-- =====================================================================
-- 用户拉活-曝光-拉回分析表 (recommend_distribution_data_total)
-- 维度: 用户拉活量分层 × 进入小时 × 进入场景 × 进入内容品类 × 推荐内容品类 × 内容id
-- 粒度: GROUP BY CUBE 全维度组合 + SUM 汇总
-- =====================================================================

-- DROP TABLE IF EXISTS loghubods.recommend_distribution_data_total;
CREATE TABLE IF NOT EXISTS loghubods.recommend_distribution_data_total (
    `用户拉活量分层`             STRING    COMMENT '用户拉活量分层（R0&新用户/R1-50等，汇总为SUM）',
    `进入小时`                   STRING    COMMENT '进入小时（1-4/5-8等，汇总为SUM）',
    `进入场景`                   STRING    COMMENT '进入场景（业务场景描述，汇总为SUM）',
    `进入内容品类`               STRING    COMMENT '进入内容品类（merge_leve2维度，汇总为SUM）',
    `推荐内容品类`               STRING    COMMENT '推荐内容品类（merge_leve2维度，汇总为SUM）',
    `内容id`                     STRING    COMMENT '内容id（videoid，其他为兜底，汇总为SUM）',

    -- ===== 基础流量指标 =====
    `访问人数`                   BIGINT    COMMENT '去重访问人数（machinecode维度）',
    `曝光人数`                   BIGINT    COMMENT '去重曝光人数（mid维度）',
    `曝光人数比访问人数`         DOUBLE    COMMENT '曝光人数/访问人数 比值',
    `曝光次数`                   BIGINT    COMMENT '曝光总次数（mid计数）',
    `曝光次数人均`               DOUBLE    COMMENT '曝光次数/去重曝光人数 人均曝光次数',
    `视频个数`                   BIGINT    COMMENT '去重曝光视频个数（vid维度）',
    `单视频曝光次数`             DOUBLE    COMMENT '曝光次数/去重视频个数 单视频平均曝光次数',

    -- ===== 全链路拉回 =====
    `ALL拉回n层`                 BIGINT    COMMENT '全量拉回n层人数（多来源拉回人数求和）',
    `ALL拉回n层比曝光次数`       DOUBLE    COMMENT '全量拉回n层人数/曝光次数 比值，保留6位小数',

    -- ===== 原生拉回 & rovn =====
    `return_n_uv_noself`         BIGINT    COMMENT '原生n层拉回人数（无自返）',
    `rovn`                       DOUBLE    COMMENT '原生n层拉回人数/曝光次数 比值，保留6位小数',
    `rovn_pred`                  DOUBLE    COMMENT 'rovn预估值（str_pred*rosn_pred平均值），保留6位小数',
    `rovn_copc`                  DOUBLE    COMMENT 'rovn实际/rovn预估 比值，保留4位小数',

    -- ===== STR 指标 =====
    `str_real`                   DOUBLE    COMMENT 'str实际值（is_return_noself求和/曝光次数），保留6位小数',
    `str_pred`                   DOUBLE    COMMENT 'str预估值（str_pred求和/曝光次数），保留6位小数',
    `str_copc`                   DOUBLE    COMMENT 'str实际/str预估 比值，保留4位小数',
    `str_MAE`                    DOUBLE    COMMENT 'str预估与实际的平均绝对误差，保留6位小数',
    `STR_VAR`                    DOUBLE    COMMENT 'str预估与实际差值的方差，保留6位小数',
    `strauc`                     DOUBLE    COMMENT 'str AUC，保留6位小数',
    `str多维加权copc`            DOUBLE    COMMENT 'str多维加权copc，保留6位小数',

    -- ===== ROSN 指标 =====
    `rosn_real`                  DOUBLE    COMMENT 'rosn实际值（原生n层拉回人数/is_return_noself求和），保留6位小数',
    `rosn_pred`                  DOUBLE    COMMENT 'rosn预估值（rosn_pred求和/曝光次数），保留6位小数',
    `rosn_copc`                  DOUBLE    COMMENT 'rosn实际/rosn预估 比值，保留4位小数',
    `rosn_实际预估diff绝对距离`  DOUBLE    COMMENT '拉回时rosn预估与实际的平均绝对距离，保留6位小数',
    `rosn_实际预估高低估分布比例` DOUBLE   COMMENT '拉回时rosn预估与实际差值的方差，保留6位小数',

