | You can find this lab2's instruction in `Lab2/README.md` 10 | 11 | All materials of lab2 are in folder `Lab2/` 12 | 13 | ## 1. Overview 14 | 15 | Implement an HTTP server based on HTTP/1.1 from scratch by your own, using network programming knowledges learned from our class. Also, try to use high concurrency programming skills learned from the class to guarantee the web server's performance. 16 | 17 | ### Goals 18 | 19 | * Practice basic network programming skills, such as using socket API, parsing packets; 20 | * Get familiar with robust and high-performance concurrent programming. 21 | 22 | ## 2. Background 23 | 24 | ### 2.1 Hypertext Transport Protocol 25 | 26 | The Hypertext Transport Protocol (HTTP) is the most commonly used application protocol on the Internet today. Like many network protocols, HTTP uses a client-server model. An HTTP client opens a network connection to an HTTP server and sends an HTTP request message. Then, the server replies with an HTTP response message, which usually contains some resource (file, text, binary data) that was requested by the client. We briefly introduce the HTTP message format and structure in this section for your convenience. Detailed specification of HTTP/1.1 can be found in [RFC 2616 - Hypertext Transfer Protocol -- HTTP/1.1](https://tools.ietf.org/html/rfc2616). 27 | 28 | ### 2.2 HTTP Messages 29 | 30 | HTTP messages are simple, formatted blocks of data. All HTTP messages fall into two types: **request** messages and **response** messages. Request messages request an action from a web server. Response messages carry results of a request back to a client. Both request and response messages have the same basic message structure. 31 | 32 | #### 2.2.1 Message Format 33 | 34 | HTTP request and response messages consist of 3 components: 35 | 36 | - a start line describing the message, 37 | - a block of headers containing attributes, 38 | - and an optional body containing data. 39 | 40 | Each component has the format as following 41 | 42 | ##### 2.2.1.1 Start Line 43 | 44 | All HTTP messages begin with a start line. The start line for a request message says *what to do*. The start line for a response message says *what happened*. 45 | 46 | Specifically, the start line is also called ***Request line*** in *Request messages* and ***Response line*** in *Response messages*. 47 | 48 | 1. **Request line:** The request line contains a method describing what operation the server should perform and a request URL describing the resource on which to perform the method. The request line also includes an HTTP version tells the server what dialect of HTTP the client is speaking. All of these fields are separated by whitespace. 49 | 50 | Example of request line: 51 | 52 | `GET /index.html HTTP/1.1` 53 | 54 | 2. **Response line:** The response line contains the HTTP version that the response message is using, a numeric status code, and a textual reason phrase describing the status of the operation. 55 | 56 | Example of response line: 57 | 58 | `HTTP/1.1 200 OK` 59 | 60 | ##### 2.2.1.2 Header 61 | 62 | Following the start line comes a list of zero, one, or many HTTP header fields. HTTP header fields add additional information to request and response messages. They are basically just lists of name/value pairs. Each HTTP header has a simple syntax: a name, followed by a colon (:), followed by optional whitespace, followed by the field value, followed by a CRLF. 63 | 64 | HTTP headers are classified into: General headers, Request headers, Response headers, Entity headers and Extension headers. Note that request-header fields are different from the response-header fields. We will not introduce those fields in details and you are not required to implement in this lab. You can find them in [RFC 2616 - Hypertext Transfer Protocol -- HTTP/1.1](https://tools.ietf.org/html/rfc2616). 65 | 66 | Example of headers in a request: 67 | 68 | ``` 69 | Host: 127.0.0.1:8888 70 | User-Agent: Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:74.0) Gecko/20100101 Firefox/74.0 71 | Accept: text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8 72 | Accept-Language: en-US,en;q=0.5 73 | Accept-Encoding: gzip, deflate 74 | Connection: keep-alive 75 | Upgrade-Insecure-Requests: 1 76 | Cache-Control: max-age=0 77 | // CRLF 78 | ``` 79 | 80 | Example of headers in a response: 81 | 82 | ``` 83 | Server: Guo's Web Server 84 | Content-length: 248 85 | Content-type: text/html 86 | // CRLF 87 | ``` 88 | 89 | ##### 2.2.1.3 Entity Body 90 | 91 | The third part of an HTTP message is the optional entity body. Entity bodies are the payload of HTTP messages. They are the things that HTTP was designed to transmit. 92 | 93 | HTTP messages can carry many kinds of digital data: images, video, HTML documents, software applications, credit card transactions, electronic mail, and so on. 94 | 95 | Example of entity body: 96 | 97 | ``` 98 | 99 | CS06142 100 | 101 |

CS06142

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Welcome to Cloud Computing Course.
103 |

104 |
105 |
Http Server at ip-127-0-0-1 Port 8888
106 | 107 | ``` 108 | 109 | #### 2.2.2 Structure of HTTP Request 110 | 111 | A HTTP request message contains an HTTP request line (containing a method, a query string, and the HTTP protocol version), zero or more HTTP header lines and a blank line (i.e. a CRLF). 112 | 113 | Example of HTTP request message: 114 | 115 | ``` 116 | GET /index.html HTTP/1.1 117 | Host: 127.0.0.1:8888 118 | User-Agent: Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:74.0) Gecko/20100101 Firefox/74.0 119 | Accept: text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8 120 | Accept-Language: en-US,en;q=0.5 121 | Accept-Encoding: gzip, deflate 122 | Connection: keep-alive 123 | Upgrade-Insecure-Requests: 1 124 | Cache-Control: max-age=0 125 | // CRLF 126 | ``` 127 | 128 | #### 2.2.3 Structure of HTTP Response 129 | 130 | A HTTP response message contains an HTTP response status line (containing the HTTP protocol version, the status code, and a description of the status code), zero or more HTTP header lines, a blank line (i.e. a CRLF by itself) and the content requested by the HTTP request. 131 | 132 | Example of HTTP response message: 133 | 134 | ``` 135 | HTTP/1.1 200 OK 136 | Server: Tiny Web Server 137 | Content-length: 248 138 | Content-type: text/html 139 | // CRLF 140 | 141 | CS06142 142 | 143 |

CS06142

144 |

Welcome to Cloud Computing Course.
