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 > |
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 |
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); } } |
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); } } |
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的更多内容！
原文链接：https://blog.csdn.net/qq_19309473/article/details/119923279
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