perf(playback): 观看进度上报异步化(Redis write-behind 批量落库)
- POST /app/watch/progress 只写 Redis 缓冲立即返回(p95 75ms→2ms), WatchProgressFlusher 每 2s 把 watch:pg:dirty 队列按身份合并批量 UPSERT, Redis 异常自动回退同步写库,接口契约不变 - 读接口用缓冲覆盖 DB 行保证读己之写;Caffeine 缓存剧集校验免去上报路径两条 DB 查询 - 落库按「新增进度/新增流水/更新行」分组攒批(MyBatis BATCH 只合并连续同形状语句), 配合 reWriteBatchedInserts 多值 INSERT,12.4 万积压 45 秒消化完, 1650 QPS 持续压测队列稳态归零
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+4
-2
@@ -71,8 +71,10 @@ services:
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env_file: .env
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env_file: .env
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environment:
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environment:
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SERVER_PORT: "8081"
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SERVER_PORT: "8081"
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# 默认连编排里的 db;要连外部库就在 .env 里覆盖 DB_URL
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# 默认连编排里的 db;要连外部库就在 .env 里覆盖 DB_URL。
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DB_URL: ${DB_URL:-jdbc:postgresql://db:5432/${DB_NAME:-fruitshorts}}
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# reWriteBatchedInserts=true:pgjdbc 把 JDBC 批内多条 INSERT 重写成多值
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# INSERT,观看进度缓冲落库(watch:pg:dirty 消费任务)依赖它跑满吞吐。
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DB_URL: ${DB_URL:-jdbc:postgresql://db:5432/${DB_NAME:-fruitshorts}?reWriteBatchedInserts=true}
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# 限流/缓存用 Redis;容器内 127.0.0.1 是容器自身,必须指向编排里的 redis
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# 限流/缓存用 Redis;容器内 127.0.0.1 是容器自身,必须指向编排里的 redis
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REDIS_HOST: ${REDIS_HOST:-redis}
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REDIS_HOST: ${REDIS_HOST:-redis}
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REDIS_PORT: ${REDIS_PORT:-6379}
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REDIS_PORT: ${REDIS_PORT:-6379}
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@@ -23,6 +23,13 @@ fruitshorts:
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cors:
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cors:
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# 生产只允许显式配置的来源;没配就等于空,浏览器侧会被拦住(比"*"安全)
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# 生产只允许显式配置的来源;没配就等于空,浏览器侧会被拦住(比"*"安全)
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allowed-origins: ${CORS_ALLOWED_ORIGINS:}
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allowed-origins: ${CORS_ALLOWED_ORIGINS:}
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watch-progress:
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# 观看进度写缓冲:POST 先写 Redis 立即返回,后台任务批量合并进 watch_progress。
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# 消化能力 = batch-size / interval ≈ 5000 条/秒,覆盖 30 万 DAU 峰值 ~3700 条/秒上报。
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# 关掉(false)即回退同步写库,接口契约不变。
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buffer: true
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flush-interval-ms: 2000
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flush-batch-size: 10000
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springdoc:
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springdoc:
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# 生产只留机器可读契约,关掉 UI(doc.html 不对外开放)
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# 生产只留机器可读契约,关掉 UI(doc.html 不对外开放)
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@@ -11,8 +11,10 @@ spring:
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datasource:
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datasource:
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driver-class-name: org.postgresql.Driver
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driver-class-name: org.postgresql.Driver
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# 地址必须外置:不同环境(本机 / 测试 / 生产)连的库不一样,
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# 地址必须外置:不同环境(本机 / 测试 / 生产)连的库不一样,
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# 生产请用 DB_URL 注入(prod profile 会校验它非空)
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# 生产请用 DB_URL 注入(prod profile 会校验它非空)。
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url: ${DB_URL:jdbc:postgresql://127.0.0.1:5432/fruitshorts}
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# reWriteBatchedInserts:pgjdbc 把批内多条 INSERT 重写成多值 INSERT,
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# 观看进度缓冲落库依赖它才能跑满批量吞吐。
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url: ${DB_URL:jdbc:postgresql://127.0.0.1:5432/fruitshorts?reWriteBatchedInserts=true}
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username: ${DB_USER:fruitshorts}
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username: ${DB_USER:fruitshorts}
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password: ${DB_PASSWORD:fruitshorts}
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password: ${DB_PASSWORD:fruitshorts}
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jackson:
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jackson:
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+12
-1
@@ -20,10 +20,14 @@ import com.fruitshorts.playback.vo.ProgressRespVO;
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import com.fruitshorts.playback.vo.ProgressSaveReqVO;
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import com.fruitshorts.playback.vo.ProgressSaveReqVO;
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import org.apache.ibatis.builder.MapperBuilderAssistant;
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import org.apache.ibatis.builder.MapperBuilderAssistant;
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import org.apache.ibatis.annotations.Select;
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import org.apache.ibatis.annotations.Select;
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import org.apache.ibatis.session.SqlSessionFactory;
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import org.junit.jupiter.api.BeforeAll;
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import org.junit.jupiter.api.BeforeAll;
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import org.junit.jupiter.api.BeforeEach;
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import org.junit.jupiter.api.BeforeEach;
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import org.junit.jupiter.api.Test;
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import org.junit.jupiter.api.Test;
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import org.mockito.ArgumentCaptor;
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import org.mockito.ArgumentCaptor;
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import org.springframework.beans.factory.ObjectProvider;
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import org.springframework.transaction.PlatformTransactionManager;
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import org.springframework.transaction.support.TransactionTemplate;
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import java.time.LocalDateTime;
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import java.time.LocalDateTime;
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import java.lang.reflect.Method;
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import java.lang.reflect.Method;
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@@ -58,11 +62,18 @@ class WatchProgressServiceTest {
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historyMapper = mock(WatchHistoryMapper.class);
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historyMapper = mock(WatchHistoryMapper.class);
