需求: 实现搜索历史最大保存N条,保存N天
一.RedisTemplate
String key= RedisKeyPrefix.识虫历史记录.getKey() + SecurityUtils.getLoginUser().getUser().getUserId(); redisTemplate.expire(key,30, TimeUnit.DAYS);
redisTemplate.opsForList().leftPush(key,JSONUtil.toJsonStr(item));
Long size = redisTemplate.opsForList().size(key);
if (size>10){
redisTemplate.opsForList().rightPop(key);
}
@GetMapping(value = "/serarchHistory") @ApiOperation("识虫历史记录") public AjaxResult serarchHistory() { String key= RedisKeyPrefix.识虫历史记录.getKey() + SecurityUtils.getLoginUser().getUser().getUserId(); Long size = redisTemplate.opsForList().size(key); List<String> range = redisTemplate.opsForList().range(key, 0,size-1); return AjaxResult.success(range); }
二.redisson
package com.ruoyi.common.utils; import com.google.common.collect.Lists; import com.ruoyi.common.utils.spring.SpringUtils; import lombok.AccessLevel; import lombok.NoArgsConstructor; import org.redisson.api.*; import java.util.Collection; import java.util.List; import java.util.Map; import java.util.Set; import java.util.concurrent.TimeUnit; import java.util.function.Consumer; /** * redis 工具类 * * @author Lion Li * @version 3.1.0 新增 */ @NoArgsConstructor(access = AccessLevel.PUBLIC) @SuppressWarnings(value = {"unchecked", "rawtypes"}) public class RedisUtils { public static RedissonClient client = SpringUtils.getBean(RedissonClient.class); /** * 限流 * * @param key 限流key * @param rateType 限流类型 * @param rate 速率 * @param rateInterval 速率间隔 * @return -1 表示失败 */ public static long rateLimiter(String key, RateType rateType, int rate, int rateInterval) { RRateLimiter rateLimiter = client.getRateLimiter(key); rateLimiter.trySetRate(rateType, rate, rateInterval, RateIntervalUnit.SECONDS); if (rateLimiter.tryAcquire()) { return rateLimiter.availablePermits(); } else { return -1L; } } /** * 获取实例id */ public static String getClientId() { return client.getId(); } /** * 发布通道消息 * * @param channelKey 通道key * @param msg 发送数据 * @param consumer 自定义处理 */ public static <T> void publish(String channelKey, T msg, Consumer<T> consumer) { RTopic topic = client.getTopic(channelKey); topic.publish(msg); consumer.accept(msg); } public static <T> void publish(String channelKey, T msg) { RTopic topic = client.getTopic(channelKey); topic.publish(msg); } /** * 订阅通道接收消息 * * @param channelKey 通道key * @param clazz 消息类型 * @param consumer 自定义处理 */ public static <T> void subscribe(String channelKey, Class<T> clazz, Consumer<T> consumer) { RTopic topic = client.getTopic(channelKey); topic.addListener(clazz, (channel, msg) -> consumer.accept(msg)); } /** * 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 static <T> void setCacheObject(final String key, final T value) { setCacheObject(key, value, false); } /** * 缓存基本的对象，保留当前对象 TTL 有效期 * * @param key 缓存的键值 * @param value 缓存的值 * @param isSaveTtl 是否保留TTL有效期(例如: set之前ttl剩余90 set之后还是为90) * @since Redis 6.X 以上使用 setAndKeepTTL 兼容 5.X 方案 */ public static <T> void setCacheObject(final String key, final T value, final boolean isSaveTtl) { RBucket<Object> bucket = client.getBucket(key); if (isSaveTtl) { try { bucket.setAndKeepTTL(value); } catch (Exception e) { long timeToLive = bucket.remainTimeToLive(); bucket.set(value); bucket.expire(timeToLive, TimeUnit.MILLISECONDS); } } else { bucket.set(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 static <T> void setCacheObject(final String key, final T value, final long timeout, final TimeUnit timeUnit) { RBucket<T> result = client.getBucket(key); result.set(value); result.expire(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 static 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 static boolean expire(final String key, final long timeout, final TimeUnit unit) { RBucket rBucket = client.getBucket(key); return