项目场景
Redis的keys *
命令在生产环境是慎用的,特别是一些并发量很大的项目,原因是Redis是单线程的,keys *
会引发Redis锁,占用reids CPU,如果key数量很大而且并发是比较大的情况,效率是很慢的,很有可能导致服务雪崩,在Redis官方的文档是这样解释的,官方的推荐是使用scan
命令或者集合
解决方案
搭建一个工程来实践一下,项目环境:
-
JDK 1.8
-
SpringBoot 2.2.1
-
Maven 3.2+
-
Mysql 8.0.26
-
spring-boot-starter-data-redis 2.2.1
-
jedis3.1.0
-
开发工具
-
IntelliJ IDEA
-
smartGit
-
新建一个SpringBoot项目
选择需要的依赖
选择Maven项目和jdk对应的版本
<?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>2.2.1.RELEASE</version>
<relativePath/> <!-- lookup parent from repository -->
</parent>
<groupId>com.example</groupId>
<artifactId>springboot-jedis</artifactId>
<version>0.0.1-SNAPSHOT</version>
<name>springboot-jedis</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>
<exclusions>
<exclusion>
<groupId>io.lettuce</groupId>
<artifactId>lettuce-core</artifactId>
</exclusion>
</exclusions>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-web</artifactId>
</dependency>
<dependency>
<groupId>redis.clients</groupId>
<artifactId>jedis</artifactId>
</dependency>
<dependency>
<groupId>cn.hutool</groupId>
<artifactId>hutool-all</artifactId>
<version>5.7.11</version>
</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>
</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>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-compiler-plugin</artifactId>
<configuration>
<source>8</source>
<target>8</target>
</configuration>
</plugin>
</plugins>
</build>
</project>
package com.example.jedis.configuration;
import com.example.jedis.common.JedisTemplate;
import lombok.extern.slf4j.Slf4j;
import org.apache.commons.pool2.impl.GenericObjectPool;
import org.springframework.boot.autoconfigure.condition.ConditionalOnClass;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.data.redis.connection.RedisConnectionFactory;
import org.springframework.data.redis.connection.jedis.JedisConnection;
import org.springframework.data.redis.connection.jedis.JedisConnectionFactory;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.data.redis.repository.configuration.EnableRedisRepositories;
import org.springframework.data.redis.serializer.GenericJackson2JsonRedisSerializer;
import org.springframework.data.redis.serializer.StringRedisSerializer;
import redis.clients.jedis.Jedis;
import redis.clients.jedis.JedisPool;
import redis.clients.jedis.JedisPoolConfig;
@Configuration
@ConditionalOnClass({GenericObjectPool.class, JedisConnection.class, Jedis.class})
@EnableRedisRepositories(basePackages = "com.example.jedis.repository")
@Slf4j
public class RedisConfiguration {
@Bean
public JedisPoolConfig jedisPoolConfig() {
return new JedisPoolConfig();
}
@Bean
public JedisPool jedisPool() {
return new JedisPool(jedisPoolConfig());
}
@Bean
public RedisConnectionFactory jedisConnectionFactory() {
return new JedisConnectionFactory();
}
@Bean
public RedisTemplate<String, Object> redisTemplate() {
RedisTemplate<String, Object> template = new RedisTemplate<String, Object>();
template.setConnectionFactory(jedisConnectionFactory());
template.setKeySerializer(new StringRedisSerializer());
template.setValueSerializer(new GenericJackson2JsonRedisSerializer());
return template;
}
}
写一个工具类,实现redis scan
和keys *
的逻辑,当然也可以直接使用RedisTemplate
import cn.hutool.core.collection.ConcurrentHashSet;
import lombok.extern.slf4j.Slf4j;
import org.springframework.beans.factory.InitializingBean;
import org.springframework.stereotype.Component;
import redis.clients.jedis.Jedis;
import redis.clients.jedis.JedisPool;
import redis.clients.jedis.ScanParams;
import redis.clients.jedis.ScanResult;
import redis.clients.jedis.exceptions.JedisConnectionException;
import redis.clients.jedis.exceptions.JedisDataException;
import redis.clients.jedis.exceptions.JedisException;
import redis.clients.jedis.params.SetParams;
import javax.annotation.Resource;
import java.util.List;
import java.util.Map;