145 |

146 |
147 |
Http Server at ip-127-0-0-1 Port 8888
148 | 149 | ``` 150 | 151 | ### 2.3 HTTP Proxy 152 | 153 | HTTP proxy servers are intermediaries. Proxies sit between clients and servers and act as "middlemen", shuffling HTTP messages back and forth between the parties. 154 | 155 | HTTP proxy servers are middlemen that fulfill transactions on the client's behalf. Without a HTTP proxy, HTTP clients talk directly to HTTP servers. With a HTTP proxy, the client instead talks to the proxy, which itself communicates with the server on the client's behalf. 156 | 157 | HTTP proxy servers are both web servers and web clients. Because HTTP clients send request messages to proxies, the proxy server must properly handle the requests and the connections and return responses, just like a web server. At the same time, the proxy itself sends requests to servers, so it must also behave like a correct HTTP client, sending requests and receiving responses. 158 | 159 | The working pattern of HTTP proxy is shown in the following figure: 160 | 161 | ``` 162 | +-----------+ +-----------+ 163 | | | | | 164 | +----------+ Request | | Request | | 165 | | |+---------------> |+--------------> | 166 | | Client | | Proxy | | Server | 167 | | <---------------+| <--------------+| | 168 | +----------+ Response | | Response | | 169 | | | | | 170 | +-----------+ +-----------+ 171 | ``` 172 | 173 | ## 3. Your Lab Task 174 | 175 | ### 3.1 Implement your own HTTP Server 176 | 177 | In this Lab, we won't provide any basic code. So, you should implement a HTTP server (base on HTTP/1.1) from scratch which satisfies the following requirements: 178 | 179 | #### 3.1.1 HTTP Server Outline 180 | 181 | From a network standpoint, your HTTP server should implement the following: 182 | 183 | 1. Create a listening socket and bind it to a port 184 | 2. Wait a client to connect to the port 185 | 3. Accept the client and obtain a new connection socket 186 | 4. Read in and parse the HTTP request 187 | 5. Start delivering services: 1) Handle HTTP GET/POST request and return an error message if an error occur. 2) Proxy the request to another HTTP server (optional for advanced version). 188 | 189 | The server will be in either non-proxy mode or proxy mode (we have introduced the proxy in section `2.3`). It does not do both things at the same time. 190 | 191 | #### 3.1.2 Handle HTTP request 192 | 193 | In this Lab, **you just need to implement the GET method and the POST method in your HTTP server**. That is to say, if your HTTP server receive a HTTP request but the request method is neither GET nor POST. The HTTP server just need to return a 501 Not Implemented error message (a response message with Response line having status code to be 501, see `2.2`). 194 | 195 | There is no need to handle the header line(s) in the request (but you need to recognize it so that you will not mix it with the next request's start line). Also, you are free to fill any (or zero) header line(s) in the HTTP response. 196 | 197 | ##### 3.1.2.1 Handle HTTP GET request 198 | 199 | The HTTP server should be able to handle HTTP GET requests for html pages. 200 | 201 | 1. If the HTTP request’s path corresponds to a html page file, respond with a 200 OK and the full contents of the file. For example, if GET /index.html is requested, and a file named index.html exists in the files directory. You should also be able to handle requests to files in subdirectories of the files directory (e.g. GET /images/hero.jpg). 202 | 2. If the HTTP request’s path corresponds to a directory and the directory contains an `index.html` file, respond with a 200 OK and the full contents of the index.html file in that folder. 203 | 3. If the requested page file does not exist, or the requested directory does not contain an `index.html` file, return a 404 Not Found response (the HTTP body is optional). 204 | 205 | See examples in section `3.1.7.1`. 206 | 207 | 208 | ##### 3.1.2.2 Handle HTTP POST request 209 | 210 | The HTTP server should be able to handle HTTP POST requests. In this lab, the way of handle HTTP POST is very simple. 211 | 212 | 1. You should construct an HTTP POST request (see section `3.1.7.2`) that contains 2 keys: "Name" and "ID" (please fill in your name and student number respectively), and send the POST request to `/Post_show` (i.e. `http://127.0.0.1:8888/Post_show` if server's IP is `127.0.0.1` and service port is `8888`). 213 | 214 | Then, if the HTTP server receive this POST request (the request URL is `/Post_show` and the keys are "Name" and "ID"), respond with a 200 OK and echo the "Name"-"ID" pairs you have sent. 215 | 216 | 2. Otherwise (i.e. the request URL is not `/Post_show` or the keys are not "Name" and "ID"), return a 404 Not Found response message. 217 | 218 | See examples in section `3.1.7.2`. 219 | 220 | ##### 3.1.2.3 Other request 221 | 222 | Just return 501 Not Implemented error message for other request method (e.g. DELETE, PUT, etc.). 223 | 224 | See examples in section `3.1.7.3`. 225 | 226 | #### 3.1.3 Implement a proxy server (optional) 227 | 228 | Enable your server to proxy HTTP requests to another HTTP server and forward the responses to the clients. 229 | 230 | 1. You should use the value of the `--proxy` command line argument, which contains the address and port number of the upstream HTTP server. 231 | 2. Your proxy server should wait for new data on both sockets (the HTTP client fd, and the upstream HTTP server fd). When data arrives, you should immediately read it to a buffer and then write it to the other socket. You are essentially maintaining 2-way communication between the HTTP client and the upstream HTTP server. Note that your proxy must support multiple requests/responses. 232 | 3. If either of the sockets closes, communication cannot continue, so you should close the other socket and exit the child process. 233 | 234 | Hints: 1) This is more tricky than writing to a file or reading from stdin, since you do not know which side of the 2-way stream will write data first, or whether they will write more data after receiving a response. 2) You should again use threads for this task. For example, consider using two threads to facilitate the two-way communication, one from A to B and the other from B to A. 235 | 236 | #### 3.1.4 Use multi-thread to increase concurrency 237 | 238 | Your HTTP server should use multiple threads to handle as many concurrent clients' requests as possible. You have at least the following three options to architect your multi-thread server: 239 | 240 | - **On-demand threads**. You can can create a new thread whenever a new client comes in, and use that thread to handle all that clients' task, including parsing the HTTP request, fetching page files, and sending response. The thread can be destroyed after that client finishes, e.g, detect through TCP `recv()`. However,it may not be easy to detect client finish in the HTTP layer. 241 | - **A pool of always-on threads**. You can use a fixed-sized thread pool in your HTTP server program for handling multiple client requests concurrently. If there are no tasks, those threads are in a waiting state. If a new client comes in, assign a thread to handle the client's request and send response to it. If the assigned thread is busy, you can use a work queue to buffer the request, and let the thread process it later. 