rBucket.expire(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 static <T> T getCacheObject(final String key) { RBucket<T> rBucket = client.getBucket(key); return rBucket.get(); } /** * 获得key剩余存活时间 * * @param key 缓存键值 * @return 剩余存活时间 */ public static <T> long getTimeToLive(final String key) { RBucket<T> rBucket = client.getBucket(key); return rBucket.remainTimeToLive(); } /** * 删除单个对象 * * @param key */ public static boolean deleteObject(final String key) { return client.getBucket(key).delete(); } /* */ /** * 删除集合对象 * * @param collection 多个对象 * @return */ public static void deleteObject(final Collection collection) { RBatch batch = client.createBatch(); collection.forEach(t -> { batch.getBucket(t.toString()).deleteAsync(); }); batch.execute(); } /** * 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 static <T> boolean setCacheList(final String key, final List<T> dataList) { RList<T> rList = client.getList(key); return rList.addAll(dataList); } /** * 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 static <T> List<T> getCacheList(final String key) { RList<T> rList = client.getList(key); return rList.readAll(); } /** * 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 static <T> boolean setCacheSet(final String key, final Set<T> dataSet) { RSet<T> rSet = client.getSet(key); return rSet.addAll(dataSet); } /** * 获得缓存的set * * @param key * @return */ public static <T> Set<T> getCacheSet(final String key) { RSet<T> rSet = client.getSet(key); return rSet.readAll(); } /** * 缓存Map * * @param key * @param dataMap */ public static <T> void setCacheMap(final String key, final Map<String, T> dataMap) { if (dataMap != null) { RMap<String, T> rMap = client.getMap(key); rMap.putAll(dataMap); } } /** * 获得缓存的Map * * @param key * @return */ public static <T> Map<String, T> getCacheMap(final String key) { RMap<String, T> rMap = client.getMap(key); return rMap.getAll(rMap.keySet()); } /** * 往Hash中存入数据 * * @param key Redis键 * @param hKey Hash键 * @param value 值 */ public static <T> void setCacheMapValue(final String key, final String hKey, final T value) { RMap<String, T> rMap = client.getMap(key); rMap.put(hKey, value); } /** * 获取Hash中的数据 * * @param key Redis键 * @param hKey Hash键 * @return Hash中的对象 */ public static <T> T getCacheMapValue(final String key, final String hKey) { RMap<String, T> rMap = client.getMap(key); return rMap.get(hKey); } /** * 删除Hash中的数据 * * @param key Redis键 * @param hKey Hash键 * @return Hash中的对象 */ public static <T> T delCacheMapValue(final String key, final String hKey) { RMap<String, T> rMap = client.getMap(key); return rMap.remove(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 static <K, V> Map<K, V> getMultiCacheMapValue(final String key, final Set<K> hKeys) { RMap<K, V> rMap = client.getMap(key); return rMap.getAll(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 static Collection<String> keys(final String pattern) { Iterable<String> iterable = client.getKeys().getKeysByPattern(pattern); return Lists.newArrayList(iterable); } }
if (StrUtil.isNotEmpty(bo.getKeyWord())){ String redisKey= RedisKeyType.商品搜索历史.getCode()+SecurityUtils.getUserId(); // 存放关键词 List<String> keyWords = RedisUtils.getCacheList(redisKey); if (keyWords!=null&&keyWords.size()>7){ keyWords.remove(0); keyWords.add(bo.getKeyWord()); }else { if (keyWords!=null){ keyWords.add(bo.getKeyWord()); }else { keyWords=new ArrayList<>(); keyWords.add(bo.getKeyWord()); } RedisUtils.setCacheList(redisKey,keyWords); } RedisUtils.expire(redisKey,7, TimeUnit.DAYS); }
@ApiOperation("获取商品搜索历史")
@GetMapping("/goodsHistory")
public AjaxResult< List<String> > goodsHistory( ) {
String redisKey= RedisKeyType.商品搜索历史.getCode()+ SecurityUtils.getUserId();
// 存放关键词
List<String> keyWords = RedisUtils.getCacheList(redisKey);
return AjaxResult.success(keyWords);
}