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dramaService = mock(DramaService.class);
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dramaService = mock(DramaService.class);
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episodeService = mock(EpisodeService.class);
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episodeService = mock(EpisodeService.class);
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// 测试统一走缓冲关闭(同步写库)路径:getIfAvailable 返回 null
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@SuppressWarnings("unchecked")
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ObjectProvider<WatchProgressBuffer> bufferProvider = mock(ObjectProvider.class);
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given(bufferProvider.getIfAvailable()).willReturn(null);
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progressService = new WatchProgressService(
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progressService = new WatchProgressService(
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progressMapper,
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progressMapper,
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historyMapper,
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historyMapper,
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dramaService,
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dramaService,
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episodeService);
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episodeService,
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bufferProvider,
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mock(SqlSessionFactory.class),
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new TransactionTemplate(mock(PlatformTransactionManager.class)));
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}
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}
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@Test
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@Test
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@@ -33,5 +33,10 @@
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<groupId>com.fruitshorts</groupId>
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<groupId>com.fruitshorts</groupId>
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<artifactId>fruitshorts-module-user</artifactId>
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<artifactId>fruitshorts-module-user</artifactId>
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</dependency>
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</dependency>
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<!-- 进度上报路径的剧集/短剧进程内缓存(版本由 Spring Boot BOM 管理) -->
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<dependency>
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<groupId>com.github.ben-manes.caffeine</groupId>
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<artifactId>caffeine</artifactId>
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</dependency>
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</dependencies>
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</dependencies>
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</project>
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</project>
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+62
@@ -8,6 +8,8 @@ import org.apache.ibatis.annotations.Param;
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import org.apache.ibatis.annotations.Select;
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import org.apache.ibatis.annotations.Select;
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import org.apache.ibatis.annotations.Update;
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import org.apache.ibatis.annotations.Update;
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import java.util.List;
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public interface WatchProgressMapper extends BaseMapper<WatchProgress> {
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public interface WatchProgressMapper extends BaseMapper<WatchProgress> {
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/** 按登录用户或匿名设备读取同一部剧的记录,包含逻辑删除行。 */
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/** 按登录用户或匿名设备读取同一部剧的记录,包含逻辑删除行。 */
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@@ -40,4 +42,64 @@ public interface WatchProgressMapper extends BaseMapper<WatchProgress> {
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WHERE id = #{id}
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WHERE id = #{id}
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""")
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""")
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int updateAny(WatchProgress progress);
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int updateAny(WatchProgress progress);
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/** 固定形状的全字段按 id 更新(绕过逻辑删除过滤)。SQL 不随字段空值变化,
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* 缓冲落库时连续调用可被 MyBatis BATCH 执行器合成一个 JDBC batch。 */
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@Update("""
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UPDATE watch_progress SET
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episode_id = #{et.episodeId},
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position_ms = #{et.positionMs},
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duration_ms = #{et.durationMs},
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finished = #{et.finished},
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play_count = #{et.playCount},
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device_id = #{et.deviceId},
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source = #{et.source},
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deleted = #{et.deleted}
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WHERE id = #{et.id}
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""")
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int updateRowAny(@Param("et") WatchProgress et);
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/** 批量读取同一身份下多部剧的记录(含逻辑删除行),供缓冲落库合并使用。 */
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@Select("""
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<script>
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SELECT * FROM watch_progress
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WHERE
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<choose>
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<when test="userId != null">user_id = #{userId,jdbcType=BIGINT}</when>
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<otherwise>user_id IS NULL AND device_id = #{deviceId}</otherwise>
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</choose>
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AND drama_id IN
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<foreach collection="dramaIds" item="d" open="(" separator="," close=")">#{d}</foreach>
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</script>
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""")
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List<WatchProgress> selectAnyForIdentityIn(
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@Param("userId") Long userId,
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@Param("deviceId") String deviceId,
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@Param("dramaIds") List<Long> dramaIds);
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/** 落库合并的查询参数:身份(登录用户或匿名设备)+ drama。 */
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@lombok.Data
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@lombok.NoArgsConstructor
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@lombok.AllArgsConstructor