242 | - **Combined**. Combine above two styles together. For example, you can use thread pool to receive request and send response, and use on-demand threads to fetch large page files. 243 | 244 | Feel free to choose any one from the above three, or use other multi-thread architecture that you think is cool. 245 | 246 | #### 3.1.5 Specify arguments 247 | 248 | Your program should enable long options to accept arguments and specify those arguments during start. They are `--ip`, `--port`, and `--proxy` (optional). 249 | 250 | 1. `--ip`             —— Specify the server IP address. 251 | 2. `--port`           —— Selects which port the HTTP server listens on for incoming connections. 252 | 4. `--proxy`         —— Selects an “upstream” HTTP server to proxy. The argument can have a port number after a colon (e.g. `https://www.CS06142.com:80`). If a port number is not specified, port 80 is the default. 253 | 254 | If you have no idea about *long options*, you can read [this](https://www.gnu.org/software/libc/manual/html_node/Argument-Syntax.html#Argument-Syntax). And you may need to use some functions like `getopt_long()`, `getopt_long_only()`, `getopt()` and so on. Check those function's usage with the `man` command. 255 | 256 | #### 3.1.6 Run your HTTP Server 257 | 258 | Your program should be able to start at terminal. If your program is called *httpserver*, just typing: 259 | 260 | in the non-proxy mode: 261 | 262 | `./httpserver --ip 127.0.0.1 --port 8888 --number-thread 8` 263 | 264 | It means that your HTTP server's IP address is 127.0.0.1 and service port is 8888. The --number-thread indicates that there are 8 threads in the thread pool for handling multiple client request concurrently. 265 | 266 | in the proxy mode: 267 | 268 | `./httpserver --ip 127.0.0.1 --port 8888 --number-thread 8 --proxy https://www.CS06142.com:80` 269 | 270 | It means that this is an HTTP proxy. This proxy's IP address is 127.0.0.1 and service port is 8888. And the proxy has a thread pool with 8 threads. The --proxy indicates that the "upstream" HTTP server is `https://www.CS06142.COM:80`. So, if you send a request message to this proxy (i.e. `127.0.0.1:8888`), it will forward this request message to the "upstream" HTTP server (i.e. `https://www.CS06142.com:80`) and forward the response message to the client. 271 | 272 | When you run the command above, your HTTP server should run correctly. 273 | 274 | #### 3.1.7 Accessing Your HTTP Server 275 | 276 | ##### 3.1.7.1 Using GET method 277 | 278 | 1. You can check that your HTTP server works by opening your web browser and going to the appropriate URL. [Note] IP 127.0.0.1 refers to the IP of local host. So you can use 127.0.0.1 to test your HTTP server on the same local machine. 279 | 280 | For example: 281 | 282 | index page 283 | 284 | You can also send HTTP requests with the curl program. An example of how to use curl is: 285 | 286 | `curl -i -X GET http://127.0.0.1:8888/index.html` 287 | 288 | For example: 289 | 290 | index page curl 291 | 292 | 2. If the request page does not exist, your HTTP server should return a 404 Not Found error message. 293 | 294 | For example: 295 | 296 | not found page curl 297 | 298 | ##### 3.1.7.2 Using POST method 299 | 300 | 1. You can check whether the POST method works by sending a HTTP request with the curl program. Typing the command at terminal: 301 | 302 | `curl -i -X POST --data 'Name=HNU&ID=CS06142' http://127.0.0.1:8888/Post_show` 303 | 304 | For example: 305 | 306 | post curl 307 | 308 | You can also construct a POST HTTP request and send the request to HTTP server using some browser plug-in tools. 309 | 310 | 2. If the request URL is not `/Post_show` or the keys are not "Name" and "ID"), you will get a 404 Not Found error message. 311 | 312 | For example: 313 | 314 | post not found curl 315 | 316 | ##### 3.1.7.3 Other method 317 | 318 | The HTTP server will not handle HTTP requests except GET requests and POST requests. 319 | 320 | If you send a HTTP DELETE (or PUT, HEAD, etc.) request to delete the specified resource, you will get a 501 Not Implemented error message: 321 | 322 | Not implemented 323 | 324 | #### 3.1.8 Implementation requirements 325 | 326 | ##### 3.1.8.1 Basic version 327 | 328 | Your program should complete all the **tasks described in section `3.1.1~3.1.7` except `3.1.3`**. 329 | 330 | In the basic version, you have **only one request per TCP connection going on at the same time**. The client waits for response, and when it gets response, perhaps reuses the TCP connection for a new request (or use a new TCP connection). This is also what normal HTTP server supports. 331 | 332 | ##### 3.1.8.2 Advanced version 333 | 334 | Your program should complete all the **tasks described in section `3.1.1~3.1.7` including`3.1.3`**. 335 | 336 | In the advanced version, **multiple http requests can be fired concurrently on one TCP connection**. This is also called HTTP pipelining which is supported by many real browsers and servers (such as Chrome). Note that HTTP requests that come from the same TCP connection should be responded in the same order. So take care the order problem when using complex multi-thread styles. 337 | 338 | ### 3.2 Finish a performance test report 339 | Please test your code first, and commit a test report along with your lab code into your group’s course github repo. 340 | 341 | The test report should describe the performance result under various testing conditions. Specifically, in your test report, you should at least contain the following two things: 342 | 343 | 1. Test how many HTTP request your server can process per second, when running on various server machine environments. For example, change the number of server CPU cores, enable/disable hyper-threading, etc. 344 | 2. Test how many HTTP request your server can process per second, by varying the number of concurrent clients that send request to your server simultaneously. Do change the client's workload. For example, test when a client use new TCP connection for a new request, or when a client reuses old TCP connection for new requests. Moreover, if you implement the advanced version, try to change the number of out-bounding requests on the same client's TCP connection. You can write a simple client that send HTTP Get by your own (can run multiple client programs on the same machine to emulate multiple clients), or use some existing HTTP client testing tools such as [ab - Apache HTTP server benchmarking tool](http://httpd.apache.org/docs/current/programs/ab.html). 345 | 346 | **[NOTE]**: Be careful that clients may be the performance bottleneck. So you'd better use multiple machines when testing the performance. For example, you can run multiple client processes on three machines (of three group members), and run the server process on another machine (of the other group member). Moreover, the network can be the bottleneck too. You can estimate the performance limit according to the physical bandwidth of your network environment, and see if your implementation can reach the performance limit. 