springboot redis緩存配置

今天小編就為大家帶來一篇springboot redis緩存配置的文章。小編覺得挺實用的，為此分享給大家做個參考。一起跟隨小編過來看看吧。

開啟遠程訪問：

找到redis中的redis.conf文件并編輯（在安裝路徑中找到）

vim ./redis.conf

1、找到bind 127.0.0.1并注釋掉

默認127.0.0.1只能本地訪問，注釋掉即可ip訪問

2、修改 protected-mode 屬性值為no

注釋掉并把保護模式禁用以后可以IP訪問

3、修改daemonize屬性將no 改為yes

將daemonize設置為yes即啟動后臺運行

4、開放6379端口

/sbin/iptables -I INPUT -p tcp --dport 6379 -j ACCEPT

默認不對外開放6379

5、啟動redis

redis-server /myconf/redis.conf

redis-server默認在/usr/local/bin路徑下，redis.conf在redis的安裝路徑下

6、測試連接

redis-cli -h 192.168.126.129 -p 6379

redis-cli -h redis服務器IP -p 6379 -a 密碼（沒有設置redis密碼不要寫空，否則報錯）

java代碼編寫：

項目源碼結構

一個user表

代碼：

pom.xml文件（可以根據自己的需要來添加或修改）

<dependencies>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-web</artifactId>
        </dependency>

        <!-- mybatis 與 spring boot 2.x的整合包 -->
        <dependency>
            <groupId>org.mybatis.spring.boot</groupId>
            <artifactId>mybatis-spring-boot-starter</artifactId>
            <version>1.3.2</version>
        </dependency>

        <!--mysql JDBC驅動 -->
        <dependency>
            <groupId>mysql</groupId>
            <artifactId>mysql-connector-java</artifactId>
            <version>5.1.39</version>
        </dependency>

        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-test</artifactId>
            <scope>test</scope>
        </dependency>

        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-data-redis</artifactId>
        </dependency>

        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-cache</artifactId>
        </dependency>
    </dependencies>

下面是springboot的配置文件application.yml，配置redis（里面都有注釋解釋）

server:
  port: 8081
 
#數據庫連接
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數據庫索引（默認為0）
    database: 0
    ## Redis服務器地址
    host: 192.168.126.129
    ## Redis服務器連接端口
    port: 6379
    ## Redis服務器連接密碼（默認為空）
    password:
    jedis:
      pool:
        ## 連接池最大連接數（使用負值表示沒有限制）
        #spring.redis.pool.max-active=8
        max-active: 8
        ## 連接池最大阻塞等待時間（使用負值表示沒有限制）
        #spring.redis.pool.max-wait=-1
        max-wait: -1
        ## 連接池中的最大空閑連接
        #spring.redis.pool.max-idle=8
        max-idle: 8
        ## 連接池中的最小空閑連接
        #spring.redis.pool.min-idle=0
        min-idle: 0
    ## 連接超時時間（毫秒）
    timeout: 1200
 
  #將themilef的默認緩存禁用，熱加載生效
  thymeleaf:
    cache: false
 
  #mybatis的下劃線轉駝峰配置
  configuration:
    map-underscore-to-camel-case: true
 
    #另外一種打印語句的方式
    log-impl: org.apache.ibatis.logging.stdout.StdOutImpl
 
#打印sql時的語句
logging:
  level:
    com:
      acong:
        dao: debug
  file: d:/logs/bsbdj.log

接著是實體類，這個比較簡單就不多說了

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();
    }
}　

這是controller類，用于暴露接口訪問

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 List<User> queryAll(){
        List<User> lists = userService.queryAll();
        return lists;
    }
 
    @RequestMapping("/findUserById")
    public Map<String, Object> findUserById(@RequestParam int id){
        User user = userService.findUserById(id);
        Map<String, Object> 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 {
 
    /**
     * 選擇redis作為默認緩存工具
     * @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)); // 設置緩存有效期一小時
        return RedisCacheManager
                .builder(RedisCacheWriter.nonLockingRedisCacheWriter(redisConnectionFactory))
                .cacheDefaults(redisCacheConfiguration).build();
    }
 
    /**
     * retemplate相關配置
     * @param factory
     * @return
     */
    @Bean
    public RedisTemplate<String, Object> redisTemplate(RedisConnectionFactory factory) {
 
        RedisTemplate<String, Object> template = new RedisTemplate<>();
        // 配置連接工廠
        template.setConnectionFactory(factory);
 
        //使用Jackson2JsonRedisSerializer來序列化和反序列化redis的value值（默認使用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,以及修飾符范圍，ANY是都有包括private和public
        om.setVisibility(PropertyAccessor.ALL, JsonAutoDetect.Visibility.ANY);
        // 指定序列化輸入的類型，類必須是非final修飾的，final修飾的類，比如String,Integer等會跑出異常
        om.enableDefaultTyping(ObjectMapper.DefaultTyping.NON_FINAL);
        jacksonSeial.setObjectMapper(om);
 