    -- ===== B链 (分享→点击) =====
    `Buv1层拉回人数`             BIGINT    COMMENT 'B端uv1层拉回人数（is_return_noself求和）',
    `rov0`                       DOUBLE    COMMENT 'B端uv1层拉回人数/曝光次数 比值，保留6位小数',
    `rov0预估`                   BIGINT    COMMENT 'rov0预估值（固定为0）',
    `rov0copc`                   BIGINT    COMMENT 'rov0copc值（固定为0）',
    `ros0`                       DOUBLE    COMMENT 'ros0实际值（B端uv1层拉回人数/分享次数），保留6位小数',
    `ros0预估`                   BIGINT    COMMENT 'ros0预估值（固定为0）',
    `ros0copc`                   BIGINT    COMMENT 'ros0copc值（固定为0）',
    `Bnuvn层拉回人数`            BIGINT    COMMENT 'B端nuvn层拉回人数（原生n层拉回人数一致）',
    `rorn_b`                     DOUBLE    COMMENT 'B端n层拉回率（Bnuvn/uv1层拉回人数），保留6位小数',
    `ror1单层_b`                 DOUBLE    COMMENT 'B端1层拉回率（b1/uv1层拉回人数），保留6位小数',
    `ror2单层_b`                 DOUBLE    COMMENT 'B端2层拉回率（b2/b1），保留6位小数',

    -- ===== B链 T+1 =====
    `Bnuvn层拉回人数_t1`         DOUBLE    COMMENT 'T1维度B端nuvn层拉回人数，保留6位小数',
    `rorn_b_t1`                  DOUBLE    COMMENT 'T1维度B端n层拉回率，保留6位小数',
    `ror1单层_b_t1`              DOUBLE    COMMENT 'T1维度B端1层拉回率，保留6位小数',
    `ror2单层_b_t1`              DOUBLE    COMMENT 'T1维度B端2层拉回率，保留6位小数',

    -- ===== C链 (二次分享→点击) =====
    `cn`                         BIGINT    COMMENT 'C端拉回n层人数',
    `rorn_c`                     DOUBLE    COMMENT 'C端n层拉回率（cn/原生n层拉回人数）',
    `ror1_c`                     DOUBLE    COMMENT 'C端1层拉回率（c/原生n层拉回人数）',
    `vor单层_c`                  DOUBLE    COMMENT 'C端单层视频访问率（cviews/原生n层拉回人数）',
    `vor单层预估`                BIGINT    COMMENT 'C端单层视频访问率预估（固定为0）',
    `vor单层copc`                BIGINT    COMMENT 'C端单层视频访问率copc（固定为0）',

    -- ===== D链 (session内后续曝光传播) =====
    `a`                          BIGINT    COMMENT 'D端去重访问人数（machinecode维度）',
    `dn`                         BIGINT    COMMENT 'D端拉回n层人数',
    `rorn_d`                     DOUBLE    COMMENT 'D端n层拉回率（dn/D端去重访问人数），保留6位小数',
    `ror1_d`                     DOUBLE    COMMENT 'D端1层拉回率（d1/D端去重访问人数），保留6位小数',
    `vor_d`                      DOUBLE    COMMENT 'D端视频访问率（g.mid计数/D端去重访问人数）'
)
COMMENT '用户拉活-曝光-拉回分析表'
PARTITIONED BY (
    dt STRING COMMENT '统计日期，格式yyyyMMdd'
);


-- =====================================================================
-- CTE: 基础样本提取 + 特征工程
-- =====================================================================