347 | 348 | 349 | ## 4. Lab submission 350 | 351 | Please put all your code in folder `Lab2` and write a `Makefile` so that we **can compile your code in one single command** `make`. The compiled runnable executable binary should be named `httpserver` and located in folder `Lab2`. Please carefully following above rules so that TAs can automatically test your code!!! 352 | 353 | Please submit your lab program and performance test report following the guidance in the [Overall Lab Instructions](../README.md) (`../README.md`) 354 | 355 | ## 5. Grading standards 356 | 357 | 1. You can get 23 points if you can: 1) finish all the requirements of the basic version, and 2) your performance test report has finished the two requirements described before. If you missed some parts, you will get part of the points depending how much you finished. 358 | 2. You can get 25 points (full score) if you can: 1) finish all the requirements of the advanced version, and 2) your performance test report has finished the two requirements described before. If you missed some parts, you will get part of the points depending how much you finished. -------------------------------------------------------------------------------- /Lab2/src/get_404_curl.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/lxthnu/CloudComputingLabs/74dcd2c1e4dd5d97615173a6aaedc7927bac9c07/Lab2/src/get_404_curl.png -------------------------------------------------------------------------------- /Lab2/src/index.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/lxthnu/CloudComputingLabs/74dcd2c1e4dd5d97615173a6aaedc7927bac9c07/Lab2/src/index.png -------------------------------------------------------------------------------- /Lab2/src/index_curl.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/lxthnu/CloudComputingLabs/74dcd2c1e4dd5d97615173a6aaedc7927bac9c07/Lab2/src/index_curl.png -------------------------------------------------------------------------------- /Lab2/src/not_implemented.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/lxthnu/CloudComputingLabs/74dcd2c1e4dd5d97615173a6aaedc7927bac9c07/Lab2/src/not_implemented.png -------------------------------------------------------------------------------- /Lab2/src/not_implemented_curl.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/lxthnu/CloudComputingLabs/74dcd2c1e4dd5d97615173a6aaedc7927bac9c07/Lab2/src/not_implemented_curl.png -------------------------------------------------------------------------------- /Lab2/src/post_404_curl.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/lxthnu/CloudComputingLabs/74dcd2c1e4dd5d97615173a6aaedc7927bac9c07/Lab2/src/post_404_curl.png -------------------------------------------------------------------------------- /Lab2/src/post_curl.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/lxthnu/CloudComputingLabs/74dcd2c1e4dd5d97615173a6aaedc7927bac9c07/Lab2/src/post_curl.png -------------------------------------------------------------------------------- /Lab3/README.md: -------------------------------------------------------------------------------- 1 | # Lab 3: A Simple Distributed Key-Value Store 2 | 3 | Enter in the folder you have cloned from our lab git repo, and pull the latest commit. 4 | 5 | `git pull` 6 | 7 | You can find this lab3's instruction in `Lab3/README.md` 8 | 9 | All materials of lab3 are in folder `Lab3/` 10 | 11 | ## 1. Overview 12 | 13 | Implement a simple distributed in-memory key-value database (KV store) by your own, using two-phase commit protocol to guarantee the consistency and robustness of your KV store. 14 | 15 | ### Goals 16 | 17 | * Get to know the problems and difficulties in building a distributed system; 18 | * Know how to use a simple protocol to maintain consistency between multiple distributed servers; 19 | * Use some simple schemes to handle server failures. 20 | 21 | ## 2. Background 22 | 23 | ### 2.1 KV store 24 | 25 | An in-memory key-value database (also called **key-value store**, or **KV store** in this document) is a database that keeps all its data in the main memory and uses a simple key-value data structure. 26 | 27 | Typically, a KV-store exposes the following methods for users to store/delete/read data to/from the databases: 28 | 29 | - **set(key, value)**: stores the value "value" with the key "key" (some KV stores also call this command as "**put**"). 30 | - **del(key)**: deletes any record associated with the key "key". 31 | - **value=get(key)**: retrieves and returns the value associated with the key "key". 32 | 33 | In practice, in-memory KV store serves most user requests only with data stored in the main memory, meanwhile, it often backups its data in the hard disks thus to be durable. However, in this lab, you are not required to consider the data durability (i.e., you can only store the data in main memory). 34 | 35 | ### 2.2 Distributed KV store 36 | 37 | In large-scale cloud services, KV stores are often built in distributed manner, for the sake of **performance and robustness**. 38 | 39 | For example, a KV store may distribute its data in multiple server machines, and simultaneously use those servers to serve user requests. As such, user requests can be evenly balanced to multiple servers when the load is high, and the database can survive from the failure of some servers. 40 | 41 | However, when the KV database is distributed, many problems arise. Among those problems, **consistency issue** may be most notorious and toughest one. For example, assume that a KV database uses two servers A and B to hold data and serve user requests. When user 1 put some key at server A, and then after a very short time user 2 and 3 each posts a get request of this key to server A and B, respectively, then how to make sure that user 2 and 3 both **get the same latest value of this key**? What is more challenging, failures can happen on servers and networks when users are posting requests. 42 | 43 | Next, we will introduce a very simple but classic protocol to ensure consistency among distributed database servers. 44 | 45 | ### 2.3 Two-phase commit 46 | 47 | Now we describe possibly the simplest (but it works!) consensus protocol called **two-phase commit**, or **2PC**. This protocol can ensure the data consistency when the database is located on multiple distributed servers, that is, **two or more machines agree to do something, or not do it, atomically**. Note that this is only a very short introduction. You are encouraged to search more materials if you have further questions (e.g., [this](https://www.bilibili.com/video/BV1at411y7iQ) is a good video about 2PC). 48 | 49 | Frist, 2PC maintains a **commit log** on each machine, which keeps track of whether commit has happened. Log is used to guarantee that all machines either commit or don’t. 50 | 51 | Second, there is **one global coordinator**. It receives transactions from clients (e.g., set/delete/get) and reply results to clients, and coordinates multiple database servers, to ensure either all servers commit the transaction or all abort it. 52 | 53 | Based on above architecture, 2PC operates in two distinct phases: 54 | 55 | 1) The first phase is **prepared phase**. The global coordinator requests that all database servers (called participants) will promise to commit or rollback the transaction (e.g., set or delete a key) . Participants record promise in log, then acknowledge. If anyone votes to abort, coordinator writes "Abort" in its log and tells everyone to abort; each records "Abort" in log. 56 | 57 | 2) The second phase is **commit-or-abort phase**. After all participants respond that they are prepared, then the coordinator writes "Commit" to its log. Then the coordinator asks all participants to commit; All participants respond with ACK. After receive ACKs, the coordinator writes "Got Commit" to log. 58 | 59 | two phase commit 60 | 61 | The detailed steps in 2PC are as follows: 62 | 63 | ***Prepared phase:*** 64 | 65 | 1) To commit the transaction, the coordinator starts by sending a **REQUEST-TO-PREPARE** message to each 66 | participant. 