第四章秒杀压测
目录
1.SpringBoot打包
1.1SpringBoot打jar包
注意把packaging标签改为jar,此标签也可不写,springboot默认打包方式为jar。
<groupId>com.example</groupId>
<artifactId>springboot-upload</artifactId>
<version>0.0.1-SNAPSHOT</version>
<packaging>jar</packaging>
//注意把packaging标签改为jar,此标签也可不写,默认打包方式为jar。
<build>
<plugins>
<plugin>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-maven-plugin</artifactId>
<configuration>
<fork>true</fork>
</configuration>
</plugin>
</plugins>
</build>
使用idea打包: 在IDEA
右侧Maven Projects
栏双击package
等待Build Success
即可
使用命令行打包:
a.黑窗口cd到根目录(和pom.xml
、target
同级),也可在idea工具中选择Terminal
b.执行打包命令 mvn clean package
(跳过测试类命令 mvn clean package -Dmaven.test.skip=true
)
c.打包成功结果如下
运行jar包
java -jar jar包的名字.jar
1.2SpringBoot打war包
pom.xml
中把jar
改成war
,并且添加外置tomcat
依赖
<packaging>war</packaging>
<!--打包时排除tomcat-->
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-tomcat</artifactId>
<scope>provided</scope>
</dependency>
在这里将 scope
属性设置为provided
,这样在最终形成的 WAR
中不会包含这个JAR
包,因为Tomcat
或Jetty
等服务器在运行时将会提供相关的API
类。
在入口类中继承SpringBootServletInitializer
并重写configure
方法
@SpringBootApplication
public class SpringbootUploadApplication extends SpringBootServletInitializer {
public static void main(String[] args) {
SpringApplication.run(SpringbootUploadApplication.class, args);
}
@Override
protected SpringApplicationBuilder configure(SpringApplicationBuilder builder){
return builder.sources(SpringbootUploadApplication.class);
}
}
输入命令 mvn clean package
打包,把target
目录下生成的war
放到tomcat
的webapps
目录下即可。
运行tomcat就可以访问了
2.JMeter
2.1Windows下使用
基本结构有一个线程组包含:HTTP请求,HTTP请求默认值,CSV数据文件设置,聚合报告等。我们接下来说一下常用的操作。
线程组:可以设置线程数和循环次数
HTTP请求默认值:常用于设置域名或ip、端口号、协议,还可以添加参数
聚合报告:会显示吞吐率也就是我们常说的QPS
CSV数据文件设置:从文件中读取数据
数据文件如图
而对应改变的就是http请求的参数
2.2命令行下使用
1.在windows下录制好jmx,上传(设置好所用请求和参数)
2.命令行:sh jmeter.sh -n -t XXX.jmx -l result.jtl
3.把result.jtl导入jmeter
3.自定义变量模式多用户
public class UserUtil {
private static void createUser(int count) throws Exception{
List<MiaoshaUser> users = new ArrayList<MiaoshaUser>(count);
//生成用户
for(int i=0;i<count;i++) {
MiaoshaUser user = new MiaoshaUser();
user.setId(13000000000L+i);
user.setLoginCount(1);
user.setNickname("user"+i);
user.setRegisterDate(new Date());
user.setSalt("1a2b3c");
user.setPassword(MD5Util.inputPassToDbPass("123456", user.getSalt()));
users.add(user);
}
System.out.println("create user");
//插入数据库
Connection conn = DBUtil.getConn();
String sql = "insert into miaosha_user(login_count, nickname, register_date, salt, password, id)values(?,?,?,?,?,?)";
PreparedStatement pstmt = conn.prepareStatement(sql);
for(int i=0;i<users.size();i++) {
MiaoshaUser user = users.get(i);
pstmt.setInt(1, user.getLoginCount());
pstmt.setString(2, user.getNickname());
pstmt.setTimestamp(3, new Timestamp(user.getRegisterDate().getTime()));
pstmt.setString(4, user.getSalt());
pstmt.setString(5, user.getPassword());
pstmt.setLong(6, user.getId());
pstmt.addBatch();
}
pstmt.executeBatch();
pstmt.close();
conn.close();
System.out.println("insert to db");
//登录,生成token
String urlString = "http://localhost:8080/login/do_login";
File file = new File("D:/tokens.txt");