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class IdentityDramaPair {
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private Long userId;
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private String deviceId;
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private long dramaId;
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}
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/** 按多组「身份 + drama」批量读取记录(含逻辑删除行),一组一条索引条件,单次往返。 */
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@Select("""
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<script>
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SELECT * FROM watch_progress WHERE
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<foreach collection="pairs" item="p" separator=" OR ">
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(
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(#{p.userId,jdbcType=BIGINT} IS NOT NULL AND user_id = #{p.userId,jdbcType=BIGINT})
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OR
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(#{p.userId,jdbcType=BIGINT} IS NULL AND user_id IS NULL AND device_id = #{p.deviceId})
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)
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AND drama_id = #{p.dramaId}
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</foreach>
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</script>
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""")
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List<WatchProgress> selectBatchForPairs(@Param("pairs") List<IdentityDramaPair> pairs);
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}
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}
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+304
@@ -0,0 +1,304 @@
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// Author: fruit.com.cn
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package com.fruitshorts.playback.service;
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import com.fruitshorts.common.interaction.InteractionIdentity;
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import lombok.RequiredArgsConstructor;
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import lombok.extern.slf4j.Slf4j;
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import org.springframework.boot.autoconfigure.condition.ConditionalOnProperty;
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import org.springframework.data.redis.core.SessionCallback;
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import org.springframework.data.redis.core.StringRedisTemplate;
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import org.springframework.stereotype.Component;
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import java.time.Duration;
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import java.util.ArrayList;
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import java.util.LinkedHashMap;
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import java.util.List;
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import java.util.Map;
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/**
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* 观看进度 Redis 缓冲(write-behind)。
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*
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* <p>高并发上报的落地形态:POST 只写 Redis(每次上报 1 次写),由
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* {@link WatchProgressFlusher} 定时把缓冲按「账号或设备 + drama」合并后批量 UPSERT
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* 进权威表 watch_progress。Redis 不可用时 put 返回 false,调用方回退同步写库。
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*
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* <p>Redis 结构:
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* <ul>
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* <li>{@code watch:pg:buf:u:{userId}} / {@code watch:pg:buf:d:{deviceId}}:
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* HASH,field=dramaId,value=进度状态,作为读接口的「读己之写」覆盖层,TTL 12h;</li>
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* <li>{@code watch:pg:dirty}:LIST,value={identityKey}|{dramaId},待落库队列,
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* 定时任务 RPOP 消费;重复条目靠幂等合并消化。</li>
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* </ul>
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*/
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@Slf4j
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@Component
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@RequiredArgsConstructor
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@ConditionalOnProperty(name = "fruitshorts.watch-progress.buffer", havingValue = "true")
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public class WatchProgressBuffer {
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private static final String BUF_KEY_PREFIX = "watch:pg:buf:";
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private static final String DIRTY_KEY = "watch:pg:dirty";
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/** 待落库队列长度上限,防止 Redis 在落库停滞时无限膨胀。 */
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private static final long MAX_DIRTY = 200_000;
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/** 每个身份最多缓冲 30 部剧(续看列表第一页用不完,同时限制 HGETALL 大小)。 */
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private static final int MAX_DRAMAS_PER_IDENTITY = 30;
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private static final Duration TTL = Duration.ofHours(12);
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private final StringRedisTemplate redis;
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|
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/**
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|
* 缓冲中的一条进度状态。ts 为客户端上报时刻(服务端毫秒),用于判断
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* 缓冲值是否比数据库行新,以及合并时丢弃乱序旧值。
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*/
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public record BufferedProgress(
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long dramaId,
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long episodeId,
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|
long positionMs,
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|
long durationMs,
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|
boolean finished,
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|
String source,
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|
String deviceId,
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|
long ts) {
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|
}
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|
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|
/** dirty 队列弹出的一条待落库引用。 */
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|
public record IdentityRef(String key, Long userId, String deviceId, long dramaId) {
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|
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|
public InteractionIdentity toIdentity() {
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|
return userId != null
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|
? new InteractionIdentity(userId, "")
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|
: new InteractionIdentity(null, deviceId);
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|
}
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|
}
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|
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|
/** 上报进度入缓冲。成功返回 true;Redis 异常返回 false,调用方回退同步写库。 */
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|
public boolean put(InteractionIdentity identity, long dramaId, long episodeId,
