1、添加依赖
ruoyi-common\pom.xml模块添加整合依赖
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<!-- springboot整合redis -->
< dependency >
< groupId >org.springframework.boot</ groupId >
< artifactId >spring-boot-starter-data-redis</ artifactId >
</ dependency >
<!-- 阿里JSON解析器 -->
< dependency >
< groupId >com.alibaba</ groupId >
< artifactId >fastjson</ artifactId >
</ dependency >
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2、修改配置
ruoyi-admin目录下的application-druid.yml,添加redis配置
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# 数据源配置
spring:
# redis配置
redis:
database: 0
host: 127.0 . 0.1
port: 6379
password:
timeout: 6000ms # 连接超时时长(毫秒)
lettuce:
pool:
max-active: 1000 # 连接池最大连接数(使用负值表示没有限制)
max-wait: -1ms # 连接池最大阻塞等待时间(使用负值表示没有限制)
max-idle: 10 # 连接池中的最大空闲连接
min-idle: 5 # 连接池中的最小空闲连接
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3、增加配置
ruoyi-framework目录下的config文件里,增加RedisConfig.java和FastJson2JsonRedisSerializer.java类
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import com.fasterxml.jackson.annotation.JsonAutoDetect;
import com.fasterxml.jackson.annotation.JsonTypeInfo;
import com.fasterxml.jackson.annotation.PropertyAccessor;
import com.fasterxml.jackson.databind.ObjectMapper;
import com.fasterxml.jackson.databind.jsontype.impl.LaissezFaireSubTypeValidator;
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.connection.RedisConnectionFactory;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.data.redis.serializer.StringRedisSerializer;
/**
* redis配置
*
* @author YangPC
*/
@Configuration
@EnableCaching
public class RedisConfig extends CachingConfigurerSupport {
@Bean
@SuppressWarnings (value = { "unchecked" , "rawtypes" })
public RedisTemplate<Object, Object> redisTemplate(RedisConnectionFactory connectionFactory) {
RedisTemplate<Object, Object> template = new RedisTemplate<>();
template.setConnectionFactory(connectionFactory);
FastJson2JsonRedisSerializer serializer = new FastJson2JsonRedisSerializer(Object. class );
ObjectMapper mapper = new ObjectMapper();
mapper.setVisibility(PropertyAccessor.ALL, JsonAutoDetect.Visibility.ANY);
mapper.activateDefaultTyping(LaissezFaireSubTypeValidator.instance, ObjectMapper.DefaultTyping.NON_FINAL, JsonTypeInfo.As.PROPERTY);
serializer.setObjectMapper(mapper);
// 使用StringRedisSerializer来序列化和反序列化redis的key值
template.setKeySerializer( new StringRedisSerializer());
template.setValueSerializer(serializer);
// Hash的key也采用StringRedisSerializer的序列化方式
template.setHashKeySerializer( new StringRedisSerializer());
template.setHashValueSerializer(serializer);
template.afterPropertiesSet();
return template;
}
}
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import com.alibaba.fastjson.JSON;
import com.alibaba.fastjson.parser.ParserConfig;
import com.alibaba.fastjson.serializer.SerializerFeature;
import com.fasterxml.jackson.databind.JavaType;
import com.fasterxml.jackson.databind.ObjectMapper;
import com.fasterxml.jackson.databind.type.TypeFactory;
import org.springframework.data.redis.serializer.RedisSerializer;
import org.springframework.data.redis.serializer.SerializationException;
import org.springframework.util.Assert;
import java.nio.charset.Charset;
/**
* Redis使用FastJson序列化
*
* @author YangPC
*/
public class FastJson2JsonRedisSerializer<T> implements RedisSerializer<T>
{
@SuppressWarnings ( "unused" )
private ObjectMapper objectMapper = new ObjectMapper();
public static final Charset DEFAULT_CHARSET = Charset.forName( "UTF-8" );
private Class<T> clazz;
static
{
ParserConfig.getGlobalInstance().setAutoTypeSupport( true );
}
public FastJson2JsonRedisSerializer(Class<T> clazz)
{
super ();
this .clazz = clazz;
}
@Override
public byte [] serialize(T t) throws SerializationException
{
if (t == null )
{
return new byte [ 0 ];
}
return JSON.toJSONString(t, SerializerFeature.WriteClassName).getBytes(DEFAULT_CHARSET);
}
@Override
public T deserialize( byte [] bytes) throws SerializationException
{
if (bytes == null || bytes.length <= 0 )
{
return null ;
}
String str = new String(bytes, DEFAULT_CHARSET);
return JSON.parseObject(str, clazz);
}
public void setObjectMapper(ObjectMapper objectMapper)
{
Assert.notNull(objectMapper, "'objectMapper' must not be null" );
this .objectMapper = objectMapper;
}
protected JavaType getJavaType(Class<?> clazz)
{
return TypeFactory.defaultInstance().constructType(clazz);
}
}
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4、增加工具类
ruoyi-common模块下utils里面新增RedisCache.java类,有利于提高redis操作效率。