        // 值采用json序列化
        template.setValueSerializer(jacksonSeial);
        //使用StringRedisSerializer來序列化和反序列化redis的key值
        template.setKeySerializer(new StringRedisSerializer());
 
        // 設置hash key 和value序列化模式
        template.setHashKeySerializer(new StringRedisSerializer());
        template.setHashValueSerializer(jacksonSeial);
        template.afterPropertiesSet();
 
        return template;
    }
 
    /**
     * 對hash類型的數據操作
     *
     * @param redisTemplate
     * @return
     */
    @Bean
    public HashOperations<String, String, Object> hashOperations(RedisTemplate<String, Object> redisTemplate) {
        return redisTemplate.opsForHash();
    }
 
    /**
     * 對redis字符串類型數據操作
     *
     * @param redisTemplate
     * @return
     */
    @Bean
    public ValueOperations<String, Object> valueOperations(RedisTemplate<String, Object> redisTemplate) {
        return redisTemplate.opsForValue();
    }
 
    /**
     * 對鏈表類型的數據操作
     *
     * @param redisTemplate
     * @return
     */
    @Bean
    public ListOperations<String, Object> listOperations(RedisTemplate<String, Object> redisTemplate) {
        return redisTemplate.opsForList();
    }
 
    /**
     * 對無序集合類型的數據操作
     *
     * @param redisTemplate
     * @return
     */
    @Bean
    public SetOperations<String, Object> setOperations(RedisTemplate<String, Object> redisTemplate) {
        return redisTemplate.opsForSet();
    }
 
    /**
     * 對有序集合類型的數據操作
     *
     * @param redisTemplate
     * @return
     */
    @Bean
    public ZSetOperations<String, Object> zSetOperations(RedisTemplate<String, Object> redisTemplate) {
        return redisTemplate.opsForZSet();
    }
}

接著是Mapper持久層Dao，這里主要用注解寫比較方便，也可以使用mybatis的xml配置文件寫sql語句

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")
    List<User> queryAll();
 
    @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層，這里主要是使用redis模板來寫

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 List<User> queryAll() {
        return userDao.queryAll();
    }
 
    /**
     * 獲取用戶策略：先從緩存中獲取用戶，沒有則取數據表中 數據，再將數據寫入緩存
     */
    public User findUserById(int id) {
        String key = "user_" + id;
 
        ValueOperations<String, User> operations = redisTemplate.opsForValue();
 
        //判斷redis中是否有鍵為key的緩存
        boolean hasKey = redisTemplate.hasKey(key);
 
        if (hasKey) {
            User user = operations.get(key);
            System.out.println("從緩存中獲得數據："+user.getUserName());
            System.out.println("------------------------------------");
            return user;
        } else {
            User user = userDao.findUserById(id);
            System.out.println("查詢數據庫獲得數據："+user.getUserName());
            System.out.println("------------------------------------");
 
            // 寫入緩存
            operations.set(key, user, 5, TimeUnit.HOURS);
            return user;
        }
    }
 
    /**
     * 更新用戶策略：先更新數據表，成功之后，刪除原來的緩存，再更新緩存
     */
    public int updateUser(User user) {
        ValueOperations<String, User> 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("刪除緩存中的key-----------> " + key);
            }
            // 再將更新后的數據加入緩存
            User userNew = userDao.findUserById(user.getUid());
            if (userNew != null) {
                operations.set(key, userNew, 3, TimeUnit.HOURS);
            }
        }
        return result;
    }
 
    /**
     * 刪除用戶策略：刪除數據表中數據，然后刪除緩存
     */
    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("刪除了緩存中的key:" + key);
            }
        }
        return result;
    }
 
}　

這里主要是使用RedisTemplate來對遠程redis操作，每次訪問controller暴露的接口，首先判斷redis緩存中是否存在該數據，若不存在就從數據庫中讀取數據，然后保存到redis緩存中，當下次訪問的時候，就直接從緩存中取出來。

這樣就不用每次都執行sql語句，能夠提高訪問速度。 但是在保存數據到緩存中，通過設置鍵和值和超時刪除，注意設置超時刪除緩存時間不要太長，否則會給服務器帶來壓力。

執行spring boot的啟動類，訪問http://localhost:8081/findUserById?id=1

再次訪問http://localhost:8081/findUserById?id=1就是從緩存中獲取保存的數據

以上就是springboot redis緩存配置的詳細內容，代碼示例簡單明了，如果在日常工作遇到此問題。通過這篇文章，希望你能有所收獲，更多詳情敬請關注億速云行業資訊頻道！