WITH
-- [1] 原始样本: 从推荐算法样本表取数，解析 scoresMap
t_raw AS (
    SELECT  *
            ,REPLACE(GET_JSON_OBJECT(extend_alg, '$.scoresMap'), "\\", "") AS scoresmap
            ,CASE
                WHEN page IN ("回流后沉浸页&内页feed", "详情后沉浸页", "首页feed", "详情页") THEN "推荐"
                WHEN page IN ("回流页", "其他")                                               THEN "非推荐"
                ELSE "其他"
             END AS page_type
    FROM    loghubods.dwd_recsys_alg_sample_all_20250212
    WHERE   dt = '${bizdate}'
    -- AND     apptype IN ("0","4")
    AND     abcode IN ("ab0","ab1","ab2","ab3","ab4","ab5","ab6","ab7","ab8","ab9")
    AND     abcode NOT IN ("ab100")
    AND     extend_alg IS NOT NULL
    AND     GET_JSON_OBJECT(extend_alg, '$.scoresMap') IS NOT NULL
)

-- [2] 过滤: 只保留推荐页面
,t_filtered AS (
    SELECT  *
    FROM    t_raw
    WHERE   page_type = "推荐"
)

-- [3] 特征提取: 维度映射 + 模型分数解析
,t_base AS (
    SELECT  dt
            ,apptype
            ,CASE
                WHEN apptype IN ("4") AND abcode IN ("ab0","ab1") THEN "实验组-先验地域降权"
                WHEN apptype IN ("4") AND abcode IN ("ab6","ab7") THEN "实验组-str+校准&ros-统计量"
                WHEN apptype IN ("4") AND abcode IN ("ab8","ab9") THEN "实验组-str+校准"
                WHEN apptype IN ("4") AND abcode IN ("ab2","ab3") THEN "对照组"
                WHEN apptype IN ("4") AND abcode IN ("ab4","ab5") THEN "ab4-5"
                ELSE "其他"
             END AS abcode
            ,page_type AS page
            ,mid
            ,vid
            ,is_share
            ,share_cnt
            ,is_return_1
            ,is_return_n
            ,is_return_noself
            ,return_1_uv
            ,return_n_uv
            ,return_n_uv_noself
            ,new_exposure_cnt
            ,flowpool
            ,scoresmap
            ,subsessionid
            ,CAST(GET_JSON_OBJECT(scoresmap, '$.fmRov') AS DOUBLE)                            AS str_pred
            ,1.22 * POW(CAST(GET_JSON_OBJECT(scoresmap, '$.NorXGBScore') AS DOUBLE), 1.15)    AS rosn_pred
            ,CAST(GET_JSON_OBJECT(scoresmap, '$.hasReturnRovScore') AS DOUBLE)                 AS rosn_stat
            ,GET_JSON_OBJECT(v1_feature, '$.title')                                            AS vid_title
    FROM    t_filtered
)


-- =====================================================================
-- 主查询: INSERT OVERWRITE → 多维度 CUBE 聚合
-- =====================================================================

-- SELECT * FROM loghubods.recommend_distribution_data_total WHERE dt = 20260204 ORDER BY 访问人数 DESC

INSERT OVERWRITE TABLE loghubods.recommend_distribution_data_total PARTITION (dt = '${bizdate}')
SELECT
        -- ==================== 维度列 ====================

        -- 用户拉活量分层
        CASE WHEN grouping(
                    COALESCE(
                        CASE
                            WHEN e.type IS NULL OR e.type = 'R_0'                       THEN 'R0&新用户'
                            WHEN e.type IN ('R_1','R_2_10','R_10_50')                    THEN 'R1-50'
                            WHEN e.type IN ('R_50_100','R_100_180','R_180_330')           THEN 'R_180_330'
                            ELSE e.type
                        END
                    , '-')
                 ) = 1
             THEN 'SUM'
             ELSE NVL(
                    COALESCE(
                        CASE
                            WHEN e.type IS NULL OR e.type = 'R_0'                       THEN 'R0&新用户'
                            WHEN e.type IN ('R_1','R_2_10','R_10_50')                    THEN 'R1-50'
                            WHEN e.type IN ('R_50_100','R_100_180','R_180_330')           THEN 'R_180_330'
                            ELSE e.type
                        END
                    , '-')
                 , 'SUM')
        END                                                                     AS 用户拉活量分层

