什么叫緩存穿透?

模擬一個(gè)場景:

前端用戶發(fā)送請求獲取數(shù)據(jù),后端首先會在緩存Redis中查詢,如果能查到數(shù)據(jù),則直接返回.如果緩存中查不到數(shù)據(jù),則要去數(shù)據(jù)庫查詢,如果數(shù)據(jù)庫有,將數(shù)據(jù)保存到Redis緩存中并且返回用戶數(shù)據(jù).如果數(shù)據(jù)庫沒有則返回null;

這個(gè)緩存穿透的問題就是這個(gè)返回的null上面,如果客戶端惡意頻繁的發(fā)起Redis不存在的Key,且數(shù)據(jù)庫中也不存在的數(shù)據(jù),返回永遠(yuǎn)是null.當(dāng)洪流式的請求過來,給數(shù)據(jù)庫造成極大壓力,甚至壓垮數(shù)據(jù)庫.它永遠(yuǎn)越過Redis緩存而直接訪問數(shù)據(jù)庫,這個(gè)過程就是緩存穿透.

其實(shí)是個(gè)設(shè)計(jì)上的缺陷.

緩存穿透解決方案

業(yè)界比較成熟的一種解決方案:當(dāng)越過緩存,且數(shù)據(jù)庫沒有該數(shù)據(jù)返回客戶端null并且存到Redis,數(shù)據(jù)是為"",看實(shí)際情況并給這個(gè)Key設(shè)置過期時(shí)間.這種方案一定程度上減少數(shù)據(jù)庫頻繁查詢的壓力.

實(shí)戰(zhàn)過程

CREATE TABLE `item` (
? `id` int(11) NOT NULL AUTO_INCREMENT,
? `code` varchar(255) DEFAULT NULL COMMENT '商品編號',
? `name` varchar(255) CHARACTER SET utf8mb4 DEFAULT NULL COMMENT '商品名稱',
? `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緩存穿透實(shí)戰(zhàn)', '2019-03-17 17:21:16');

項(xiàng)目整體結(jié)構(gòu)

依賴

<?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>

啟動類

@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-test
  redis:
    ##redis 單機(jī)環(huán)境配置
    ##將docker腳本部署的redis服務(wù)映射為宿主機(jī)ip
    ##生產(chǎn)環(huán)境推薦使用阿里云高可用redis服務(wù)并設(shè)置密碼
    host: 127.0.0.1
    port: 6379
    password:
    database: 0
    ssl: false
    ##redis 集群環(huán)境配置
    #cluster:
    #  nodes: 127.0.0.1:7001,127.0.0.1:7002,127.0.0.1:7003
    #  commandTimeout: 5000
  datasource:
    driver-class-name: com.mysql.cj.jdbc.Driver
    url: jdbc:mysql://1111111:3306/redis-test?useSSL=false&useUnicode=true&characterEncoding=UTF-8&autoReconnect=true&serverTimezone=GMT%2B8&useCursorFetch=true
    username: xxxx
    password: xxxxxxxx
mybatis:
  mapper-locations: classpath:mappers/*Mapper.xml  # 指定mapper文件位置
  type-aliases-package: com.example.redis1.pojo
  configuration:
    map-underscore-to-camel-case: true
logging:
  level:
    com.example.redis1.mapper: debug

數(shù)據(jù)庫映射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 item
    where id = #{id,jdbcType=INTEGER}
  </select>
  <delete id="deleteByPrimaryKey" parameterType="java.lang.Integer" >
    delete from item
    where 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 item
    set code = #{code,jdbcType=VARCHAR},
      name = #{name,jdbcType=VARCHAR},
      create_time = #{createTime,jdbcType=TIMESTAMP}
    where id = #{id,jdbcType=INTEGER}
  </update>

  <!--根據(jù)商品編碼查詢-->
  <select id="selectByCode" resultType="item">
    select
    <include refid="Base_Column_List" />
    from item
    where 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;

/**
 * 緩存穿透service
 * Created by Administrator on 2019/3/17.
 */
@Service
public class CachePassService {

    private static final Logger log= LoggerFactory.getLogger(CachePassService.class);

    @Autowired
    private ItemMapper itemMapper;

    @Autowired
    private RedisTemplate redisTemplate;

    @Autowired
    private ObjectMapper objectMapper;

    private static final String keyPrefix="item:";

    /**
     * 獲取商品詳情-如果緩存有，則從緩存中獲取；如果沒有，則從數(shù)據(jù)庫查詢，并將查詢結(jié)果塞入緩存中
     * @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("---獲取商品詳情-緩存中存在該商品---商品編號為：{} ",itemCode);

            //從緩存中查詢該商品詳情
            Object res=valueOperations.get(key);
            if (res!=null&&!(res.equals(""))){
                item=objectMapper.readValue(res.toString(),Item.class);
            }
        }else{
            log.info("---獲取商品詳情-緩存中不存在該商品-從數(shù)據(jù)庫中查詢---商品編號為：{} ",itemCode);

            //從數(shù)據(jù)庫中獲取該商品詳情
            item=itemMapper.selectByCode(itemCode);
            if (item!=null){
                valueOperations.set(key,objectMapper.writeValueAsString(item));
            }else{
                //過期失效時(shí)間TTL設(shè)置為30分鐘-當(dāng)然實(shí)際情況要根據(jù)實(shí)際業(yè)務(wù)決定
                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;


/**
 * 緩存穿透實(shí)戰(zhàn)
 * @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";

    @Autowired
    private CachePassService cachePassService;


    /**
     * 獲取熱銷商品信息
     * @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","失敗"+e.getMessage());
        }
        return resMap;
    }
}

第一次訪問

localhost/cache/pass/item/info?itemCode=book_10010

查看日志輸出

用個(gè)數(shù)據(jù)庫不存在的

localhost/cache/pass/item/info?itemCode=book_10012

后端的處理是將不存在的key存到redis并指定過期時(shí)間

其他典型問題介紹

緩存雪崩:指的的某個(gè)時(shí)間點(diǎn),緩存中的Key集體發(fā)生過期失效,導(dǎo)致大量查詢的請求落到數(shù)據(jù)庫上,導(dǎo)致數(shù)據(jù)庫負(fù)載過高,壓力暴增的現(xiàn)象

解決方案:設(shè)置錯(cuò)開不同的過期時(shí)間

緩存擊穿:指緩存中某個(gè)頻繁被訪問的Key(熱點(diǎn)Key),突然過期時(shí)間到了失效了,持續(xù)的高并發(fā)訪問瞬間就像擊破緩存一樣瞬間到達(dá)數(shù)據(jù)庫。

解決辦法:設(shè)置熱點(diǎn)Key永不過期

緩存預(yù)熱:一般指應(yīng)用啟動前,提前加載數(shù)據(jù)到緩存中文章來源地址http://www.zghlxwxcb.cn/news/detail-837572.html

到了這里，關(guān)于Redis緩存預(yù)熱-緩存穿透-緩存雪崩-緩存擊穿的文章就介紹完了。如果您還想了解更多內(nèi)容，請?jiān)谟疑辖撬阉鱐OY模板網(wǎng)以前的文章或繼續(xù)瀏覽下面的相關(guān)文章，希望大家以后多多支持TOY模板網(wǎng)！