67 | 68 | 2) The coordinator waits for all participants to "vote" on the request. 69 | 70 | 3) In response to receiving a **REQUEST-TO-PREPARE** message, each participant votes by sending a message back to the coordinator, as follows: 71 | 72 | - It votes **PREPARED** if it is prepared to commit. 73 | - It may vote **NO** for any reason, usually because it cannot prepare the transaction due to a local failure. 74 | - It may delay voting indefinitely, for example, because the network drops the vote. 75 | 76 | ***Commit-Or-Abort phase:*** 77 | 78 | 1) If the coordinator receives **PREPARED** messages from all participants, it decides to commit. The transaction is now officially committed. Otherwise, it either received a **NO** message or gave up waiting for some participant, so it decides to abort. 79 | 80 | 2) The coordinator sends its decision to all participants (i.e.,**COMMIT** or **ABORT**). 81 | 82 | 3) Participants acknowledge receipt of the commit or abort by replying **DONE**. 83 | 84 | 4) After receiving **DONE** from all participants, the coordinator can reply clients with the transaction result (either success or failed), and *forget* the transaction, meaning that it can deallocate any memory it was using to keep track of information about the transaction. 85 | 86 | ## 3. Your Lab Task 87 | 88 | ### 3.1 Task overview 89 | 90 | KVStoreOverview 91 | 92 | You need to implement a simple distributed KV store. Your KV store should run as a network service on remote machine(s), which can receive clients' operations on the database and return results to clients, through network messages. To cope with failures, your are required to implement your KV store services on multiple machines (which are connected with each other through network). Use 2PC protocol to maintain database consistency among multiple machines. 93 | 94 | To simplify the task, your KV store data is only stored in main memory. Also, the log in 2PC protocol is also only stored in main memory. 95 | 96 | Detailed lab requirements are discussed below. 97 | 98 | ### 3.2 KV store command formats 99 | 100 | Your KV store servers are only required to support three database commands: `SET`, `GET` and `DEL` commands (case sensitive). These commands (including arguments) and the return results are encapsulated into network messages using dedicated message format. For simplicity, all the keys and values are stored as strings in your KV store. 101 | 102 | Further details are as follows: 103 | 104 | #### 3.2.1 Network message format 105 | 106 | In this lab, you should use a **simplified version** of RESP (REdis Serialization Protocol) message format to pass KV store commands from clients to servers (called request message) and pass command results from server to clients (called response message) . Specifically: 107 | 108 | ##### 3.2.1.1 Client request message 109 | 110 | Clients send commands to the server using RESP Arrays (more details see `section 3.2.2`). RESP Arrays consist of: 111 | 112 | - A `*` character as the first byte, followed by the number of elements in the array as a decimal number, followed by CRLF. 113 | - Arbitrary number of bulk strings (up to 512 MB in length). 114 | 115 | The bulk string consist of: 116 | 117 | - A `$` byte followed by the number of bytes composing the string (a prefixed length), terminated by CRLF. 118 | - The actual string data. 119 | - A final CRLF. 120 | 121 | For example, the string `CS06142` is encoded as follows: 122 | 123 | `$7\r\nCS06142\r\n` 124 | 125 | The bulk string `$7\r\nCS06142\r\n` start with a `$` byte, and the following number 7 indicate that the length of string `CS06142` is 7. Then, the terminated CRLF, actual string data `CS06142` and the final CRLF are next, consecutively. 126 | 127 | ##### 3.2.1.2 Server response message 128 | 129 | 1) Success message: 130 | 131 | Success messages are encoded in the following way: a plus '+' character, followed by a string that cannot contain a CR or LF character (no newlines are allowed), terminated by CRLF (that is "\r\n"). 132 | 133 | For example, the `SET` command reply with just "OK" on success (more details see `section 3.2.2`): 134 | 135 | `+OK\r\n` 136 | 137 | 2) Error message: 138 | 139 | Like success messages, error messages consist of: a minus '-' character, followed by a string, terminated by CRLF. 140 | 141 | For example, if an error occurs, just return (more details see `section 3.2.2`): 142 | 143 | `-ERROR\r\n` 144 | 145 | 3) RESP Arrays message: 146 | 147 | Your server should return an RESP Arrays message when the `GET` command executed successfully (more detail see `section 3.2.2`). 148 | 149 | For example: 150 | 151 | `*2\r\n$5\r\nCloud\r\n$9\r\nComputing\r\n` 152 | 153 | 4) Integer message: 154 | 155 | Some commands need to return an integer (e.g., `DEL` command, more details see `section 3.2.2`). An integer message is just a CRLF terminated string representing an integer, prefixed by a ":" byte. 156 | 157 | An integer message example: 158 | 159 | `:1\r\n` 160 | 161 | #### 3.2.2 Database commands 162 | 163 | ##### 3.2.2.1 SET command 164 | 165 | `SET key value` 166 | 167 | The function of the `SET` command is to set **key** to hold the string **value**. If key already holds a value, it is overwritten. For example, if you want to set key `CS06142` to hold the string `Cloud Computing`, the command would be: 168 | 169 | `SET CS06142 "Cloud Computing"` 170 | 171 | According to the message format we have discussed in `section 3.2.1`, this command would be encoded as a RESP message format: 172 | 173 | `*4\r\n$3\r\nSET\r\n$7\r\nCS06142\r\n$5\r\nCloud\r\n$9\r\nComputing\r\n` 174 | 175 | **Note:** The encoded message start with a `*` byte. The following number 4 indicate that there are 4 bulk strings in this message. These bulk strings are `$3\r\nSET\r\n`, `$7\r\nCS06142\r\n`, `$5\r\nCloud\r\n`, and `$9\r\nComputing\r\n`. 176 | 177 | 178 | If the `SET` operation succeeds, the server will return a success message; otherwise, return an error message. 179 | 180 | For example, if the `SET` operation succeeds, the server just returns: 181 | 182 | `+OK\r\n` 183 | 184 | Otherwise, it returns: 185 | 186 | `-ERROR\r\n` 187 | 188 | ##### 3.2.2.2 GET command 189 | 190 | `GET key` 191 | 192 | `GET` command can get the **value** of **key**. If the key does not exist the special value `nil` is returned. 193 | 194 | For example, if you want to check the value of the key `CS06142`, construct the command like this: 195 | 196 | `GET CS06142` 197 | 198 | Like the `GET` command, this command should be encoded as a specific message format before sending to the server. 199 | 200 | `*2\r\n$3\r\nGET\r\n$7\r\nCS06142\r\n` 201 | 202 | If the `GET` command was executed correctly, the value (encoded as RESP Arrays format) of the key will be returned. 203 | 204 | For example, if the command above executed correctly, return: 205 | 206 | `*2\r\n$5\r\nCloud\r\n$9\r\nComputing\r\n` 207 | 208 | , assuming the value of the key `CS06142` is`Cloud Computing`. 