        -- 进入小时
        ,CASE WHEN grouping(
                    COALESCE(
                        CASE
                            WHEN in_hour >= 1  AND in_hour <= 4  THEN '1-4'
                            WHEN in_hour >= 5  AND in_hour <= 8  THEN '5-8'
                            WHEN in_hour >= 9  AND in_hour <= 12 THEN '9-12'
                            WHEN in_hour >= 13 AND in_hour <= 16 THEN '13-16'
                            WHEN in_hour >= 17 AND in_hour <= 20 THEN '17-20'
                            WHEN in_hour >= 21 AND in_hour <= 24 THEN '21-24'
                            ELSE '-'
                        END
                    , '-')
                 ) = 1
              THEN 'SUM'
              ELSE NVL(
                    COALESCE(
                        CASE
                            WHEN in_hour >= 1  AND in_hour <= 4  THEN '1-4'
                            WHEN in_hour >= 5  AND in_hour <= 8  THEN '5-8'
                            WHEN in_hour >= 9  AND in_hour <= 12 THEN '9-12'
                            WHEN in_hour >= 13 AND in_hour <= 16 THEN '13-16'
                            WHEN in_hour >= 17 AND in_hour <= 20 THEN '17-20'
                            WHEN in_hour >= 21 AND in_hour <= 24 THEN '21-24'
                            ELSE '-'
                        END
                    , '-')
                 , 'SUM')
        END                                                                     AS 进入小时

        -- 进入场景
        ,CASE WHEN grouping(CASE WHEN f.scene_id IS NOT NULL THEN f.scene_desc ELSE '其他' END) = 1
              THEN 'SUM'
              ELSE NVL(CASE WHEN f.scene_id IS NOT NULL THEN f.scene_desc ELSE '其他' END, 'SUM')
        END                                                                     AS 进入场景

        -- 进入内容品类
        ,CASE WHEN grouping(CASE WHEN m.merge_leve2 IS NOT NULL THEN d.merge_leve2 ELSE '其他' END) = 1
              THEN 'SUM'
              ELSE NVL(CASE WHEN m.merge_leve2 IS NOT NULL THEN d.merge_leve2 ELSE '其他' END, 'SUM')
        END                                                                     AS 进入内容品类

        -- 推荐内容品类
        ,CASE WHEN grouping(CASE WHEN l.merge_leve2 IS NOT NULL THEN h.merge_leve2 ELSE '其他' END) = 1
              THEN 'SUM'
              ELSE NVL(CASE WHEN l.merge_leve2 IS NOT NULL THEN h.merge_leve2 ELSE '其他' END, 'SUM')
        END                                                                     AS 推荐内容品类

        -- 内容id
        ,CASE WHEN grouping(COALESCE(CASE WHEN i.merge_leve2 IS NOT NULL THEN i.videoid ELSE '其他' END, '-')) = 1
              THEN 'SUM'
              ELSE NVL(COALESCE(CASE WHEN i.merge_leve2 IS NOT NULL THEN i.videoid ELSE '其他' END, '-'), 'SUM')
        END                                                                     AS 内容id

        -- ==================== 基础流量指标 ====================
        ,COUNT(DISTINCT a.machinecode)                                          AS 访问人数
        ,COUNT(DISTINCT j.mid)                                                  AS 曝光人数
        ,COUNT(DISTINCT j.mid) / COUNT(DISTINCT a.machinecode)                  AS 曝光人数比访问人数
        ,COUNT(j.mid)                                                           AS 曝光次数
        ,COUNT(j.mid) / COUNT(DISTINCT j.mid)                                   AS 曝光次数人均
        ,COUNT(DISTINCT j.vid)                                                  AS 视频个数
        ,COUNT(j.mid) / COUNT(DISTINCT j.vid)                                   AS 单视频曝光次数

        -- ==================== 全链路拉回 ====================
        ,SUM(return_n_uv_noself) + SUM(cc.cn) + SUM(dd.dn)                     AS ALL拉回n层
        ,ROUND(COALESCE(
            (SUM(return_n_uv_noself) + SUM(cc.cn) + SUM(dd.dn)) / COUNT(j.mid)
        , 0), 6)                                                                AS ALL拉回n层比曝光次数