import java.util.Optional;
import java.util.Set;
import java.util.function.Consumer;
import java.util.function.Function;
@Component
@Slf4j
public class JedisUtil implements InitializingBean {
@Resource
private JedisPool jedisPool;
private Jedis jedis;
public JedisTemplate(JedisPool jedisPool) {
this.jedisPool = jedisPool;
}
public JedisTemplate() {
}
@Override
public void afterPropertiesSet() {
jedis = jedisPool.getResource();
}
public <T> T execute(Function<Jedis, T> action) {
T apply = null;
try {
jedis = jedisPool.getResource();
apply = action.apply(jedis);
} catch (JedisException e) {
handleException(e);
throw e;
} finally {
jedis.close();
}
return apply;
}
public void execute(Consumer<Jedis> action) {
try {
jedis = jedisPool.getResource();
action.accept(jedis);
} catch (JedisException e) {
handleException(e);
throw e;
} finally {
jedis.close();
}
}
public JedisPool getJedisPool() {
return this.jedisPool;
}
public Set<String> keys(final String pattern) {
return execute(e->{
return jedis.keys(pattern);
});
}
public Set<String> scan(String pattern) {
return execute(e->{
return this.doScan(pattern);
});
}
protected Set<String> doScan(String pattern) {
Set<String> resultSet = new ConcurrentHashSet<>();
String cursor = String.valueOf(0);
try {
do {
ScanParams params = new ScanParams();
params.count(300);
params.match(pattern);
ScanResult<String> scanResult = jedis.scan(cursor, params);
cursor = scanResult.getCursor();
resultSet.addAll(scanResult.getResult());
} while (Integer.valueOf(cursor) > 0);
} catch (NumberFormatException e) {
log.error("doScan NumberFormatException:{}", e);
} catch (Exception e) {
log.error("doScan Exception :{}", e);
}
return resultSet;
}
protected void handleException(JedisException e) {
if (e instanceof JedisConnectionException) {
log.error("redis connection exception:{}", e);
} else if (e instanceof JedisDataException) {
log.error("jedis data exception:{}", e);
} else {
log.error("jedis exception:{}", e);
}
}
}
新增测试类
import cn.hutool.core.date.DateUtil;
import cn.hutool.core.date.TimeInterval;
import cn.hutool.core.thread.ExecutorBuilder;
import cn.hutool.core.util.IdUtil;
import com.example.jedis.common.JedisTemplate;
import com.example.jedis.configuration.RedisConfiguration;
import com.example.jedis.model.UserDto;
import com.example.jedis.repository.UserRepository;
import lombok.extern.slf4j.Slf4j;
import org.junit.jupiter.api.Test;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.boot.test.context.SpringBootTest;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.test.annotation.DirtiesContext;
import org.springframework.test.context.ContextConfiguration;
import redis.clients.jedis.Jedis;
import redis.clients.jedis.JedisPool;
import java.util.Set;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.LinkedBlockingQueue;
import java.util.concurrent.atomic.AtomicInteger;
import java.util.stream.IntStream;
@SpringBootTest
//@ContextConfiguration(classes = RedisConfiguration.class)
//@DirtiesContext(classMode = DirtiesContext.ClassMode.BEFORE_CLASS)
@Slf4j
class SpringbootJedisApplicationTests {
@Autowired
JedisUtil jedisUtil;
@Test
void testCrud() {
IntStream.range(0,100000).forEach(e->{
final UserDto userDto = UserDto.builder()
.id(IdUtil.getSnowflake().nextId())
.name("用户1")
.gender(UserDto.Gender.MALE)
.build();
userRepository.save(userDto);
});
}
@Test
void testKeys() {
TimeInterval timeInterval = DateUtil.timer();
Set<String> setData = jedisUitil.keys("user:*");
System.out.println("keys use:"+timeInterval.intervalRestart()+"ms");
Set<String> setDataScan = jedisUitil.scan("user:*");
System.out.println("scan use:"+timeInterval.intervalRestart()+"ms");
}
}
使用了3千多额数据,测试keys *
和scan
其实查询效率差别不大的,scan
命令效率和分多少数量一批次也有关系
搞到一万的数据量
经过测试,scan查询效率并不一定是比keys *
快多少的,跟这个数据量和count
批次有关系,需要自己调试,所以对于线上的业务场景,如果key数量很多的,可以使用集合来替换keys *