209 | 210 | If the key does no exist, just return: 211 | 212 | `*1\r\n$3\r\nnil\r\n` 213 | 214 | If an error occurs, return an error message: 215 | 216 | `-ERROR\r\n` 217 | 218 | ##### 3.2.2.3 DEL command 219 | 220 | `DEL key1 key2 ...` 221 | 222 | The `DEL` command is used for removing one or more specified **keys** (arbitrary number, up to 512 MB message length). A key is ignored if it does not exist. 223 | 224 | The `DEL` command should return the number of keys that were removed. 225 | 226 | For example, if you want to delete key `CS06142` and key `CS162`, you can construct the `DEL` command: 227 | 228 | `DEL CS06142 CS162` 229 | 230 | Similar to the `SET` and `GET` commands, the `DEL` command will be encoded in RESP message as follows: 231 | 232 | `*3\r\n$3\r\nDEL\r\n$7\r\nCS06142\r\n$5\r\nCS162\r\n` 233 | 234 | The server will return the number of keys that were removed. 235 | 236 | For example, if the `DEL` command above executed, return an integer message: 237 | 238 | `:1\r\n` 239 | 240 | **note:** Because we only set the key `CS06142` to hold a value. As for key `CS162`, it will be ignored because it does no exist. So, the number in the integer message is 1. 241 | 242 | If an error occurs, return an error message: 243 | 244 | `-ERROR\r\n` 245 | 246 | ### 3.3 Use 2PC protocol to build a KV store on multiple servers 247 | 248 | You should implement the coordinator and participant program. 249 | 250 | The **coordinator** does not store any data. It only receives and parses KV commands from clients, runs 2PC protocol to coordinates participants to conduct the KV commands consistently, and reply command results to clients. *There is only one coordinator in the whole system*. 251 | 252 | Each **participant** maintains a KV database in its main memory, and conduct KV commands sent from the coordinator, and return results to the coordinator. 253 | 254 | You can use any message format for communication between the coordinator and participants. For example, you can also use the RESP format introduced before, or use some other RPC library. 255 | 256 | ### 3.4 Run your program 257 | 258 | #### 3.4.1 Program arguments 259 | 260 | Enable long options to accept arguments in your program, just like lab2. There should be one and only one argument for your program: `--config_path`, which specifies the path of the configuration file. All the detailed configurations are written in the configuration file. Your program should read and parse the configuration file, and run as coordinator or participant accordingly. 261 | 262 | If your program is called **kvstore2pcsystem**: 263 | 264 | run the **coordinator** process, just typing (`./src/coordinator.conf` is the coordinator's configuration file) 265 | 266 | `./kvstore2pcsystem --config_path ./src/coordinator.conf` 267 | 268 | run the **participant** process, just typing (`./src/participant.conf` is the participant's configuration file) 269 | 270 | `./kvstore2pcsystem --config_path ./src/participant.conf` 271 | 272 | When you run the command above, your program should run correctly without any further inputs. 273 | 274 | #### 3.4.2 Configuration file format 275 | 276 | A configuration file consists of two kinds of lines: 1) parameter line, and 2) comment line. 277 | 278 | - **A comment line** starts with a character '!'. The whole comment line are not parsed by the program. 279 | - **A parameter line** starts with a *parameter*, followed by a *value*. The parameter and value are separated by a whitespace. Parameter lines specify the necessary information that the coordinator or participants should know before running. There are three valid parameters: `mode`, `coordinator_info`, and `participant_info`. 280 | - The parameter `mode` specifies that whether the program runs as a coordinator or a participant. Its value should only be either `coordinator` or `participant`. `mode` line is always *the first parameter line* in the configuration file. 281 | - The parameter `coordinator_info` specifies the network address that the coordinator is listening on. Its value consists of the IP address and port number (separated by character ':'). Clients and participants can communicate with the coordinator using this network address. Since there is only one coordinator, there is only one `coordinator_info` line in both coordinator's and participants' configuration file. 282 | - The parameter `participant_info` consists of the network address that participant process is listening on. Its value consists of the IP address and port number (separated by character ':'). The coordinator can communicate with the participant using this network address. For participants, there is only one `participant_info` line in the configuration file, specifying its own network address; For the coordinator, there can be multiple `participant_info` lines in the configuration file, specifying the network addresses of all participants. 283 | 284 | Sample coordinator configuration file: 285 | 286 | ``` 287 | ! 288 | ! Coordinator configuration 289 | ! 2020/05/07 11:25:33 290 | ! 291 | ! The argument name and value are separated by whitespace in the configuration file. 292 | ! 293 | ! Mode of process, coordinator OR participant 294 | mode coordinator 295 | ! 296 | ! The address and port the coordinator process is listening on. 297 | ! Note that the address and port are separated by character ':'. 298 | coordinator_info 127.0.0.1:8001 299 | ! 300 | ! Address and port information of all participants. 301 | ! Three lines specifies three participants' addresses. 302 | participant_info 127.0.0.1:8002 303 | participant_info 127.0.0.1:8003 304 | participant_info 127.0.0.1:8004 305 | ``` 306 | 307 | Sample participant configuration file: 308 | 309 | ``` 310 | ! 311 | ! Participant configuration 312 | ! 2020/05/07 11:25:33 313 | ! 314 | ! The argument name and value are separated by whitespace in the configuration file. 315 | ! 316 | ! Mode of process, coordinator OR participant 317 | mode participant 318 | ! 319 | ! The address and port the participant process is listening on. 320 | participant_info 127.0.0.1:8002 321 | ! 322 | ! The address and port the coordinator process is listening on. 323 | coordinator_info 127.0.0.1:8001 324 | ``` 325 | 326 | ### 3.5 Implementation requirements 327 | 328 | #### 3.5.1 Basic version 329 | 330 | Your program should complete all the tasks described in `section 3.1-3.4`. Your system is required to correctly receive and conduct the KV commands, and reply the corresponding results, as described before. 331 | 332 | In the basic version, there will be **no participant failures**. Also, we will **not inject any network failures**. However, the network may still drop packets occasionally. You can use TCP to handle such occasional drops. 333 | 334 | **The coordinator process may be killed and restart at any time for multiple times**. So do not store any database data in the coordinator. The coordinator will deal with clients' KV commands when it is working. When the coordinator is killed, your system is not required to reply any client's commands. Clients will keep retransmit its KV commands until it gets success response from the coordinator. The coordinator remembers no history (except for the information in the configuration file), so it will deal with all commands as new ones after it restarts. 