        -- ==================== 原生拉回 & rovn ====================
        ,SUM(return_n_uv_noself)                                                AS return_n_uv_noself
        ,ROUND(SUM(return_n_uv_noself) / COUNT(j.mid), 6)                      AS rovn
        ,ROUND(AVG(str_pred * rosn_pred), 6)                                    AS rovn_pred
        ,ROUND(
            (SUM(return_n_uv_noself) / COUNT(j.mid))
            / NULLIF(AVG(str_pred * rosn_pred), 0)
        , 4)                                                                    AS rovn_copc

        -- ==================== STR 指标 ====================
        ,ROUND(COALESCE(SUM(is_return_noself) / COUNT(j.mid), 0), 6)           AS str_real
        ,ROUND(COALESCE(SUM(str_pred)         / COUNT(j.mid), 0), 6)           AS str_pred
        ,ROUND(
            (SUM(is_return_noself) / COUNT(j.mid))
            / NULLIF(SUM(str_pred) / COUNT(j.mid), 0)
        , 4)                                                                    AS str_copc
        ,ROUND(AVG(ABS(str_pred - is_return_noself)), 6)                       AS str_MAE
        ,ROUND(VARIANCE(str_pred - is_return_noself), 6)                       AS STR_VAR
        ,0                                                                      AS strauc
        ,0                                                                      AS str多维加权copc

        -- ==================== ROSN 指标 ====================
        ,ROUND(COALESCE(
            SUM(return_n_uv_noself) / NULLIF(SUM(is_return_noself), 0)
        , 0), 6)                                                                AS rosn_real
        ,ROUND(COALESCE(SUM(rosn_pred) / COUNT(j.mid), 0), 6)                 AS rosn_pred
        ,ROUND(
            (SUM(return_n_uv_noself) / NULLIF(SUM(is_return_noself), 0))
            / NULLIF(SUM(rosn_pred) / COUNT(1), 0)
        , 4)                                                                    AS rosn_copc
        ,ROUND(AVG(
            CASE WHEN is_return_noself = 1
                 THEN ABS(rosn_pred - return_n_uv_noself)
            END
        ), 6)                                                                   AS rosn_实际预估diff绝对距离
        ,ROUND(VARIANCE(
            CASE WHEN is_return_noself = 1
                 THEN rosn_pred - return_n_uv_noself
            END
        ), 6)                                                                   AS rosn_实际预估高低估分布比例

        -- ==================== B链: 分享→点击 ====================
        ,SUM(is_return_noself)                                                  AS Buv1层拉回人数
        ,ROUND(SUM(is_return_noself) / COUNT(j.mid), 6)                        AS rov0
        ,0                                                                      AS rov0预估
        ,0                                                                      AS rov0copc
        ,ROUND(COALESCE(
            SUM(is_return_noself) / NULLIF(SUM(share_cnt), 0)
        , 0), 6)                                                                AS ros0
        ,0                                                                      AS ros0预估
        ,0                                                                      AS ros0copc
        ,SUM(return_n_uv_noself)                                                AS Bnuvn层拉回人数
        ,ROUND(COALESCE(SUM(return_n_uv_noself) / SUM(is_return_noself), 0), 6) AS rorn_b
        ,ROUND(COALESCE(SUM(k.b1)               / SUM(is_return_noself), 0), 6) AS ror1单层_b
        ,ROUND(COALESCE(SUM(k.b2)               / SUM(k.b1),             0), 6) AS ror2单层_b

        -- ==================== B链 T+1 ====================
        ,ROUND(COALESCE(SUM(k1.bn), 0), 6)                                     AS Bnuvn层拉回人数_t1
        ,ROUND(COALESCE(SUM(k1.bn) / SUM(k1.b),  0), 6)                       AS rorn_b_t1
        ,ROUND(COALESCE(SUM(k1.b1) / SUM(k1.b),  0), 6)                       AS ror1单层_b_t1
        ,ROUND(COALESCE(SUM(k1.b2) / SUM(k1.b1), 0), 6)                       AS ror2单层_b_t1

