准备工作
1.Linux系统
2.安装redis(也可以安装docker,然后再docker中装redis,本文章就直接用Linux安装redis做演示)
redis下载地址:http://download.redis.io/releases/redis-4.0.14.tar.gz
修改redis,开启远程访问
找到redis中的redis.conf文件并编辑(在安装路径中找到)
vim ./redis.conf
1、找到bind 127.0.0.1并注释掉
默认127.0.0.1只能本地访问,注释掉即可ip访问
2、修改 protected-mode 属性值为no
注释掉并把保护模式禁用以后可以IP访问
3、修改daemonize属性将no 改为yes
将daemonize设置为yes即启动后台运行
4、开放6379端口
/sbin/iptables -I INPUT -p tcp --dport 6379 -j ACCEPT
默认不对外开放6379
5、启动redis
redis-server /myconf/redis.conf
redis-server默认在/usr/local/bin路径下,redis.conf在redis的安装路径下
6、测试连接
redis-cli -h 192.168.126.129 -p 6379
redis-cli -h redis服务器IP -p 6379 -a 密码(没有设置redis密码不要写空,否则报错)
Java代码编写
目录结构
项目源码结构
一个user表
代码
pom.xml文件(可以根据自己的需要来添加或修改)
org.springframework.boot spring-boot-starter-web org.mybatis.spring.boot mybatis-spring-boot-starter 1.3.2 mysql mysql-connector-java 5.1.39 org.springframework.boot spring-boot-starter-test test org.springframework.boot spring-boot-starter-data-redis org.springframework.boot spring-boot-starter-cache
下面是springboot的配置文件application.yml,配置redis(里面都有注释解释)
server: port: 8081 #数据库连接 spring: datasource: url: jdbc:mysql://localhost:3306/mytest_springboot_cache?useUnicode=true driver-class-name: com.mysql.jdbc.Driver username: root password: lzh ## Redis 配置 redis: ## Redis数据库索引(默认为0) database: 0 ## Redis服务器地址 host: 192.168.126.129 ## Redis服务器连接端口 port: 6379 ## Redis服务器连接密码(默认为空) password: jedis: pool: ## 连接池最大连接数(使用负值表示没有限制) #spring.redis.pool.max-active=8 max-active: 8 ## 连接池最大阻塞等待时间(使用负值表示没有限制) #spring.redis.pool.max-wait=-1 max-wait: -1 ## 连接池中的最大空闲连接 #spring.redis.pool.max-idle=8 max-idle: 8 ## 连接池中的最小空闲连接 #spring.redis.pool.min-idle=0 min-idle: 0 ## 连接超时时间(毫秒) timeout: 1200 #将themilef的默认缓存禁用,热加载生效 thymeleaf: cache: false #mybatis的下划线转驼峰配置 configuration: map-underscore-to-camel-case: true #另外一种打印语句的方式 log-impl: org.apache.ibatis.logging.stdout.StdOutImpl #打印sql时的语句 logging: level: com: acong: dao: debug file: d:/logs/bsbdj.log
接着是实体类,这个比较简单就不多说了
package com.lzh.springbootstudytest.bean; import java.io.Serializable; /** * @author lzh * create 2019-09-18-22:32 */ public class User implements Serializable { private static final long serialVersionUID = 1L; private int uid; private String userName; private String passWord; private int salary; public int getUid() { return uid; } public void setUid(int uid) { this.uid = uid; } public String getUserName() { return userName; } public void setUserName(String userName) { this.userName = userName; } public String getPassWord() { return passWord; } public void setPassWord(String passWord) { this.passWord = passWord; } public int getSalary() { return salary; } public void setSalary(int salary) { this.salary = salary; } public User(int uid, String userName, String passWord, int salary) { super(); this.uid = uid; this.userName = userName; this.passWord = passWord; this.salary = salary; } public User() { super(); } }
这是controller类,用于暴露接口访问
package com.lzh.springbootstudytest.controller; import com.lzh.springbootstudytest.bean.User; import com.lzh.springbootstudytest.service.UserService; import org.springframework.beans.factory.annotation.Autowired; import org.springframework.stereotype.Controller; import org.springframework.web.bind.annotation.RequestMapping; import org.springframework.web.bind.annotation.RequestParam; import org.springframework.web.bind.annotation.ResponseBody; import org.springframework.web.bind.annotation.RestController; import java.util.HashMap; import java.util.List; import java.util.Map; /** * @author lzh * create 2019-09-18-22:36 */ @RestController public class TestController { @Autowired private UserService userService; @RequestMapping("/queryAll") public ListqueryAll(){ List lists = userService.queryAll(); return lists; } @RequestMapping("/findUserById") public Map findUserById(@RequestParam int id){ User user = userService.findUserById(id); Map result = new HashMap<>(); result.put("uid", user.getUid()); result.put("uname", user.getUserName()); result.put("pass", user.getPassWord()); result.put("salary", user.getSalary()); return result; } @RequestMapping("/updateUser") public String updateUser(){ User user = new User(); user.setUid(1); user.setUserName("cat"); user.setPassWord("miaomiao"); user.setSalary(4000); int result = userService.updateUser(user); if(result != 0){ return "update user success"; } return "fail"; } @RequestMapping("/deleteUserById") public String deleteUserById(@RequestParam int id){ int result = userService.deleteUserById(id); if(result != 0){ return "delete success"; } return "delete fail"; } }
配置redistemplate序列化
package com.lzh.springbootstudytest.config; import com.fasterxml.jackson.annotation.JsonAutoDetect; import com.fasterxml.jackson.annotation.PropertyAccessor; import com.fasterxml.jackson.databind.ObjectMapper; import org.springframework.cache.CacheManager; import org.springframework.cache.annotation.CachingConfigurerSupport; import org.springframework.cache.annotation.EnableCaching; import org.springframework.context.annotation.Bean; import org.springframework.context.annotation.Configuration; import org.springframework.data.redis.cache.RedisCacheConfiguration; import org.springframework.data.redis.cache.RedisCacheManager; import org.springframework.data.redis.cache.RedisCacheWriter; import org.springframework.data.redis.connection.RedisConnectionFactory; import org.springframework.data.redis.core.*; import org.springframework.data.redis.serializer.Jackson2JsonRedisSerializer; import org.springframework.data.redis.serializer.StringRedisSerializer; import java.time.Duration; /** * @author lzh * create 2019-09-24-15:07 */ @Configuration @EnableCaching public class RedisConfig extends CachingConfigurerSupport { /** * 选择redis作为默认缓存工具 * @param redisConnectionFactory * @return */ /*@Bean //springboot 1.xx public CacheManager cacheManager(RedisTemplate redisTemplate) { RedisCacheManager rcm = new RedisCacheManager(redisTemplate); return rcm; }*/ @Bean public CacheManager cacheManager(RedisConnectionFactory redisConnectionFactory) { RedisCacheConfiguration redisCacheConfiguration = RedisCacheConfiguration.defaultCacheConfig() .entryTtl(Duration.ofHours(1)); // 设置缓存有效期一小时 return RedisCacheManager .builder(RedisCacheWriter.nonLockingRedisCacheWriter(redisConnectionFactory)) .cacheDefaults(redisCacheConfiguration).build(); } /** * retemplate相关配置 * @param factory * @return */ @Bean public RedisTemplateredisTemplate(RedisConnectionFactory factory) { RedisTemplate template = new RedisTemplate<>(); // 配置连接工厂 template.setConnectionFactory(factory); //使用Jackson2JsonRedisSerializer来序列化和反序列化redis的value值(默认使用JDK的序列化方式) Jackson2JsonRedisSerializer jacksonSeial = new Jackson2JsonRedisSerializer(Object.class); ObjectMapper om = new ObjectMapper(); // 指定要序列化的域,field,get和set,以及修饰符范围,ANY是都有包括private和public om.setVisibility(PropertyAccessor.ALL, JsonAutoDetect.Visibility.ANY); // 指定序列化输入的类型,类必须是非final修饰的,final修饰的类,比如String,Integer等会跑出异常 om.enableDefaultTyping(ObjectMapper.DefaultTyping.NON_FINAL); jacksonSeial.setObjectMapper(om); // 值采用json序列化 template.setValueSerializer(jacksonSeial); //使用StringRedisSerializer来序列化和反序列化redis的key值 template.setKeySerializer(new StringRedisSerializer()); // 设置hash key 和value序列化模式 template.setHashKeySerializer(new StringRedisSerializer()); template.setHashValueSerializer(jacksonSeial); template.afterPropertiesSet(); return template; } /** * 对hash类型的数据操作 * * @param redisTemplate * @return */ @Bean public HashOperations hashOperations(RedisTemplate redisTemplate) { return redisTemplate.opsForHash(); } /** * 对redis字符串类型数据操作 * * @param redisTemplate * @return */ @Bean public ValueOperations valueOperations(RedisTemplate redisTemplate) { return redisTemplate.opsForValue(); } /** * 对链表类型的数据操作 * * @param redisTemplate * @return */ @Bean public ListOperations listOperations(RedisTemplate redisTemplate) { return redisTemplate.opsForList(); } /** * 对无序集合类型的数据操作 * * @param redisTemplate * @return */ @Bean public SetOperations setOperations(RedisTemplate redisTemplate) { return redisTemplate.opsForSet(); } /** * 对有序集合类型的数据操作 * * @param redisTemplate * @return */ @Bean public ZSetOperations zSetOperations(RedisTemplate redisTemplate) { return redisTemplate.opsForZSet(); } }