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import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.data.redis.core.BoundSetOperations;
import org.springframework.data.redis.core.HashOperations;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.data.redis.core.ValueOperations;
import org.springframework.stereotype.Component;
import java.util.*;
import java.util.concurrent.TimeUnit;
/**
* spring redis 工具类
*
* @author YangPC
**/
@SuppressWarnings (value = { "unchecked" , "rawtypes" })
@Component
public class RedisCache {
@Autowired
public RedisTemplate redisTemplate;
/**
* 缓存基本的对象,Integer、String、实体类等
*
* @param key 缓存的键值
* @param value 缓存的值
*/
public <T> void setCacheObject( final String key, final T value) {
redisTemplate.opsForValue().set(key, value);
}
/**
* 缓存基本的对象,Integer、String、实体类等
*
* @param key 缓存的键值
* @param value 缓存的值
* @param timeout 时间
* @param timeUnit 时间颗粒度
*/
public <T> void setCacheObject( final String key, final T value, final Integer timeout, final TimeUnit timeUnit) {
redisTemplate.opsForValue().set(key, value, timeout, timeUnit);
}
/**
* 设置有效时间
*
* @param key Redis键
* @param timeout 超时时间
* @return true=设置成功;false=设置失败
*/
public boolean expire( final String key, final long timeout) {
return expire(key, timeout, TimeUnit.SECONDS);
}
/**
* 设置有效时间
*
* @param key Redis键
* @param timeout 超时时间
* @param unit 时间单位
* @return true=设置成功;false=设置失败
*/
public boolean expire( final String key, final long timeout, final TimeUnit unit) {
return redisTemplate.expire(key, timeout, unit);
}
/**
* 获得缓存的基本对象。
*
* @param key 缓存键值
* @return 缓存键值对应的数据
*/
public <T> T getCacheObject( final String key) {
ValueOperations<String, T> operation = redisTemplate.opsForValue();
return operation.get(key);
}
/**
* 删除单个对象
*
* @param key
*/
public boolean deleteObject( final String key) {
return redisTemplate.delete(key);
}
/**
* 删除集合对象
*
* @param collection 多个对象
* @return
*/
public long deleteObject( final Collection collection) {
return redisTemplate.delete(collection);
}
/**
* 缓存List数据
*
* @param key 缓存的键值
* @param dataList 待缓存的List数据
* @return 缓存的对象
*/
public <T> long setCacheList( final String key, final List<T> dataList) {
Long count = redisTemplate.opsForList().rightPushAll(key, dataList);
return count == null ? 0 : count;
}
/**
* 获得缓存的list对象
*
* @param key 缓存的键值
* @return 缓存键值对应的数据
*/
public <T> List<T> getCacheList( final String key) {
return redisTemplate.opsForList().range(key, 0 , - 1 );
}
/**
* 缓存Set
*
* @param key 缓存键值
* @param dataSet 缓存的数据
* @return 缓存数据的对象
*/
public <T> BoundSetOperations<String, T> setCacheSet( final String key, final Set<T> dataSet) {
BoundSetOperations<String, T> setOperation = redisTemplate.boundSetOps(key);
Iterator<T> it = dataSet.iterator();
while (it.hasNext()) {
setOperation.add(it.next());
}
return setOperation;
}
/**
* 获得缓存的set
*
* @param key
* @return
*/
public <T> Set<T> getCacheSet( final String key) {
return redisTemplate.opsForSet().members(key);
}
/**
* 缓存Map
*
* @param key
* @param dataMap
*/
public <T> void setCacheMap( final String key, final Map<String, T> dataMap) {
if (dataMap != null ) {
redisTemplate.opsForHash().putAll(key, dataMap);
}
}
/**
* 获得缓存的Map
*
* @param key
* @return
*/
public <T> Map<String, T> getCacheMap( final String key) {
return redisTemplate.opsForHash().entries(key);
}
/**
* 往Hash中存入数据
*
* @param key Redis键
* @param hKey Hash键
* @param value 值
*/
public <T> void setCacheMapValue( final String key, final String hKey, final T value) {
redisTemplate.opsForHash().put(key, hKey, value);
}
/**
* 获取Hash中的数据
*
* @param key Redis键
* @param hKey Hash键
* @return Hash中的对象
*/
public <T> T getCacheMapValue( final String key, final String hKey) {
HashOperations<String, String, T> opsForHash = redisTemplate.opsForHash();
return opsForHash.get(key, hKey);
}
/**
* 获取多个Hash中的数据
*
* @param key Redis键
* @param hKeys Hash键集合
* @return Hash对象集合
*/
public <T> List<T> getMultiCacheMapValue( final String key, final Collection<Object> hKeys) {
return redisTemplate.opsForHash().multiGet(key, hKeys);
}
/**
* 获得缓存的基本对象列表
*
* @param pattern 字符串前缀
* @return 对象列表
*/
public Collection<String> keys( final String pattern) {
return redisTemplate.keys(pattern);
}
/**
* 判断Key是否存在
*
* @param key
* @return
*/
public boolean hasKey(String key) {
return redisTemplate.hasKey(key);
}
/**
* 清除缓存(自定义)
*/
public void cleanCache() {
List<String> keys = new ArrayList<>();
redisTemplate.delete(keys);
}
}
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总结
本篇文章就到这里了,希望能给你带来帮助,也希望您能够多多关注服务器之家的更多内容!
原文链接:https://blog.csdn.net/qq_19309473/article/details/119923279