        -- ==================== C链: 二次分享 ====================
        ,SUM(cc.cn)                                                             AS cn
        ,SUM(cc.cn)     / SUM(return_n_uv_noself)                              AS rorn_c
        ,SUM(cc.c)      / SUM(return_n_uv_noself)                              AS ror1_c
        ,SUM(cc.cviews) / SUM(return_n_uv_noself)                              AS vor单层_c
        ,0                                                                      AS vor单层预估
        ,0                                                                      AS vor单层copc

        -- ==================== D链: session内后续曝光传播 ====================
        ,COUNT(DISTINCT b.machinecode)                                          AS a
        ,SUM(dd.dn)                                                             AS dn
        ,ROUND(COALESCE(SUM(dd.dn) / COUNT(DISTINCT b.machinecode), 0), 6)    AS rorn_d
        ,ROUND(COALESCE(SUM(dd.d1) / COUNT(DISTINCT b.machinecode), 0), 6)    AS ror1_d
        ,COUNT(g.mid) / COUNT(DISTINCT b.machinecode)                           AS vor_d


-- =====================================================================
-- FROM + JOINs
-- =====================================================================

FROM    (
            -- [a] 用户活跃日志 + 进入小时
            SELECT  *
                    ,TO_CHAR(FROM_UNIXTIME(a.clienttimestamp / 1000), 'HH') + 1 AS in_hour
            FROM    loghubods.useractive_log a
            WHERE   a.dt = '${bizdate}'
        ) a

-- [b] 分享点击日志 (topic=click)
LEFT JOIN (
            SELECT  DISTINCT
                    machinecode
                    ,sessionid
                    ,subsessionid
                    ,pagesource
                    ,topic
                    ,shareid
                    ,clickobjectid
                    ,shareobjectid
                    ,clientip
                    ,CASE
                        WHEN topic = 'click' THEN clickobjectid
                        WHEN topic = 'share' THEN shareobjectid
                     END AS videoid
                    ,sharetitleid
                    ,sharetitle
                    ,shareimageurl
                    ,rootsharemid
                    ,clienttimestamp
                    ,FROM_UNIXTIME(clienttimestamp / 1000)                                         AS click_time
                    ,GET_JSON_OBJECT(videocdm.Ip2RegionAnalyse(clientip), "$.province")            AS click_province
                    ,GET_JSON_OBJECT(videocdm.Ip2RegionAnalyse(clientip), "$.city")                AS click_city
                    ,TO_CHAR(FROM_UNIXTIME(clienttimestamp / 1000), 'HH') + 1                     AS click_hour
            FROM    loghubods.user_share_log
            WHERE   dt = '${bizdate}'
            AND     topic = 'click'
        ) b
ON      a.machinecode  = b.machinecode
AND     a.subsessionid = b.subsessionid

-- [c] 视频元信息
LEFT JOIN videoods.wx_video c
ON      b.videoid = c.id

-- [d] 点击视频品类标签
LEFT JOIN loghubods.video_merge_tag d
ON      b.videoid = d.videoid

-- [e] 用户拉活量分层 (R0/R1-50/R_180_330/...)
LEFT JOIN (
            SELECT  DISTINCT type, openid
            FROM    loghubods.mid_share_return_people_1year
            WHERE   dt = '${bizdate-1}'
            AND     type IS NOT NULL
            AND     type != 'S_ALL'
            AND     type NOT REGEXP 'R50'
        ) e
ON      SUBSTRING_INDEX(a.machinecode, 'weixin_openid_', -1) = e.openid

-- [f] TOP5 进入场景
LEFT JOIN (
            SELECT  a.scene_id
                    ,a.scene_desc
                    ,COUNT(DISTINCT b.machinecode) AS cnt
            FROM    loghubods.wechat_miniprogram_scene_simple a
            LEFT JOIN loghubods.useractive_log b
            ON      a.scene_id = b.sencetype
            AND     b.dt = '${bizdate}'
            GROUP BY a.scene_id, a.scene_desc
            ORDER BY cnt DESC
            LIMIT   5
        ) f
ON      a.sencetype = f.scene_id