接着是Mapper持久层Dao,这里主要用注解写比较方便,也可以使用mybatis的xml配置文件写sql语句
package com.lzh.springbootstudytest.mapper; import com.lzh.springbootstudytest.bean.User; import org.apache.ibatis.annotations.*; import java.util.List; /** * @author lzh * create 2019-09-18-22:32 */ @Mapper public interface UserDao { @Select("select * from user") ListqueryAll(); @Select("select * from user where uid = #{id}") User findUserById(int id); @Update("UPDATE USER SET username = CASE WHEN (#{userName} != NULL) AND (#{userName} != '') THEN #{userName},PASSWORD = CASE WHEN (#{passWord} != NULL) AND (#{passWord} != '') THEN #{passWord},salary = CASE WHEN (#{salary} != 0) THEN #{salary} WHERE uid = #{uid}") int updateUser(@Param("user") User user); @Delete("delete from user where uid = #{id}") int deleteUserById(int id); }
service层,这里主要是使用redis模板来写
package com.lzh.springbootstudytest.service; import com.lzh.springbootstudytest.bean.User; import com.lzh.springbootstudytest.mapper.UserDao; import org.springframework.beans.factory.annotation.Autowired; import org.springframework.data.redis.core.RedisTemplate; import org.springframework.data.redis.core.ValueOperations; import org.springframework.stereotype.Service; import java.util.List; import java.util.concurrent.TimeUnit; /** * @author lzh * create 2019-09-18-22:33 */ @Service public class UserService { @Autowired private UserDao userDao; @Autowired private RedisTemplate redisTemplate; public ListqueryAll() { return userDao.queryAll(); } /** * 获取用户策略:先从缓存中获取用户,没有则取数据表中 数据,再将数据写入缓存 */ public User findUserById(int id) { String key = "user_" + id; ValueOperations operations = redisTemplate.opsForValue(); //判断redis中是否有键为key的缓存 boolean hasKey = redisTemplate.hasKey(key); if (hasKey) { User user = operations.get(key); System.out.println("从缓存中获得数据:"+user.getUserName()); System.out.println("------------------------------------"); return user; } else { User user = userDao.findUserById(id); System.out.println("查询数据库获得数据:"+user.getUserName()); System.out.println("------------------------------------"); // 写入缓存 operations.set(key, user, 5, TimeUnit.HOURS); return user; } } /** * 更新用户策略:先更新数据表,成功之后,删除原来的缓存,再更新缓存 */ public int updateUser(User user) { ValueOperations operations = redisTemplate.opsForValue(); int result = userDao.updateUser(user); if (result != 0) { String key = "user_" + user.getUid(); boolean haskey = redisTemplate.hasKey(key); if (haskey) { redisTemplate.delete(key); System.out.println("删除缓存中的key-----------> " + key); } // 再将更新后的数据加入缓存 User userNew = userDao.findUserById(user.getUid()); if (userNew != null) { operations.set(key, userNew, 3, TimeUnit.HOURS); } } return result; } /** * 删除用户策略:删除数据表中数据,然后删除缓存 */ public int deleteUserById(int id) { int result = userDao.deleteUserById(id); String key = "user_" + id; if (result != 0) { boolean hasKey = redisTemplate.hasKey(key); if (hasKey) { redisTemplate.delete(key); System.out.println("删除了缓存中的key:" + key); } } return result; } }
这里主要是使用RedisTemplate来对远程redis操作,每次访问controller暴露的接口,首先判断redis缓存中是否存在该数据,若不存在就从数据库中读取数据,然后保存到redis缓存中,当下次访问的时候,就直接从缓存中取出来。这样就不用每次都执行sql语句,能够提高访问速度。 但是在保存数据到缓存中,通过设置键和值和超时删除,注意设置超时删除缓存时间不要太长,否则会给服务器带来压力。
执行spring boot的启动类,访问http://localhost:8081/findUserById?id=1
再次访问http://localhost:8081/findUserById?id=1就是从缓存中获取保存的数据