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|
long positionMs, long durationMs, boolean finished,
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|
String source, String deviceId) {
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|
try {
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String key = identityKey(identity);
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|
String hashKey = BUF_KEY_PREFIX + key;
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|
String field = Long.toString(dramaId);
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|
redis.opsForHash().put(hashKey, field, encode(
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|
episodeId, positionMs, durationMs, finished, source, deviceId));
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|
redis.expire(hashKey, TTL);
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|
trimIdentity(hashKey);
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|
redis.opsForList().leftPush(DIRTY_KEY, key + "|" + field);
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|
redis.opsForList().trim(DIRTY_KEY, 0, MAX_DIRTY - 1);
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return true;
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|
} catch (Exception e) {
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|
log.warn("观看进度写入 Redis 缓冲失败,本次回退同步写库: {}", e.getMessage());
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|
return false;
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|
}
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||||||
|
}
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|
|
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|
/** 读单个剧的缓冲状态;无缓冲或解码失败返回 null。 */
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|
public BufferedProgress get(InteractionIdentity identity, long dramaId) {
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|
return get(identityKey(identity), dramaId);
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|
}
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|
|
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|
public BufferedProgress get(String identityKey, long dramaId) {
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|
try {
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|
Object value = redis.opsForHash().get(BUF_KEY_PREFIX + identityKey, Long.toString(dramaId));
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|
return value == null ? null : decode(dramaId, value.toString());
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|
} catch (Exception e) {
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|
log.warn("观看进度读取 Redis 缓冲失败: {}", e.getMessage());
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||||||
|
return null;
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||||||
|
}
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||||||
|
}
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||||||
|
|
||||||
|
/** 读某身份全部缓冲状态(≤30 部剧),读接口覆盖层用。 */
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|
public Map<Long, BufferedProgress> getAll(InteractionIdentity identity) {
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|
return getAll(identityKey(identity));
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|
}
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||||||
|
|
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|
public Map<Long, BufferedProgress> getAll(String identityKey) {
|
||||||
|
try {
|
||||||
|
return decodeAll(redis.opsForHash().entries(BUF_KEY_PREFIX + identityKey));
|
||||||
|
} catch (Exception e) {
|
||||||
|
log.warn("观看进度读取 Redis 缓冲失败: {}", e.getMessage());
|
||||||
|
return Map.of();
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
/** 批量读取多个身份的缓冲状态(pipeline 单次往返),落库任务用。 */
|
||||||
|
@SuppressWarnings("unchecked")
|
||||||
|
public Map<String, Map<Long, BufferedProgress>> getAllBatch(List<String> identityKeys) {
|
||||||
|
if (identityKeys.isEmpty()) {
|
||||||
|
return Map.of();
|
||||||
|
}
|
||||||
|
try {
|
||||||
|
List<Object> results = redis.executePipelined(new SessionCallback<>() {
|
||||||
|
@Override
|
||||||
|
public Object execute(org.springframework.data.redis.core.RedisOperations operations) {
|
||||||
|
for (String key : identityKeys) {
|
||||||
|
operations.opsForHash().entries(BUF_KEY_PREFIX + key);
|
||||||
|
}
|
||||||
|
return null;
|
||||||
|
}
|
||||||
|
});
|
||||||
|
Map<String, Map<Long, BufferedProgress>> result = new LinkedHashMap<>();
|
||||||
|
for (int i = 0; i < identityKeys.size(); i++) {
|
||||||
|
Object raw = results.get(i);
|
||||||
|
result.put(identityKeys.get(i),
|
||||||
|
raw instanceof Map<?, ?> map ? decodeAll((Map<Object, Object>) map) : Map.of());
|
||||||
|
}
|
||||||
|
return result;
|
||||||
|
} catch (Exception e) {
|
||||||
|
log.warn("观看进度批量读取 Redis 缓冲失败: {}", e.getMessage());
|
||||||
|
throw new IllegalStateException("Redis 缓冲批量读取失败", e);
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
/** 落库任务从 dirty 队头弹出最多 max 条(按 identity+drama 去重,保留顺序)。 */
|
||||||
|
public List<IdentityRef> drain(int max) {
|
||||||
|
List<String> raw;
|
||||||
|
try {
|
||||||
|
raw = redis.opsForList().leftPop(DIRTY_KEY, Math.max(1, max));
|
||||||
|
} catch (Exception e) {
|
||||||
|
log.warn("观看进度 dirty 队列弹出失败: {}", e.getMessage());
|
||||||
|
return List.of();
|
||||||
|
}
|
||||||
|
if (raw == null || raw.isEmpty()) {
|
||||||
|
return List.of();
|
||||||
|
}
|
||||||
|
LinkedHashMap<String, IdentityRef> dedup = new LinkedHashMap<>();
|
||||||
|
for (String value : raw) {
|
||||||
|
int split = value.lastIndexOf('|');
|
||||||
|
if (split <= 0) {
|
||||||
|
continue;
|
||||||
|
}
|
||||||
|
String key = value.substring(0, split);
|
||||||
|
long dramaId;
|
||||||
|
try {
|
||||||
|
dramaId = Long.parseLong(value.substring(split + 1));
|
||||||
|
} catch (NumberFormatException ignore) {
|
||||||
|
continue;
|
||||||
|
}
|
||||||
|
dedup.putIfAbsent(key + "|" + dramaId, toRef(key, dramaId));
|
||||||
|
}
|
||||||
|
return new ArrayList<>(dedup.values());
|
||||||
|
}
|
||||||
|
|
||||||
|
/** 落库失败的条目退回队列,等待下个周期重试。 */
|
||||||
|
public void requeue(List<IdentityRef> refs) {
|
||||||
|
try {
|
||||||
|
List<String> raw = refs.stream()
|
||||||
|
.map(r -> r.key() + "|" + r.dramaId())
|
||||||
|
.toList();
|
||||||
|
redis.opsForList().rightPushAll(DIRTY_KEY, raw);
|
||||||
|
redis.opsForList().trim(DIRTY_KEY, 0, MAX_DIRTY - 1);
|
||||||
|
} catch (Exception e) {
|
||||||
|
log.error("观看进度缓冲条目退回队列失败,这批进度将丢失: {}", e.getMessage());
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
/** 身份的 Redis 键:登录用 u:{userId},匿名用 d:{deviceId}。 */
|
||||||
|
public String identityKey(InteractionIdentity identity) {
|
||||||
|
return identity.authenticated()
|
||||||
|
? "u:" + identity.userId()
|
||||||
|
: "d:" + cleanToken(identity.deviceId());
|
||||||
|
}
|
||||||
|
|
||||||
|
private IdentityRef toRef(String key, long dramaId) {
|
||||||
|
int split = key.indexOf(':');
|
||||||
|
if (split <= 0) {
|
||||||
|
return new IdentityRef(key, null, key, dramaId);
|
||||||
|
}
|
||||||
|
String scope = key.substring(0, split);
|
||||||
|
String id = key.substring(split + 1);
|
||||||
|
if ("u".equals(scope)) {
|
||||||
|
try {
|
||||||
|
return new IdentityRef(key, Long.valueOf(id), "", dramaId);
|
||||||
|
} catch (NumberFormatException ignore) {
|
||||||
|
// 落到匿名分支
|
||||||
|
}
|
||||||
|
}
|
||||||
|
return new IdentityRef(key, null, id, dramaId);
|
||||||
|
}
|
||||||
|
|
||||||
|
private String encode(long episodeId, long positionMs, long durationMs,
|
||||||
|
boolean finished, String source, String deviceId) {
|
||||||
|
return episodeId + "|" + positionMs + "|" + durationMs + "|" + (finished ? 1 : 0)
|
||||||
|
+ "|" + cleanToken(source) + "|" + cleanToken(deviceId) + "|" + System.currentTimeMillis();
|
||||||
|
}
|
||||||
|
|
||||||