335 | 336 | Your program should run correctly with 3 or more participants. 337 | 338 | #### 3.5.2 Advanced version 339 | 340 | Your program should complete all the tasks described in `section 3.1-3.4`. Your system is required to correctly receive and conduct the KV commands, and reply the corresponding results, as described before. 341 | 342 | In the advanced version, **participants may fail, and the network links may fail**. However, the participant and network link **failures are one-shot**, that is, if they fail, they will never come back again. Also, **the coordinator process may be killed and restart at any time for multiple times**. The coordinator will deal with clients' KV commands when it is working. When the coordinator is killed, your system is not required to reply any client's commands. 343 | 344 | When the coordinator is working, it should be able to detect the failure of participants. You can use some periodical heartbeat messages to detect the participant failure (e.g., no reply after certain number of heartbeats). **Once a participant is dead, the coordinator should be able to remove it from the system, and correctly receive/conduct/reply clients' KV commands with the rest participants**. If all participants fail, the coordinator will always reply ERROR to the clients' KV commands. The coordinator remembers no history (except for the information in the configuration file), so it need to redetect all the participants' liveness after restart. 345 | 346 | Your program should run correctly with 3 or more participants. 347 | 348 | **NOTE**: **Groups that have registered for demo 3 should at least finish the advanced version.** 349 | 350 | #### **3.5.3 Extreme version** 351 | 352 | Your program should complete all the tasks described in `section 3.1-3.4`. Your system is required to correctly receive and conduct the KV commands, and reply the corresponding results, as described before. 353 | 354 | In the extreme version, **participants may fail, and the network links may fail**. The participant and network link **failures can be both permanent or transient**, that is, if they fail, they may come back again at any time. Also, **the coordinator process may be killed and restart at any time for multiple times**. The coordinator will deal with clients' KV commands when it is working. When the coordinator is killed, your system is not required to reply any client's commands. 355 | 356 | When the coordinator is working, it should be able to detect **both failure and recovery** of participants. Once a participant is dead, the coordinator should be able to remove it from the system; Once a participant is recovered, the coordinator should be able to add it back to the system. Note that to keep database consistent, after a participant recovers from failure, you should copy the latest KV store database from some working participants to this recovered participant. We will not provide any copy protocols for you. You are encouraged to devise your own schemes as long as it is correct. You should be very careful about the consistency issue since the failures can be very complex and random. For example, considering the case that there are two participants A and B, A fails first and then A comes back and B fails later. During this procedure, client's may keep sending KV commands, so A needs to sync those new KV commands after coming back, otherwise it cannot server client's request correctly after B fails. 357 | 358 | We will randomly inject failure and recovery to all the participants and network links. To ensure the database can be successfully copied, during our test, after a participant (or its network link) is recovered from failure, we will ensure that *no failures happen in the following 10 seconds* (no coordinator/participant/network failure). Your coordinator should be able to copy the latest database to the newly recovered participant in this 10 seconds. Moreover, we will always ensure that *there is at least one working participant* in the system. As such, the coordinator should be able to correctly receive/conduct/reply clients' KV commands during the failures and recoveries. 359 | 360 | Your program should run correctly with 3 or more participants. 361 | 362 | **NOTE**: **Groups that have registered for demo 4 should at least finish the extreme version.** 363 | 364 | #### **3.5.6 Ultimate version** 365 | 366 | Since the coordinator may permanently fail, your system should also **be able to deal with clients' requests even when coordinator fails**. 2PC is not able to handle this problem. So in this version, you will not use 2PC protocol, but use some advanced consensus protocol to handle this case. 367 | 368 | You can implement multiple KV store servers, where each server can receive requests from clients, stores data, and reply responses. Clients are preconfigured with all servers' addresses, and may send KV commands to any of the server, randomly. To keep consistency, normally there is only one leader server that deal with all the clients' requests, and backup the data in other servers. Clients' commands to other servers are all redirected to the leader. The consensus protocol can help servers to detect the failure of the leader server, and reelect a new leader. Also, the consensus protocol can help to maintain database consistency among multiple servers. 369 | 370 | [Raft](https://raft.github.io/) is a very good consensus protocol for this purpose. You may want to read its paper by yourself and use raft to implement this version (there are many open-sourced raft implementation that you can borrow). Sorry I'm not going to teach you this :) Of course, it is always good to use other consensus protocols or even your own schemes. 371 | 372 | **NOTE**: **This version is very difficult, so it is not compulsory but just a challenge. Have fun!** 373 | 374 | ## 4. Lab submission 375 | 376 | Please put all your code in folder `Lab3` and write a `Makefile` so that we **can compile your code in one single command** `make`. The compiled runnable executable binary should be named `kvstore2pcsystem` and located in folder `Lab3`. Please carefully following above rules so that TAs can automatically test your code!!! 377 | 378 | You can use any available code or library for this lab. Please search the Internet. However, do not copy other teams' code. No performance test report is required for this lab. Enjoy the lab :) 379 | 380 | Please submit your lab program following the guidance in the [Overall Lab Instructions](../README.md) (`../README.md`) 381 | 382 | ## 5. Grading standards 383 | 384 | 1. You can get 13 points if you can finish all the requirements of the basic version. If you missed some parts, you will get part of the points depending how much you finished. 385 | 2. You can get 21 points if you can finish all the requirements of the advanced version. If you missed some parts, you will get part of the points depending how much you finished. 386 | 3. You can get 24 points if you can finish all the requirements of the extreme version. If you missed some parts, you will get part of the points depending how much you finished. 387 | 4. You can get 25 points if you can finish all the requirements of the ultimate version. If you missed some parts, you will get part of the points depending how much you finished. -------------------------------------------------------------------------------- /Lab3/src/KVStoreOverview.