if(file.exists()) {
file.delete();
}
//RandomAccessFile
RandomAccessFile raf = new RandomAccessFile(file, "rw");
file.createNewFile();
raf.seek(0);
for(int i=0;i<users.size();i++) {
MiaoshaUser user = users.get(i);
URL url = new URL(urlString);
//HttpURLConnection
HttpURLConnection co = (HttpURLConnection)url.openConnection();
co.setRequestMethod("POST");
co.setDoOutput(true);
OutputStream out = co.getOutputStream();
String params = "mobile="+user.getId()+"&password="+MD5Util.inputPassToFormPass("123456")+"&ifyzm=2";
out.write(params.getBytes());
out.flush();
InputStream inputStream = co.getInputStream();
ByteArrayOutputStream bout = new ByteArrayOutputStream();
byte buff[] = new byte[1024];
int len = 0;
while((len = inputStream.read(buff)) >= 0) {
bout.write(buff, 0 ,len);
}
inputStream.close();
bout.close();
String response = new String(bout.toByteArray());
System.out.println(response);
JSONObject jo = JSON.parseObject(response);
String token = jo.getString("data");
System.out.println("create token : " + user.getId());
String row = user.getId()+","+token;
raf.seek(raf.length());
raf.write(row.getBytes());
raf.write("\r\n".getBytes());
System.out.println("write to file : " + user.getId());
}
raf.close();
System.out.println("over");
}
public static void main(String[] args)throws Exception {
createUser(5000);
}
}
4.Redis压测工具redis-benchmark
Redis 自带了一个叫 redis-benchmark
的工具来模拟 N 个客户端同时发出 M 个请求。 你可以使用 redis-benchmark -h 来查看基准参数。
以下参数被支持:
Usage: redis-benchmark [-h <host>] [-p <port>] [-c <clients>] [-n <requests]> [-k <boolean>]
-h <hostname> Server hostname (default 127.0.0.1)
-p <port> Server port (default 6379)
-s <socket> Server socket (overrides host and port)
-a <password> Password for Redis Auth
-c <clients> Number of parallel connections (default 50)
-n <requests> Total number of requests (default 100000)
-d <size> Data size of SET/GET value in bytes (default 2)
-dbnum <db> SELECT the specified db number (default 0)
-k <boolean> 1=keep alive 0=reconnect (default 1)
-r <keyspacelen> Use random keys for SET/GET/INCR, random values for SADD
Using this option the benchmark will expand the string __rand_int__
inside an argument with a 12 digits number in the specified range
from 0 to keyspacelen-1. The substitution changes every time a command
is executed. Default tests use this to hit random keys in the
specified range.
-P <numreq> Pipeline <numreq> requests. Default 1 (no pipeline).
-q Quiet. Just show query/sec values
--csv Output in CSV format
-l Loop. Run the tests forever
-t <tests> Only run the comma separated list of tests. The test
names are the same as the ones produced as output.
-I Idle mode. Just open N idle connections and wait.
1.redis-benchmark -h 127.0.0.1 -p 6379 -c 100 -n 100000
向127.0.0.1的6379端口,100个并发连接,100000个请求
2.redis-benchmark -h 127.0.0.1 -p 6379 -q -d 100
存取大小为100字节的数据包
3.redis-benchmark -t set,lpush -q -n 100000
只测试部分操作
4.redis-benchmark -n 100000 -q script load "redis.call('set','foo','bar')"
只测试某些数值存取的性能
综述
这一章节我们了解了JMeter,我们使用JMeter测试发现在目前,接口性能较差,QPS较低。我们使用redis-benchmark发现,redis的性能比数据库更加快速,说以,我们下一章节将对性能方面进行优化