什么叫缓存穿透?
模拟一个场景:
前端用户发送请求获取数据,后端首先会在缓存Redis中查询,如果能查到数据,则直接返回.如果缓存中查不到数据,则要去数据库查询,如果数据库有,将数据保存到Redis缓存中并且返回用户数据.如果数据库没有则返回null;
这个缓存穿透的问题就是这个返回的null上面,如果客户端恶意频繁的发起Redis不存在的Key,且数据库中也不存在的数据,返回永远是null.当洪流式的请求过来,给数据库造成极大压力,甚至压垮数据库.它永远越过Redis缓存而直接访问数据库,这个过程就是缓存穿透.
其实是个设计上的缺陷.
缓存穿透解决方案
业界比较成熟的一种解决方案:当越过缓存,且数据库没有该数据返回客户端null并且存到Redis,数据是null,给这个Key设置过期时间.这种方案一定程度上减少数据库频繁查询的压力.
实战过程
CREATE TABLE `item` (
`id` int(11) NOT NULL AUTO_INCREMENT,
`code` varchar(255) DEFAULT NULL COMMENT '商品编号',
`name` varchar(255) CHARACTER SET utf8mb4 DEFAULT NULL COMMENT '商品名称',
`create_time` datetime DEFAULT NULL,
PRIMARY KEY (`id`)
) ENGINE=InnoDB AUTO_INCREMENT=2 DEFAULT CHARSET=utf8 COMMENT='商品信息表';
INSERT INTO `item` VALUES ('1', 'book_10010', 'Redis缓存穿透实战', '2019-03-17 17:21:16');
项目整体结构
依赖
<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 https://maven.apache.org/xsd/maven-4.0.0.xsd"><modelVersion>4.0.0</modelVersion><parent><groupId>org.springframework.boot</groupId><artifactId>spring-boot-starter-parent</artifactId><version>2.7.2</version><relativePath/> <!-- lookup parent from repository --></parent><groupId>com.example</groupId><artifactId>redis1</artifactId><version>0.0.1-SNAPSHOT</version><name>redis1</name><description>Demo project for Spring Boot</description><properties><java.version>8</java.version></properties><dependencies><dependency><groupId>org.springframework.boot</groupId><artifactId>spring-boot-starter-data-redis</artifactId></dependency><dependency><groupId>org.springframework.boot</groupId><artifactId>spring-boot-starter-web</artifactId></dependency><dependency><groupId>org.mybatis.spring.boot</groupId><artifactId>mybatis-spring-boot-starter</artifactId><version>2.3.0</version></dependency><dependency><groupId>org.springframework.boot</groupId><artifactId>spring-boot-devtools</artifactId><scope>runtime</scope><optional>true</optional></dependency><dependency><groupId>mysql</groupId><artifactId>mysql-connector-java</artifactId><scope>runtime</scope></dependency><dependency><groupId>org.projectlombok</groupId><artifactId>lombok</artifactId><optional>true</optional></dependency><dependency><groupId>org.springframework.boot</groupId><artifactId>spring-boot-starter-test</artifactId><scope>test</scope></dependency><dependency><groupId>org.mybatis.spring.boot</groupId><artifactId>mybatis-spring-boot-starter-test</artifactId><version>3.0.3</version><scope>test</scope></dependency></dependencies><build><plugins><plugin><groupId>org.springframework.boot</groupId><artifactId>spring-boot-maven-plugin</artifactId><configuration><excludes><exclude><groupId>org.projectlombok</groupId><artifactId>lombok</artifactId></exclude></excludes></configuration></plugin></plugins></build></project>
启动类
@SpringBootApplication
@MapperScan({"com.example.redis1.mapper"})
public class Redis1Application {public static void main(String[] args) {SpringApplication.run(Redis1Application.class, args);}}
application.yml
server:port: 80
spring:application:name: redis-testredis:##redis 单机环境配置##将docker脚本部署的redis服务映射为宿主机ip##生产环境推荐使用阿里云高可用redis服务并设置密码host: 127.0.0.1port: 6379password:database: 0ssl: false##redis 集群环境配置#cluster:# nodes: 127.0.0.1:7001,127.0.0.1:7002,127.0.0.1:7003# commandTimeout: 5000datasource:driver-class-name: com.mysql.cj.jdbc.Driverurl: jdbc:mysql://1111111:3306/redis-test?useSSL=false&useUnicode=true&characterEncoding=UTF-8&autoReconnect=true&serverTimezone=GMT%2B8&useCursorFetch=trueusername: xxxxpassword: xxxxxxxx