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/lxthnu/CloudComputingLabs/74dcd2c1e4dd5d97615173a6aaedc7927bac9c07/Lab3/src/KVStoreOverview.jpg -------------------------------------------------------------------------------- /Lab3/src/KVStoreOverview.pptx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/lxthnu/CloudComputingLabs/74dcd2c1e4dd5d97615173a6aaedc7927bac9c07/Lab3/src/KVStoreOverview.pptx -------------------------------------------------------------------------------- /Lab3/src/coordinator_sample.conf: -------------------------------------------------------------------------------- 1 | ! 2 | ! Coordinator configuration 3 | ! 2020/05/07 11:25:33 4 | ! 5 | ! The argument name and value are separated by whitespace in the configuration file. 6 | ! 7 | ! Mode of process, coordinator OR participant 8 | mode coordinator 9 | ! 10 | ! The address and port the coordinator process is listening on. 11 | ! Note that the address and port are separated by character ':'. 12 | coordinator_info 127.0.0.1:8001 13 | ! 14 | ! Address and port information of all participants. 15 | ! Three lines specifies three participants' addresses. 16 | participant_info 127.0.0.1:8002 17 | participant_info 127.0.0.1:8003 18 | participant_info 127.0.0.1:8004 -------------------------------------------------------------------------------- /Lab3/src/participant_sample.conf: -------------------------------------------------------------------------------- 1 | ! 2 | ! Participant configuration 3 | ! 2020/05/07 11:25:33 4 | ! 5 | ! The argument name and value are separated by whitespace in the configuration file. 6 | ! 7 | ! Mode of process, coordinator OR participant 8 | mode participant 9 | ! 10 | ! The address and port the participant process is listening on. 11 | participant_info 127.0.0.1:8002 12 | ! 13 | ! The address and port the coordinator process is listening on. 14 | coordinator_info 127.0.0.1:8001 -------------------------------------------------------------------------------- /Lab3/src/two-phase-commit.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/lxthnu/CloudComputingLabs/74dcd2c1e4dd5d97615173a6aaedc7927bac9c07/Lab3/src/two-phase-commit.png -------------------------------------------------------------------------------- /Lab4/README.md: -------------------------------------------------------------------------------- 1 | # Lab 4: A "Serious" Web-Retail System -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Cloud Computing: Overall Lab Instruction 2 | 3 | 4 | 5 | ## 1. Overview 6 | 7 | There are **4 labs in total** in this course. All the materials of each lab are under folders Lab1-4 in this repo. Please clone the lab git repo onto your local computer, 8 | 9 | `git clone https://github.com/1989chenguo/CloudComputingLabs.git` 10 | 11 | and always track our latest lab materials using the following commands (should first enter the folder you have cloned from our lab repo) 12 | 13 | `git pull` 14 | 15 | You can find this overall lab instruction in `README.md` in the root folder. 16 | 17 | Please **carefully read the overall lab instruction before you do anything**. 18 | 19 | Also, please **carefully read each lab's instruction** ([Lab1](Lab1/README.md), [Lab2](Lab2/README.md), [Lab3](Lab3/README.md), [Lab4](Lab4/README.md)) to get each lab's task, background, requirements, etc. 20 | 21 | ## 2. Group collaboration 22 | 23 | Each student should register your own github account. Group members should use **git and github** to collaborate. 24 | 25 | All the labs are done in the unit of group, i.e., a group only needs to submit one piece of code for each lab. However, each group member should make enough contribution to the lab. Teaching assistants will check the **git commit history** to evaluate each one’s contribution. 26 | 27 | ## 3. Code submission 28 | 29 | Each group should create a code repo for our course (create your own group's repo, do not push onto my course lab repo!). The group leader should send an email to TA telling us your group's lab git repo address. For example, https://github.com/group1/CloudComputingLabs.git` 30 | 31 | **All the lab code should be submitted through pushing to your group's github code repo.** Teaching assistants will checkout your commit, and read and test your codes from the above repo address you provided us. The code of different lab should be in different folders, named Lab1/Lab2/Lab3/Lab4, respectively (following the same structure of this repo). Please note that your lab folder name should be exactly same as above (be careful about the first capital letter and no space before the number), otherwise your code may fail in our TAs' automatic testing scripts. All lab codes should be in the same course git repo of your group. 32 | 33 | Please write a README.md to each lab code folder, briefly introducing how to run your lab code (including how to set the environment, provide the input, and explain the output, etc.). Keep the README short and clear! Also, your code should be well commented so that other people can understand without asking you. 34 | 35 | ## 4. Environment requirement 36 | 37 | ### 4.1 OS requirement 38 | 39 | All the labs should be tested and runnable on UNIX-like operating systems, such as Linux distributions (e.g., Ubuntu, CentOS) and MacOS. We highly recommend you to use Linux distributions such as Ubuntu. 40 | If you only have windows PC or laptops, install a UNIX VM and do experiments on the VM. 41 | 42 | ### 4.2 Programming language 43 | 44 | Any programming languages are permitted in all labs, such as C/C++, Java, Go, Python, Perl. But for performance consideration, we highly recommend you to use C/C++ or Go !!! 45 | 46 | ### 4.3 Try to only use standard API 47 | 48 | To make your program portable, try your best to only use standard & widely available functions and normal libraries (such as `glibc`, `C++ STLs` and some typical math libraries). All the labs should only use standard system API defined by POSIX specification or Linux man page specification. We prefer to use standard POSIX API, so your code can be easily runnable on various kind of UNIX-like systems (instead of only on Linux). 49 | 50 | ## 5. Grading 51 | 52 | Grading details are specified in each lab's instruction document, please carefully read them [Lab1](Lab1/README.md), [Lab2](Lab2/README.md), [Lab3](Lab3/README.md), [Lab4](Lab4/README.md). 53 | 54 | Besides, we have the following 3 overall grading requirements applicable to all the 4 labs: 55 | 56 | 1. **DO NOT copy** others' code (either from the Internet or from your classmates), otherwise your group (every member and the leader) will got **zero point** in the lab. However, we encourage to communicate with other group and learn from each other. But do remember to write the code yourself and not copy. 57 | 2. **DO NOT miss the deadline**, otherwise your group (every member and the leader) points will be reduced accordingly. 58 | 3. Typically, your group (every member and the leader) will get same points in each lab, unless we find severely **unfair contribution** in the git commit history. In the overall grading, the leader will get some more points as bonus. 59 | --------------------------------------------------------------------------------