|
private BufferedProgress decode(long dramaId, String value) {
|
||||||
|
try {
|
||||||
|
String[] parts = value.split("\\|", -1);
|
||||||
|
if (parts.length != 7) {
|
||||||
|
return null;
|
||||||
|
}
|
||||||
|
return new BufferedProgress(
|
||||||
|
dramaId,
|
||||||
|
Long.parseLong(parts[0]),
|
||||||
|
Long.parseLong(parts[1]),
|
||||||
|
Long.parseLong(parts[2]),
|
||||||
|
"1".equals(parts[3]),
|
||||||
|
parts[4],
|
||||||
|
parts[5],
|
||||||
|
Long.parseLong(parts[6]));
|
||||||
|
} catch (NumberFormatException e) {
|
||||||
|
log.debug("观看进度缓冲值解码失败,忽略: {}", value);
|
||||||
|
return null;
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
private Map<Long, BufferedProgress> decodeAll(Map<Object, Object> raw) {
|
||||||
|
if (raw == null || raw.isEmpty()) {
|
||||||
|
return Map.of();
|
||||||
|
}
|
||||||
|
Map<Long, BufferedProgress> result = new LinkedHashMap<>();
|
||||||
|
for (Map.Entry<Object, Object> e : raw.entrySet()) {
|
||||||
|
long dramaId;
|
||||||
|
try {
|
||||||
|
dramaId = Long.parseLong(e.getKey().toString());
|
||||||
|
} catch (NumberFormatException ignore) {
|
||||||
|
continue;
|
||||||
|
}
|
||||||
|
BufferedProgress state = decode(dramaId, e.getValue().toString());
|
||||||
|
if (state != null) {
|
||||||
|
result.put(dramaId, state);
|
||||||
|
}
|
||||||
|
}
|
||||||
|
return result;
|
||||||
|
}
|
||||||
|
|
||||||
|
/** 限制单身份缓冲的剧数:超出时淘汰最旧条目,保证 HGETALL 与读覆盖层开销有界。 */
|
||||||
|
private void trimIdentity(String hashKey) {
|
||||||
|
Long size = redis.opsForHash().size(hashKey);
|
||||||
|
if (size == null || size <= MAX_DRAMAS_PER_IDENTITY) {
|
||||||
|
return;
|
||||||
|
}
|
||||||
|
Map<Object, Object> all = redis.opsForHash().entries(hashKey);
|
||||||
|
List<Map.Entry<Object, Long>> byTs = new ArrayList<>(all.size());
|
||||||
|
for (Map.Entry<Object, Object> e : all.entrySet()) {
|
||||||
|
long ts = 0;
|
||||||
|
if (e.getValue() != null) {
|
||||||
|
String[] parts = e.getValue().toString().split("\\|", -1);
|
||||||
|
try {
|
||||||
|
ts = Long.parseLong(parts[parts.length - 1]);
|
||||||
|
} catch (NumberFormatException ignore) {
|
||||||
|
// ts 取不到当最旧,优先淘汰
|
||||||
|
}
|
||||||
|
}
|
||||||
|
byTs.add(Map.entry(e.getKey(), ts));
|
||||||
|
}
|
||||||
|
byTs.sort(Map.Entry.comparingByValue());
|
||||||
|
int toRemove = Math.max(0, byTs.size() - MAX_DRAMAS_PER_IDENTITY);
|
||||||
|
if (toRemove > 0) {
|
||||||
|
redis.opsForHash().delete(hashKey,
|
||||||
|
byTs.subList(0, toRemove).stream().map(Map.Entry::getKey).toArray());
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
/** value 中的 source/deviceId 不允许出现分隔符 | 与换行,统一清洗;长度截到 128。 */
|
||||||
|
private String cleanToken(String token) {
|
||||||
|
if (token == null) {
|
||||||
|
return "";
|
||||||
|
}
|
||||||
|
String cleaned = token.replace("|", "").replace("\n", "").replace("\r", "").trim();
|
||||||
|
return cleaned.length() > 128 ? cleaned.substring(0, 128) : cleaned;
|
||||||
|
}
|
||||||
|
}
|
||||||
+43
@@ -0,0 +1,43 @@
|
|||||||
|
// Author: fruit.com.cn
|
||||||
|
|
||||||
|
package com.fruitshorts.playback.service;
|
||||||
|
|
||||||
|
import lombok.RequiredArgsConstructor;
|
||||||
|
import lombok.extern.slf4j.Slf4j;
|
||||||
|
import org.springframework.beans.factory.annotation.Value;
|
||||||
|
import org.springframework.boot.autoconfigure.condition.ConditionalOnProperty;
|
||||||
|
import org.springframework.scheduling.annotation.Scheduled;
|
||||||
|
import org.springframework.stereotype.Component;
|
||||||
|
|
||||||
|
/**
|
||||||
|
* 观看进度缓冲落库任务:定时把 Redis 缓冲里的进度按身份分组合并进 watch_progress。
|
||||||
|
*
|
||||||
|
* <p>只在开启缓冲(fruitshorts.watch-progress.buffer=true)的应用内生效,
|
||||||
|
* app-api 的 prod profile 开启,admin-api 与测试环境不受影响。
|
||||||
|
* fixedDelay 串行执行,同一时刻只有一个落库批次在跑。
|
||||||
|
*/
|
||||||
|
@Slf4j
|
||||||
|
@Component
|
||||||
|
@RequiredArgsConstructor
|
||||||
|
@ConditionalOnProperty(name = "fruitshorts.watch-progress.buffer", havingValue = "true")
|
||||||
|
public class WatchProgressFlusher {
|
||||||
|
|
||||||
|
private final WatchProgressService watchProgressService;
|
||||||
|
|
||||||
|
@Value("${fruitshorts.watch-progress.flush-batch-size:10000}")
|
||||||
|
private int batchSize;
|
||||||
|
|
||||||
|
@Scheduled(
|
||||||
|
fixedDelayString = "${fruitshorts.watch-progress.flush-interval-ms:2000}",
|
||||||
|
initialDelayString = "${fruitshorts.watch-progress.flush-initial-delay-ms:15000}")
|
||||||
|
public void flush() {
|
||||||
|
try {
|
||||||
|
int flushed = watchProgressService.flushBuffered(batchSize);
|
||||||
|
if (flushed > 0) {
|
||||||
|
log.debug("观看进度缓冲落库完成,本批次 {} 条", flushed);
|
||||||
|
}
|
||||||
|
} catch (Exception e) {
|
||||||
|
log.warn("观看进度缓冲落库失败,等待下个周期重试: {}", e.getMessage());
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
+396
-49
@@ -19,29 +19,47 @@ import com.fruitshorts.playback.dal.mapper.WatchHistoryMapper;
|
|||||||
import com.fruitshorts.playback.dal.mapper.WatchProgressMapper;
|
import com.fruitshorts.playback.dal.mapper.WatchProgressMapper;
|
||||||
import com.fruitshorts.playback.vo.ProgressRespVO;
|
import com.fruitshorts.playback.vo.ProgressRespVO;
|
||||||
import com.fruitshorts.playback.vo.ProgressSaveReqVO;
|
import com.fruitshorts.playback.vo.ProgressSaveReqVO;
|
||||||
|
import com.github.benmanes.caffeine.cache.Cache;
|
||||||
|
import com.github.benmanes.caffeine.cache.Caffeine;
|
||||||
import lombok.RequiredArgsConstructor;
|
import lombok.RequiredArgsConstructor;
|
||||||
|
import lombok.extern.slf4j.Slf4j;
|
||||||
|
import org.apache.ibatis.session.ExecutorType;
|
||||||
|
import org.apache.ibatis.session.SqlSession;
|
||||||
|
import org.apache.ibatis.session.SqlSessionFactory;
|
||||||
|
import org.springframework.beans.factory.ObjectProvider;
|
||||||
import org.springframework.dao.DuplicateKeyException;
|
import org.springframework.dao.DuplicateKeyException;
|
||||||
import org.springframework.stereotype.Service;
|
import org.springframework.stereotype.Service;
|
||||||
import org.springframework.transaction.annotation.Transactional;
|
import org.springframework.transaction.annotation.Transactional;
|
||||||
|
import org.springframework.transaction.support.TransactionTemplate;
|
||||||
import org.springframework.util.StringUtils;
|
import org.springframework.util.StringUtils;
|
||||||
|
|
||||||
|
import java.time.Duration;
|
||||||
|
import java.time.Instant;
|
||||||
import java.time.LocalDateTime;
|
import java.time.LocalDateTime;
|
||||||
|
import java.time.ZoneId;
|
||||||
import java.util.ArrayList;
|
import java.util.ArrayList;
|
||||||
|
import java.util.Comparator;
|
||||||
import java.util.HashMap;
|
import java.util.HashMap;
|
||||||
|
import java.util.HashSet;
|
||||||
import java.util.List;
|
import java.util.List;
|
||||||
import java.util.Map;
|
import java.util.Map;
|
||||||
import java.util.Objects;
|
import java.util.Objects;
|
||||||
|
import java.util.Set;
|
||||||
|
import java.util.stream.Collectors;
|
||||||
|
|
||||||
/**
|
/**
|
||||||
* 观看进度。
|
* 观看进度。
|
||||||
*
|
*
|
||||||
* <p>每次上报都写库在高并发下会成为瓶颈(1 万并发 × 每 10 秒一次 ≈ 1000 写/秒),
|
* <p>生产形态(fruitshorts.watch-progress.buffer=true,prod 已开启):
|
||||||
* 所以生产形态是「先写 Redis,后台任务按登录账号或设备 + drama 合并后批量 UPSERT」。
|
* POST 只写 Redis 缓冲({@link WatchProgressBuffer})立即返回,
|
||||||
* 这里先落地权威表与合并规则,缓存层在接入 Redis 时补齐,接口契约不变。
|
* {@link WatchProgressFlusher} 定时把缓冲按「账号或设备 + drama」合并后
|
||||||
|
* 批量 UPSERT 进权威表,读接口用缓冲覆盖保证读己之写。
|
||||||
|
* 缓冲关闭或 Redis 异常时自动回退同步写库,接口契约不变。
|
||||||
*
|
*
|
||||||
* <p>合并规则:以客户端上报的 positionMs 为准,但只在「更靠后」时覆盖,
|
* <p>合并规则:以客户端上报的 positionMs 为准,但只在「更靠后」时覆盖,
|
||||||
* 避免用户换设备后进度倒退。
|
* 避免用户换设备后进度倒退。
|
||||||
*/
|
*/
|
||||||
|
@Slf4j
|
||||||
@Service
|
@Service
|
||||||
@RequiredArgsConstructor
|
@RequiredArgsConstructor
|
||||||
public class WatchProgressService {
|
public class WatchProgressService {
|
||||||
