这篇文章主要讲解了“java集成redis缓存的过程”,文中的讲解内容简单清晰,易于学习与理解,下面请大家跟着小编的思路慢慢深入,一起来研究和学习“java集成redis缓存的过程”吧!
1、添加依赖
2、修改配置
3、增加配置
4、增加工具类
ruoyi-common\pom.xml模块添加整合依赖
<!-- 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>
ruoyi-admin目录下的application-druid.yml,添加redis配置
# 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
ruoyi-framework目录下的config文件里,增加RedisConfig.java和FastJson2JsonRedisSerializer.java类
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; } }
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); } }
ruoyi-common模块下utils里面新增RedisCache.java类,有利于提高redis操作效率。
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); } }
感谢各位的阅读,以上就是“java集成redis缓存的过程”的内容了,经过本文的学习后,相信大家对java集成redis缓存的过程这一问题有了更深刻的体会,具体使用情况还需要大家实践验证。这里是亿速云,小编将为大家推送更多相关知识点的文章,欢迎关注!
免责声明:本站发布的内容(图片、视频和文字)以原创、转载和分享为主,文章观点不代表本网站立场,如果涉及侵权请联系站长邮箱:is@yisu.com进行举报,并提供相关证据,一经查实,将立刻删除涉嫌侵权内容。