redis keys命令可能导致阻塞问题解决以及单元测试

framework/src/main/java/cn/lili/cache/Cache.java

@@ -153,7 +153,15 @@ public interface Cache<T> {
      * @param pattern 模糊key
      * @return 缓存中的数据
      */
-    List<String> keys(String pattern);
+    List<Object> keys(String pattern);
+
+    /**
+     * 原生阻塞keys 不推荐使用
+     *
+     * @param pattern 模糊key
+     * @return 缓存中的数据
+     */
+    List<Object> keysBlock(String pattern);
 
 
     //-----------------------------------------------用于特殊场景，redis去重计数---------------------------------------------
@@ -211,11 +219,12 @@ public interface Cache<T> {
      * @return 计数器结果
      */
     Long incr(String key, long liveTime);
+
     /**
      * redis 计数器 累加
      * 注：到达liveTime之后，该次增加取消，即自动-1，而不是redis值为空
      *
-     * @param key      为累计的key，同一key每次调用则值 +1
+     * @param key 为累计的key，同一key每次调用则值 +1
      * @return 计数器结果
      */
     Long incr(String key);

framework/src/main/java/cn/lili/cache/impl/RedisCache.java

@@ -90,14 +90,13 @@ public class RedisCache implements Cache {
      */
     @Override
     public void vagueDel(Object key) {
-        Set<Object> keys = redisTemplate.keys(key + "*");
+        List keys = this.keys(key + "*");
         redisTemplate.delete(keys);
     }
 
     @Override
     public void clear() {
-
-        Set keys = redisTemplate.keys("*");
+        List keys = this.keys("*");
         redisTemplate.delete(keys);
     }
 
@@ -133,8 +132,8 @@ public class RedisCache implements Cache {
      * @return 模糊匹配key
      */
     @Override
-    public List<String> keys(String pattern) {
-        List<String> keys = new ArrayList<>();
+    public List<Object> keys(String pattern) {
+        List<Object> keys = new ArrayList<>();
         this.scan(pattern, item -> {
             //符合条件的key
             String key = new String(item, StandardCharsets.UTF_8);
@@ -143,6 +142,13 @@ public class RedisCache implements Cache {
         return keys;
     }
 
+    @Override
+    public List<Object> keysBlock(String pattern) {
+        Set<Object> set = redisTemplate.keys(pattern);
+        List<Object> list = new ArrayList<>();
+        list.addAll(set);
+        return list;
+    }
 
     /**
      * scan 实现

manager-api/src/test/java/cn/lili/test/CacheTest/CacheTest.java

@@ -1,5 +1,6 @@
 package cn.lili.test.CacheTest;
 
+import cn.hutool.json.JSONUtil;
 import cn.lili.cache.Cache;
 import cn.lili.cache.CachePrefix;
 import cn.lili.modules.statistics.util.StatisticsSuffix;
@@ -122,4 +123,51 @@ class CacheTest {
         Assertions.assertTrue(true);
     }
 
+
+    @Test
+    void scanTests() {
+
+        for (int i = 0; i < 1000000; i++) {
+            cache.put("scan" + i, i);
+        }
+        Date date = new Date();
+        System.out.println(JSONUtil.toJsonStr(cache.keys("scan999999*")));
+
+        System.out.println("100w数据耗时");
+        System.out.println(new Date().getTime() - date.getTime());
+
+
+        for (int i = 1000000; i < 5000000; i++) {
+            cache.put("scan" + i, i);
+        }
+
+        date = new Date();
+        System.out.println(JSONUtil.toJsonStr(cache.keys("scan999999*")));
+        System.out.println("600w数据耗时");
+        System.out.println(new Date().getTime() - date.getTime());
+
+    }
+
+    // scan 慢些，但是在缓存更多的情况下，表现更好，虽然用时更久，但是不会阻塞其他读写
+    //
+    //["scan999999"]
+    //redisTemplate scan 500w数据耗时
+    //2985
+    //["scan999999"]
+    //redisTemplate keys 500w数据耗时
+    //1073
+    @Test
+    void testKsysVsScan() {
+        Date date = new Date();
+        System.out.println(JSONUtil.toJsonStr(cache.keys("scan999999*")));
+        System.out.println("redisTemplate scan 500w数据耗时");
+        System.out.println(new Date().getTime() - date.getTime());
+
+        date = new Date();
+        System.out.println(JSONUtil.toJsonStr(cache.keysBlock("scan999999*")));
+        System.out.println("redisTemplate keys 500w数据耗时");
+        System.out.println(new Date().getTime() - date.getTime());
+
+    }
+
 }