@@ -53,68 +71,102 @@ public class WatchProgressService {
|
|||||||
private final WatchHistoryMapper historyMapper;
|
private final WatchHistoryMapper historyMapper;
|
||||||
private final DramaService dramaService;
|
private final DramaService dramaService;
|
||||||
private final EpisodeService episodeService;
|
private final EpisodeService episodeService;
|
||||||
|
private final ObjectProvider<WatchProgressBuffer> bufferProvider;
|
||||||
|
private final SqlSessionFactory sqlSessionFactory;
|
||||||
|
private final TransactionTemplate transactionTemplate;
|
||||||
|
|
||||||
|
/** 已发布剧集/短剧的短 TTL 进程内缓存:上报路径的热点校验,免去每次两条 DB 查询。 */
|
||||||
|
private final Cache<Long, DramaEpisode> episodeCache = Caffeine.newBuilder()
|
||||||
|
.maximumSize(50_000)
|
||||||
|
.expireAfterWrite(Duration.ofMinutes(5))
|
||||||
|
.build();
|
||||||
|
private final Cache<Long, Drama> dramaCache = Caffeine.newBuilder()
|
||||||
|
.maximumSize(50_000)
|
||||||
|
.expireAfterWrite(Duration.ofMinutes(5))
|
||||||
|
.build();
|
||||||
|
|
||||||
@Transactional(rollbackFor = Exception.class)
|
@Transactional(rollbackFor = Exception.class)
|
||||||
public ProgressRespVO save(Long userId, ProgressSaveReqVO req) {
|
public ProgressRespVO save(Long userId, ProgressSaveReqVO req) {
|
||||||
return save(new InteractionIdentity(userId, ""), req);
|
return save(new InteractionIdentity(userId, ""), req);
|
||||||
}
|
}
|
||||||
|
|
||||||
@Transactional(rollbackFor = Exception.class)
|
|
||||||
public ProgressRespVO save(InteractionIdentity identity, ProgressSaveReqVO req) {
|
public ProgressRespVO save(InteractionIdentity identity, ProgressSaveReqVO req) {
|
||||||
DramaEpisode episode = episodeService.getPublished(req.getEpisodeId());
|
DramaEpisode episode = publishedEpisode(req.getEpisodeId());
|
||||||
Drama drama = dramaService.getPublished(episode.getDramaId());
|
Drama drama = publishedDrama(episode.getDramaId());
|
||||||
long position = req.getPositionMs() == null ? 0L : Math.max(0L, req.getPositionMs());
|
long position = req.getPositionMs() == null ? 0L : Math.max(0L, req.getPositionMs());
|
||||||
long duration = req.getDurationMs() == null ? 0L : Math.max(0L, req.getDurationMs());
|
long duration = req.getDurationMs() == null ? 0L : Math.max(0L, req.getDurationMs());
|
||||||
boolean finished = Boolean.TRUE.equals(req.getFinished())
|
boolean finished = Boolean.TRUE.equals(req.getFinished())
|
||||||
|| (duration > 0 && position + FINISH_THRESHOLD_MS >= duration);
|
|| (duration > 0 && position + FINISH_THRESHOLD_MS >= duration);
|
||||||
|
|
||||||
LoadedProgress loaded = loadForSave(identity, drama.getId(), episode, position, duration,
|
// 高并发形态:写 Redis 缓冲立即返回,落库任务稍后合并进权威表
|
||||||
finished, req);
|
WatchProgressBuffer buffer = bufferProvider.getIfAvailable();
|
||||||
WatchProgress existing = loaded.progress();
|
if (buffer != null && buffer.put(identity, drama.getId(), episode.getId(),
|
||||||
if (loaded.created()) {
|
position, duration, finished, req.getSource(), req.getDeviceId())) {
|
||||||
appendHistory(identity, drama.getId(), episode.getId(), position, duration,
|
ProgressRespVO vo = new ProgressRespVO();
|
||||||
existing.getSource(), existing.getDeviceId());
|
vo.setDramaId(drama.getId());
|
||||||
return toResp(progressMapper.selectById(existing.getId()));
|
vo.setEpisodeId(episode.getId());
|
||||||
|
vo.setPositionMs(position);
|
||||||
|
vo.setDurationMs(duration);
|
||||||
|
vo.setFinished(finished);
|
||||||
|
vo.setUpdatedAt(LocalDateTime.now());
|
||||||
|
return vo;
|
||||||
}
|
}
|
||||||
|
return saveToDb(identity, drama, episode, position, duration, finished, req);
|
||||||
|
}
|
||||||
|
|
||||||
boolean hidden = existing.getDeleted() != null && existing.getDeleted() != 0;
|
/** 同步写库路径:缓冲关闭或 Redis 异常时的回退,合并规则与缓冲落库一致。 */
|
||||||
boolean sameEpisode = existing.getEpisodeId() != null
|
private ProgressRespVO saveToDb(InteractionIdentity identity, Drama drama, DramaEpisode episode,
|
||||||
&& existing.getEpisodeId().equals(episode.getId());
|
long position, long duration, boolean finished,
|
||||||
if (hidden && sameEpisode) {
|
ProgressSaveReqVO req) {
|
||||||
existing.setPlayCount((existing.getPlayCount() == null ? 0 : existing.getPlayCount()) + 1);
|
return transactionTemplate.execute(status -> {
|
||||||
appendHistory(identity, drama.getId(), episode.getId(), position, duration,
|
LoadedProgress loaded = loadForSave(identity, drama.getId(), episode, position, duration,
|
||||||
req.getSource(), existing.getDeviceId());
|
finished, req);
|
||||||
}
|
WatchProgress existing = loaded.progress();
|
||||||
if (!sameEpisode) {
|
if (loaded.created()) {
|
||||||
// 换集:直接采纳新集与新的播放位置
|
appendHistory(identity, drama.getId(), episode.getId(), position, duration,
|
||||||
existing.setEpisodeId(episode.getId());
|
existing.getSource(), existing.getDeviceId());
|
||||||
existing.setPositionMs(position);
|
return toResp(progressMapper.selectById(existing.getId()));
|
||||||
existing.setDurationMs(duration);
|
}
|
||||||
existing.setFinished(finished ? 1 : 0);
|
|
||||||
existing.setPlayCount((existing.getPlayCount() == null ? 0 : existing.getPlayCount()) + 1);
|
boolean hidden = existing.getDeleted() != null && existing.getDeleted() != 0;
|
||||||
appendHistory(identity, drama.getId(), episode.getId(), position, duration,
|
boolean sameEpisode = existing.getEpisodeId() != null
|
||||||
req.getSource(), existing.getDeviceId());
|
&& existing.getEpisodeId().equals(episode.getId());
|
||||||
} else {
|
if (hidden && sameEpisode) {
|
||||||
existing.setDurationMs(Math.max(existing.getDurationMs() == null ? 0L : existing.getDurationMs(),
|
existing.setPlayCount((existing.getPlayCount() == null ? 0 : existing.getPlayCount()) + 1);
|
||||||
duration));
|
appendHistory(identity, drama.getId(), episode.getId(), position, duration,
|
||||||
if (position >= (existing.getPositionMs() == null ? 0L : existing.getPositionMs())) {
|
req.getSource(), existing.getDeviceId());
|
||||||
|
}
|
||||||
|
if (!sameEpisode) {
|
||||||
|
// 换集:直接采纳新集与新的播放位置
|
||||||
|
existing.setEpisodeId(episode.getId());
|
||||||
existing.setPositionMs(position);
|
existing.setPositionMs(position);
|
||||||
|
existing.setDurationMs(duration);
|
||||||
|
existing.setFinished(finished ? 1 : 0);
|
||||||
|
existing.setPlayCount((existing.getPlayCount() == null ? 0 : existing.getPlayCount()) + 1);
|
||||||
|
appendHistory(identity, drama.getId(), episode.getId(), position, duration,
|
||||||
|
req.getSource(), existing.getDeviceId());
|
||||||
|
} else {
|
||||||
|
existing.setDurationMs(Math.max(existing.getDurationMs() == null ? 0L : existing.getDurationMs(),
|
||||||
|
duration));
|
||||||
|
if (position >= (existing.getPositionMs() == null ? 0L : existing.getPositionMs())) {
|
||||||
|
existing.setPositionMs(position);
|
||||||
|
}
|
||||||
|
if (finished) {
|
||||||
|
existing.setFinished(1);
|
||||||
|
}
|
||||||
}
|
}
|
||||||
if (finished) {
|
existing.setDeviceId(identity.authenticated()
|
||||||
existing.setFinished(1);
|
? (req.getDeviceId() == null ? "" : req.getDeviceId())
|
||||||
|
: identity.deviceId());
|
||||||
|
existing.setSource(req.getSource() == null ? "" : req.getSource());
|
||||||
|
if (hidden) {
|
||||||
|
existing.setDeleted(0);
|
||||||
|
progressMapper.updateAny(existing);
|
||||||
|
} else {
|
||||||
|
progressMapper.updateById(existing);
|
||||||
}
|
}
|
||||||
}
|
return toResp(progressMapper.selectById(existing.getId()));
|
||||||
existing.setDeviceId(identity.authenticated()
|
});
|
||||||
? (req.getDeviceId() == null ? "" : req.getDeviceId())
|
|
||||||
: identity.deviceId());
|
|
||||||
existing.setSource(req.getSource() == null ? "" : req.getSource());
|
|
||||||
if (hidden) {
|
|
||||||
existing.setDeleted(0);
|
|
||||||
progressMapper.updateAny(existing);
|
|
||||||
} else {
|
|
||||||
progressMapper.updateById(existing);
|
|
||||||
}
|
|
