1、添加依赖
ruoyi-common\pom.xml模块添加整合依赖
1 2 3 4 5 6 7 8 9 10 | <!-- 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
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | # 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
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 | 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; } } |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 | 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。
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 | 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
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