mybatis:mapper-locations: classpath:mappers/*Mapper.xml # 指定mapper文件位置type-aliases-package: com.example.redis1.pojoconfiguration:map-underscore-to-camel-case: true
logging:level:com.example.redis1.mapper: debug
数据库映射xml
<?xml version="1.0" encoding="UTF-8" ?>
<!DOCTYPE mapper PUBLIC "-//mybatis.org//DTD Mapper 3.0//EN" "http://mybatis.org/dtd/mybatis-3-mapper.dtd" >
<mapper namespace="com.example.redis1.mapper.ItemMapper" ><resultMap id="BaseResultMap" type="com.example.redis1.pojo.Item" ><id column="id" property="id" jdbcType="INTEGER" /><result column="code" property="code" jdbcType="VARCHAR" /><result column="name" property="name" jdbcType="VARCHAR" /><result column="create_time" property="createTime" jdbcType="TIMESTAMP" /></resultMap><sql id="Base_Column_List" >id, code, name, create_time</sql><select id="selectByPrimaryKey" resultMap="BaseResultMap" parameterType="java.lang.Integer" >select<include refid="Base_Column_List" />from itemwhere id = #{id,jdbcType=INTEGER}</select><delete id="deleteByPrimaryKey" parameterType="java.lang.Integer" >delete from itemwhere id = #{id,jdbcType=INTEGER}</delete><insert id="insert" parameterType="item" >insert into item (id, code, name,create_time)values (#{id,jdbcType=INTEGER}, #{code,jdbcType=VARCHAR}, #{name,jdbcType=VARCHAR},#{createTime,jdbcType=TIMESTAMP})</insert><insert id="insertSelective" parameterType="item" >insert into item<trim prefix="(" suffix=")" suffixOverrides="," ><if test="id != null" >id,</if><if test="code != null" >code,</if><if test="name != null" >name,</if><if test="createTime != null" >create_time,</if></trim><trim prefix="values (" suffix=")" suffixOverrides="," ><if test="id != null" >#{id,jdbcType=INTEGER},</if><if test="code != null" >#{code,jdbcType=VARCHAR},</if><if test="name != null" >#{name,jdbcType=VARCHAR},</if><if test="createTime != null" >#{createTime,jdbcType=TIMESTAMP},</if></trim></insert><update id="updateByPrimaryKeySelective" parameterType="item" >update item<set ><if test="code != null" >code = #{code,jdbcType=VARCHAR},</if><if test="name != null" >name = #{name,jdbcType=VARCHAR},</if><if test="createTime != null" >create_time = #{createTime,jdbcType=TIMESTAMP},</if></set>where id = #{id,jdbcType=INTEGER}</update><update id="updateByPrimaryKey" parameterType="item" >update itemset code = #{code,jdbcType=VARCHAR},name = #{name,jdbcType=VARCHAR},create_time = #{createTime,jdbcType=TIMESTAMP}where id = #{id,jdbcType=INTEGER}</update><!--根据商品编码查询--><select id="selectByCode" resultType="item">select<include refid="Base_Column_List" />from itemwhere code = #{code}</select></mapper>
pojo
package com.example.redis1.pojo;import com.fasterxml.jackson.annotation.JsonFormat;
import lombok.Data;import java.util.Date;@Data
public class Item {private Integer id;private String code;private String name;@JsonFormat(pattern = "yyyy-MM-dd HH:mm:ss",timezone = "GMT+8")private Date createTime;}
mapper
package com.example.redis1.mapper;import com.example.redis1.pojo.Item;