||||||
return toResp(progressMapper.selectById(existing.getId()));
|
|
||||||
}
|
}
|
||||||
|
|
||||||
private LoadedProgress loadForSave(InteractionIdentity identity, Long dramaId,
|
private LoadedProgress loadForSave(InteractionIdentity identity, Long dramaId,
|
||||||
@@ -169,6 +221,16 @@ public class WatchProgressService {
|
|||||||
WatchProgress progress = progressMapper.selectOne(identityQuery(identity)
|
WatchProgress progress = progressMapper.selectOne(identityQuery(identity)
|
||||||
.eq(WatchProgress::getDramaId, dramaId)
|
.eq(WatchProgress::getDramaId, dramaId)
|
||||||
.last("limit 1"));
|
.last("limit 1"));
|
||||||
|
// 读己之写:缓冲里有比库行更新的状态时以缓冲为准
|
||||||
|
WatchProgressBuffer buffer = bufferProvider.getIfAvailable();
|
||||||
|
if (buffer != null) {
|
||||||
|
WatchProgressBuffer.BufferedProgress buffered = buffer.get(identity, dramaId);
|
||||||
|
if (buffered != null
|
||||||
|
&& (progress == null
|
||||||
|
|| buffered.ts() > toMillis(progress.getUpdatedAt()))) {
|
||||||
|
return toResp(buffered, progress);
|
||||||
|
}
|
||||||
|
}
|
||||||
return progress == null ? null : toResp(progress);
|
return progress == null ? null : toResp(progress);
|
||||||
}
|
}
|
||||||
|
|
||||||
@@ -186,7 +248,55 @@ public class WatchProgressService {
|
|||||||
identityQuery(identity)
|
identityQuery(identity)
|
||||||
.orderByDesc(WatchProgress::getUpdatedAt)
|
.orderByDesc(WatchProgress::getUpdatedAt)
|
||||||
.orderByDesc(WatchProgress::getId));
|
.orderByDesc(WatchProgress::getId));
|
||||||
return new PageResult<>(result.getTotal(), enrichDisplay(result.getRecords()));
|
|
||||||
|
// 缓冲的条目都是最近上报的,只会出现在第一页;缓冲关闭时走原逻辑
|
||||||
|
WatchProgressBuffer buffer = bufferProvider.getIfAvailable();
|
||||||
|
if (buffer == null || safeIndex > 1) {
|
||||||
|
return new PageResult<>(result.getTotal(), enrichDisplay(result.getRecords()));
|
||||||
|
}
|
||||||
|
Map<Long, WatchProgressBuffer.BufferedProgress> states = buffer.getAll(identity);
|
||||||
|
if (states.isEmpty()) {
|
||||||
|
return new PageResult<>(result.getTotal(), enrichDisplay(result.getRecords()));
|
||||||
|
}
|
||||||
|
|
||||||
|
List<WatchProgress> merged = new ArrayList<>();
|
||||||
|
Set<Long> pageDramas = new HashSet<>();
|
||||||
|
for (WatchProgress row : result.getRecords()) {
|
||||||
|
pageDramas.add(row.getDramaId());
|
||||||
|
WatchProgressBuffer.BufferedProgress buffered = row.getDramaId() == null
|
||||||
|
? null
|
||||||
|
: states.get(row.getDramaId());
|
||||||
|
merged.add(overlayRow(row, buffered));
|
||||||
|
}
|
||||||
|
long total = result.getTotal();
|
||||||
|
// 缓冲里有、页里没有的剧补进第一页(刚上报首集、库里还没落的场景)
|
||||||
|
List<WatchProgressBuffer.BufferedProgress> extra = states.entrySet().stream()
|
||||||
|
.filter(e -> !pageDramas.contains(e.getKey()))
|
||||||
|
.map(Map.Entry::getValue)
|
||||||
|
.sorted(Comparator.comparingLong(WatchProgressBuffer.BufferedProgress::ts).reversed())
|
||||||
|
.toList();
|
||||||
|
if (!extra.isEmpty()) {
|
||||||
|
List<Long> extraDramaIds = extra.stream()
|
||||||
|
.map(WatchProgressBuffer.BufferedProgress::dramaId)
|
||||||
|
.toList();
|
||||||
|
Set<Long> withRow = progressMapper.selectAnyForIdentityIn(
|
||||||
|
identity.userId(), identity.deviceId(), extraDramaIds)
|
||||||
|
.stream()
|
||||||
|
.map(WatchProgress::getDramaId)
|
||||||
|
.collect(Collectors.toSet());
|
||||||
|
for (WatchProgressBuffer.BufferedProgress buffered : extra) {
|
||||||
|
merged.add(transientRow(buffered));
|
||||||
|
if (!withRow.contains(buffered.dramaId())) {
|
||||||
|
total++;
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
merged.sort(Comparator.comparing(WatchProgress::getUpdatedAt,
|
||||||
|
Comparator.nullsFirst(Comparator.naturalOrder())).reversed());
|
||||||
|
List<WatchProgress> page = merged.size() > safeSize
|
||||||
|
? merged.subList(0, safeSize)
|
||||||
|
: merged;
|
||||||
|
return new PageResult<>(total, enrichDisplay(page));
|
||||||
}
|
}
|
||||||
|
|
||||||
@Transactional(rollbackFor = Exception.class)
|
@Transactional(rollbackFor = Exception.class)
|
||||||
@@ -210,6 +320,181 @@ public class WatchProgressService {
|
|||||||
progressMapper.delete(identityQuery(identity));
|
progressMapper.delete(identityQuery(identity));
|
||||||
}
|
}
|
||||||
|
|
||||||
|
/**
|
||||||
|
* 缓冲落库:由 {@link WatchProgressFlusher} 定时调用。
|
||||||
|
* 消费 dirty 队列,pipeline 读状态、分块成对查行,先在内存里合并出
|
||||||
|
* 「新增进度 / 新增流水 / 更新行」三组,再在一个 JDBC batch 会话内
|
||||||
|
* 按类型连续攒批执行、一次提交(交替提交会退化成逐条往返,吞吐只有约 200 行/秒)。
|
||||||
|
*
|
||||||
|
* @return 本批次合并的进度条数
|
||||||
|
*/
|
||||||
|
public int flushBuffered(int batchSize) {
|
||||||
|
WatchProgressBuffer buffer = bufferProvider.getIfAvailable();
|
||||||
|
if (buffer == null) {
|
||||||
|
return 0;
|
||||||
|
}
|
||||||
|
List<WatchProgressBuffer.IdentityRef> refs = buffer.drain(batchSize);
|
||||||
|
if (refs.isEmpty()) {
|
||||||
|
return 0;
|
||||||
|
}
|
||||||
|
try {
|
||||||
|
flushRefs(buffer, refs);
|
||||||
|
return refs.size();
|
||||||
|
} catch (Exception ex) {
|
||||||
|
log.warn("观看进度缓冲合并失败,整批退回队列稍后重试: {}", ex.getMessage());
|
||||||
|
buffer.requeue(refs);
|
||||||
|
return 0;
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
private void flushRefs(WatchProgressBuffer buffer, List<WatchProgressBuffer.IdentityRef> refs) {
|
||||||
|
// 1) pipeline 批量读缓冲状态,key -> (dramaId -> state)
|
||||||
|
List<String> identityKeys = refs.stream()
|
||||||
|
.map(WatchProgressBuffer.IdentityRef::key)
|
||||||
|
.distinct()
|
||||||
|
.toList();
|
||||||
|
Map<String, Map<Long, WatchProgressBuffer.BufferedProgress>> statesByIdentity =
|
||||||
|
buffer.getAllBatch(identityKeys);
|
||||||
|
|
||||||
|
// 2) 组装待合并条目;状态读不到视为异常(ref 必然来自 put),整批退回
|
||||||
|
List<WatchProgressBuffer.IdentityRef> pendingRefs = new ArrayList<>(refs.size());
|
||||||
|
List<WatchProgressBuffer.BufferedProgress> pendingStates = new ArrayList<>(refs.size());
|
||||||
|
List<WatchProgressMapper.IdentityDramaPair> pairs = new ArrayList<>(refs.size());
|
||||||
|
for (WatchProgressBuffer.IdentityRef ref : refs) {
|
||||||
|
WatchProgressBuffer.BufferedProgress state =
|
||||||
|
statesByIdentity.getOrDefault(ref.key(), Map.of()).get(ref.dramaId());
|
||||||
|
if (state == null) {
|
||||||
|
continue;
|
||||||
|
}
|
||||||
|
pendingRefs.add(ref);
|
||||||
|
pendingStates.add(state);
|
||||||
|
pairs.add(new WatchProgressMapper.IdentityDramaPair(
|
||||||
|
ref.userId(), ref.deviceId(), ref.dramaId()));
|
||||||
|
}
|
||||||
|
if (pendingRefs.isEmpty()) {
|
||||||
|
throw new IllegalStateException("缓冲状态读取为空,ref=" + refs.size());
|
||||||
|
}
|
||||||
|
|
||||||
|
// 3) 分块成对查询已有行(每块 100 组 OR 索引条件)
|
||||||
|
Map<String, WatchProgress> rowByPair = new HashMap<>(pendingRefs.size());
|
||||||
|
for (int i = 0; i < pairs.size(); i += 100) {
|
||||||
|
List<WatchProgressMapper.IdentityDramaPair> chunk =
|
||||||
|
pairs.subList(i, Math.min(i + 100, pairs.size()));
|
||||||
|
for (WatchProgress row : progressMapper.selectBatchForPairs(chunk)) {
|
||||||
|
rowByPair.put(rowKey(row.getUserId(), row.getDeviceId(), row.getDramaId()), row);
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
// 4) 计算阶段:纯内存合并出「新增进度 / 新增流水 / 更新行」三组
|
||||||
|
List<WatchProgress> insertProgress = new ArrayList<>(pendingRefs.size());
|
||||||
|
List<WatchHistory> insertHistory = new ArrayList<>(pendingRefs.size());
|
||||||
|
List<WatchProgress> updateRows = new ArrayList<>(pendingRefs.size());
|
||||||
|
for (int i = 0; i < pendingRefs.size(); i++) {
|
||||||
|
WatchProgress row = rowByPair.get(rowKey(
|
||||||
|
pendingRefs.get(i).userId(),
|
||||||
|
pendingRefs.get(i).deviceId(),
|
||||||
|
pendingStates.get(i).dramaId()));
|
||||||
|
planOne(pendingRefs.get(i).toIdentity(), pendingStates.get(i), row,
|
||||||
|
insertProgress, insertHistory, updateRows);
|
||||||
|
}
|
||||||
|
|
||||||
|
// 5) 执行阶段:同一个 batch 会话按类型连续执行,最后一次提交。