import org.apache.ibatis.annotations.Param;public interface ItemMapper {int deleteByPrimaryKey(Integer id);int insert(Item record);int insertSelective(Item record);Item selectByPrimaryKey(Integer id);int updateByPrimaryKeySelective(Item record);int updateByPrimaryKey(Item record);Item selectByCode(@Param("code") String code);
}
service
package com.example.redis1.service;import com.example.redis1.mapper.ItemMapper;
import com.example.redis1.pojo.Item;
import com.fasterxml.jackson.databind.ObjectMapper;import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
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.concurrent.TimeUnit;/*** 缓存穿透service* Created by Administrator on 2019/3/17.*/
@Service
public class CachePassService {private static final Logger log= LoggerFactory.getLogger(CachePassService.class);@Autowiredprivate ItemMapper itemMapper;@Autowiredprivate RedisTemplate redisTemplate;@Autowiredprivate ObjectMapper objectMapper;private static final String keyPrefix="item:";/*** 获取商品详情-如果缓存有,则从缓存中获取;如果没有,则从数据库查询,并将查询结果塞入缓存中* @param itemCode* @return* @throws Exception*/public Item getItemInfo(String itemCode) throws Exception{Item item=null;final String key=keyPrefix+itemCode;ValueOperations valueOperations=redisTemplate.opsForValue();if (redisTemplate.hasKey(key)){log.info("---获取商品详情-缓存中存在该商品---商品编号为:{} ",itemCode);//从缓存中查询该商品详情Object res=valueOperations.get(key);if (res!=null&&!(res.equals(""))){item=objectMapper.readValue(res.toString(),Item.class);}}else{log.info("---获取商品详情-缓存中不存在该商品-从数据库中查询---商品编号为:{} ",itemCode);//从数据库中获取该商品详情item=itemMapper.selectByCode(itemCode);if (item!=null){valueOperations.set(key,objectMapper.writeValueAsString(item));}else{//过期失效时间TTL设置为30分钟-当然实际情况要根据实际业务决定valueOperations.set(key,"",30L, TimeUnit.MINUTES);}}return item;}
}
controller
package com.example.redis1.controller;import com.example.redis1.service.CachePassService;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RequestMethod;
import org.springframework.web.bind.annotation.RequestParam;
import org.springframework.web.bind.annotation.RestController;
import java.util.HashMap;
import java.util.Map;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;/*** 缓存穿透实战* @Author:debug (SteadyJack)* @Date: 2019/3/17 18:33**/
@RestController
public class CachePassController {private static final Logger log= LoggerFactory.getLogger(CachePassController.class);private static final String prefix="cache/pass";@Autowiredprivate CachePassService cachePassService;/*** 获取热销商品信息* @param itemCode* @return*/@RequestMapping(value = prefix+"/item/info",method = RequestMethod.GET)public Map<String,Object> getItem(@RequestParam String itemCode){Map<String,Object> resMap=new HashMap<>();resMap.put("code",0);resMap.put("msg","成功");try {resMap.put("data",cachePassService.getItemInfo(itemCode));}catch (Exception e){resMap.put("code",-1);resMap.put("msg","失败"+e.getMessage());}return resMap;}
}
第一次访问
localhost/cache/pass/item/info?itemCode=book_10010
查看日志输出
用个数据库不存在的
localhost/cache/pass/item/info?itemCode=book_10012
后端的处理是将不存在的key存到redis并指定过期时间
其他典型问题介绍
缓存雪崩:指的的某个时间点,缓存中的Key集体发生过期失效,导致大量查询的请求落到数据库上,导致数据库负载过高,压力暴增的现象
解决方案:设置错开不同的过期时间
缓存击穿:指缓存中某个频繁被访问的Key(热点Key),突然过期时间到了失效了,持续的高并发访问瞬间就像击破缓存一样瞬间到达数据库。
解决办法:设置热点Key永不过期