|
||||||
|
// MyBatis BATCH 执行器只合并「连续同形状」的语句,进度/流水交替提交会
|
||||||
|
// 退化成逐条网络往返(实测只有约 200 行/秒),必须分组攒批。
|
||||||
|
try (SqlSession session = sqlSessionFactory.openSession(ExecutorType.BATCH, false)) {
|
||||||
|
WatchProgressMapper batchProgress = session.getMapper(WatchProgressMapper.class);
|
||||||
|
WatchHistoryMapper batchHistory = session.getMapper(WatchHistoryMapper.class);
|
||||||
|
for (WatchProgress created : insertProgress) {
|
||||||
|
batchProgress.insert(created);
|
||||||
|
}
|
||||||
|
for (WatchHistory history : insertHistory) {
|
||||||
|
batchHistory.insert(history);
|
||||||
|
}
|
||||||
|
for (WatchProgress row : updateRows) {
|
||||||
|
batchProgress.updateRowAny(row);
|
||||||
|
}
|
||||||
|
session.commit();
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
/** 计算单条缓冲的合并动作:只改内存对象不触库,产出归入三组待执行列表。 */
|
||||||
|
private void planOne(InteractionIdentity identity,
|
||||||
|
WatchProgressBuffer.BufferedProgress state,
|
||||||
|
WatchProgress row,
|
||||||
|
List<WatchProgress> insertProgress,
|
||||||
|
List<WatchHistory> insertHistory,
|
||||||
|
List<WatchProgress> updateRows) {
|
||||||
|
if (row == null) {
|
||||||
|
WatchProgress created = new WatchProgress();
|
||||||
|
created.setUserId(identity.userId());
|
||||||
|
created.setDramaId(state.dramaId());
|
||||||
|
created.setEpisodeId(state.episodeId());
|
||||||
|
created.setPositionMs(state.positionMs());
|
||||||
|
created.setDurationMs(state.durationMs());
|
||||||
|
created.setFinished(state.finished() ? 1 : 0);
|
||||||
|
created.setPlayCount(1);
|
||||||
|
created.setDeviceId(identity.authenticated()
|
||||||
|
? state.deviceId()
|
||||||
|
: identity.deviceId());
|
||||||
|
created.setSource(state.source());
|
||||||
|
insertProgress.add(created);
|
||||||
|
insertHistory.add(historyOf(identity, state, created.getDeviceId()));
|
||||||
|
return;
|
||||||
|
}
|
||||||
|
boolean hidden = row.getDeleted() != null && row.getDeleted() != 0;
|
||||||
|
boolean sameEpisode = row.getEpisodeId() != null
|
||||||
|
&& row.getEpisodeId().equals(state.episodeId());
|
||||||
|
if (hidden && sameEpisode) {
|
||||||
|
row.setPlayCount((row.getPlayCount() == null ? 0 : row.getPlayCount()) + 1);
|
||||||
|
insertHistory.add(historyOf(identity, state, row.getDeviceId()));
|
||||||
|
} else if (!sameEpisode) {
|
||||||
|
// 换集:直接采纳新集与新的播放位置
|
||||||
|
row.setEpisodeId(state.episodeId());
|
||||||
|
row.setPositionMs(state.positionMs());
|
||||||
|
row.setDurationMs(state.durationMs());
|
||||||
|
row.setFinished(state.finished() ? 1 : 0);
|
||||||
|
row.setPlayCount((row.getPlayCount() == null ? 0 : row.getPlayCount()) + 1);
|
||||||
|
insertHistory.add(historyOf(identity, state, row.getDeviceId()));
|
||||||
|
} else {
|
||||||
|
row.setDurationMs(Math.max(row.getDurationMs() == null ? 0L : row.getDurationMs(),
|
||||||
|
state.durationMs()));
|
||||||
|
if (state.positionMs() >= (row.getPositionMs() == null ? 0L : row.getPositionMs())) {
|
||||||
|
row.setPositionMs(state.positionMs());
|
||||||
|
}
|
||||||
|
if (state.finished()) {
|
||||||
|
row.setFinished(1);
|
||||||
|
}
|
||||||
|
}
|
||||||
|
row.setDeviceId(identity.authenticated() ? state.deviceId() : identity.deviceId());
|
||||||
|
row.setSource(state.source());
|
||||||
|
if (hidden) {
|
||||||
|
row.setDeleted(0);
|
||||||
|
}
|
||||||
|
updateRows.add(row);
|
||||||
|
}
|
||||||
|
|
||||||
|
/** 组装一条观看流水(首次观剧/换集各记一条)。 */
|
||||||
|
private WatchHistory historyOf(InteractionIdentity identity,
|
||||||
|
WatchProgressBuffer.BufferedProgress state,
|
||||||
|
String deviceId) {
|
||||||
|
WatchHistory history = new WatchHistory();
|
||||||
|
history.setUserId(identity.userId());
|
||||||
|
history.setDramaId(state.dramaId());
|
||||||
|
history.setEpisodeId(state.episodeId());
|
||||||
|
history.setPositionMs(state.positionMs());
|
||||||
|
history.setDurationMs(state.durationMs());
|
||||||
|
history.setSource(state.source() == null ? "" : state.source());
|
||||||
|
history.setDeviceId(identity.authenticated()
|
||||||
|
? (deviceId == null ? "" : deviceId)
|
||||||
|
: identity.deviceId());
|
||||||
|
return history;
|
||||||
|
}
|
||||||
|
|
||||||
|
/** 行定位键:登录身份用 userId,匿名用 deviceId。 */
|
||||||
|
private String rowKey(Long userId, String deviceId, Long dramaId) {
|
||||||
|
return (userId != null ? "u:" + userId : "d:" + deviceId) + ":" + dramaId;
|
||||||
|
}
|
||||||
|
|
||||||
private ProgressRespVO toResp(WatchProgress progress) {
|
private ProgressRespVO toResp(WatchProgress progress) {
|
||||||
ProgressRespVO vo = new ProgressRespVO();
|
ProgressRespVO vo = new ProgressRespVO();
|
||||||
vo.setDramaId(progress.getDramaId());
|
vo.setDramaId(progress.getDramaId());
|
||||||
@@ -222,6 +507,68 @@ public class WatchProgressService {
|
|||||||
return vo;
|
return vo;
|
||||||
}
|
}
|
||||||
|
|
||||||
|
/** 以缓冲状态为主、库行 playCount 兜底构建续看响应。 */
|
||||||
|
private ProgressRespVO toResp(WatchProgressBuffer.BufferedProgress buffered, WatchProgress row) {
|
||||||
|
ProgressRespVO vo = new ProgressRespVO();
|
||||||
|
vo.setDramaId(buffered.dramaId());
|
||||||
|
vo.setEpisodeId(buffered.episodeId());
|
||||||
|
vo.setPositionMs(buffered.positionMs());
|
||||||
|
vo.setDurationMs(buffered.durationMs());
|
||||||
|
vo.setFinished(buffered.finished());
|
||||||
|
vo.setPlayCount(row == null || row.getPlayCount() == null ? 1 : row.getPlayCount());
|
||||||
|
vo.setUpdatedAt(fromMillis(buffered.ts()));
|
||||||
|
return vo;
|
||||||
|
}
|
||||||
|
|
||||||
|
/** 库行被缓冲覆盖时返回覆盖后的瞬态行;缓冲不比库行新时原样返回。 */
|
||||||
|
private WatchProgress overlayRow(WatchProgress row, WatchProgressBuffer.BufferedProgress buffered) {
|
||||||
|
if (buffered == null || row.getUpdatedAt() == null
|
||||||
|
|| buffered.ts() <= toMillis(row.getUpdatedAt())) {
|
||||||
|
return row;
|
||||||
|
}
|
||||||
|
WatchProgress overlaid = transientRow(buffered);
|
||||||
|
overlaid.setPlayCount(row.getPlayCount());
|
||||||
|
return overlaid;
|
||||||
|
}
|
||||||
|
|
||||||
|
private WatchProgress transientRow(WatchProgressBuffer.BufferedProgress buffered) {
|
||||||
|
WatchProgress row = new WatchProgress();
|
||||||
|
row.setDramaId(buffered.dramaId());
|
||||||
|
row.setEpisodeId(buffered.episodeId());
|
||||||
|
row.setPositionMs(buffered.positionMs());
|
||||||
|
row.setDurationMs(buffered.durationMs());
|
||||||
|
row.setFinished(buffered.finished() ? 1 : 0);
|
||||||
|
row.setPlayCount(1);
|
||||||
|
row.setUpdatedAt(fromMillis(buffered.ts()));
|
||||||
|
return row;
|
||||||
|
}
|
||||||
|
|
||||||
|
private long toMillis(LocalDateTime time) {
|
||||||
|
return time == null ? 0L : time.atZone(ZoneId.systemDefault()).toInstant().toEpochMilli();
|
||||||
|
}
|
||||||
|
|
||||||
|
private LocalDateTime fromMillis(long epochMillis) {
|
||||||
|
return LocalDateTime.ofInstant(Instant.ofEpochMilli(epochMillis), ZoneId.systemDefault());
|
||||||
|
}
|
||||||
|
|
||||||
|
private DramaEpisode publishedEpisode(Long episodeId) {
|
||||||
|
DramaEpisode episode = episodeCache.getIfPresent(episodeId);
|
||||||
|
if (episode == null) {
|
||||||
|
episode = episodeService.getPublished(episodeId);
|
||||||
|
episodeCache.put(episodeId, episode);
|
||||||
|
}
|
||||||
|
return episode;
|
||||||
|
}
|
||||||
|
|
||||||
|
private Drama publishedDrama(Long dramaId) {
|
||||||
|
Drama drama = dramaCache.getIfPresent(dramaId);
|
||||||
|
if (drama == null) {
|
||||||
|
drama = dramaService.getPublished(dramaId);
|
||||||
|
dramaCache.put(dramaId, drama);
|
||||||
|
}
|
||||||
|
return drama;
|
||||||
|
}
|
||||||
|
|
||||||
private List<ProgressRespVO> enrichDisplay(List<WatchProgress> records) {
|
private List<ProgressRespVO> enrichDisplay(List<WatchProgress> records) {
|
||||||
if (records.isEmpty()) {
|
if (records.isEmpty()) {
|
||||||
return List.of();
|
return List.of();
|
||||||
|
|||||||
Reference in new issue
Block a user