-- [g] 推荐页视频播放
LEFT JOIN (
            SELECT  DISTINCT mid, subsessionid, videoid
            FROM    loghubods.video_action_log_rp
            WHERE   dt = '${bizdate}'
            AND     businesstype = 'videoView'
            AND     pagesource REGEXP 'category$|recommend$|-pages/user-videos-detail$'
        ) g
ON      b.machinecode  = g.mid
AND     b.subsessionid = g.subsessionid

-- [h] 推荐视频品类标签
LEFT JOIN loghubods.video_merge_tag h
ON      g.videoid = h.videoid

-- [i] 热门视频 (按品类 TOP1, 曝光>10w)
LEFT JOIN (
            SELECT  merge_leve2, videoid
            FROM    (
                        SELECT  b.merge_leve2
                                ,a.videoid
                                ,COUNT(1)                                                        AS view
                                ,ROW_NUMBER() OVER (PARTITION BY b.merge_leve2 ORDER BY COUNT(1) DESC) AS rank
                        FROM    loghubods.video_action_log_rp a
                        LEFT JOIN loghubods.video_merge_tag b
                        ON      a.videoid = b.videoid
                        WHERE   dt = '${bizdate}'
                        AND     businesstype = 'videoView'
                        AND     pagesource REGEXP 'category$|recommend$|-pages/user-videos-detail$'
                        GROUP BY b.merge_leve2, a.videoid
                        HAVING  view > 100000
                    )
            WHERE   rank <= 1
        ) i
ON      g.videoid = i.videoid

-- [j] 曝光样本 (t_base CTE)
LEFT JOIN t_base j
ON      g.mid          = j.mid
AND     g.subsessionid = j.subsessionid
AND     g.videoid      = j.vid

-- [k] B链: 当天分享→点击裂变 (sharedepth 1~4)
LEFT JOIN (
            SELECT  a.machinecode                                                               AS mid
                    ,a.subsessionid
                    ,a.videoid                                                                  AS vid
                    ,COUNT(DISTINCT CASE WHEN a.machinecode <> b.machinecode                              THEN b.machinecode END) AS bn
                    ,COUNT(DISTINCT CASE WHEN b.sharedepth = 1 AND a.machinecode <> b.machinecode         THEN b.machinecode END) AS b
                    ,COUNT(DISTINCT CASE WHEN b.sharedepth = 2 AND a.machinecode <> b.machinecode         THEN b.machinecode END) AS b1
                    ,COUNT(DISTINCT CASE WHEN b.sharedepth = 3 AND a.machinecode <> b.machinecode         THEN b.machinecode END) AS b2
                    ,COUNT(DISTINCT CASE WHEN b.sharedepth = 4 AND a.machinecode <> b.machinecode         THEN b.machinecode END) AS b3
            FROM    (
                        SELECT  DISTINCT machinecode, shareobjectid AS videoid, recomTraceId,
                                subsessionid, sharedepth, shareid
                        FROM    loghubods.user_share_log
                        WHERE   dt = '${bizdate}'
                        AND     topic = 'share'
                        AND     pagesource REGEXP 'category$|recommend$|-pages/user-videos-detail$'
                    ) a
            LEFT JOIN (
                        SELECT  DISTINCT machinecode, clickobjectid, recomTraceId,
                                subsessionid, sharedepth, rootshareid
                        FROM    loghubods.user_share_log
                        WHERE   dt = '${bizdate}'
                        AND     topic = 'click'
                    ) b
            ON      a.shareid = b.rootshareid
            GROUP BY a.machinecode, a.subsessionid, a.videoid
        ) k
ON      g.mid          = k.mid
AND     g.subsessionid = k.subsessionid
AND     g.videoid      = k.vid

-- [k1] B链 T+1: 跨天分享→点击裂变
LEFT JOIN (
            SELECT  a.machinecode                                                               AS mid
                    ,a.subsessionid
                    ,a.videoid                                                                  AS vid
                    ,COUNT(DISTINCT CASE WHEN a.machinecode <> b.machinecode                              THEN b.machinecode END) AS bn
                    ,COUNT(DISTINCT CASE WHEN b.sharedepth = 1 AND a.machinecode <> b.machinecode         THEN b.machinecode END) AS b
                    ,COUNT(DISTINCT CASE WHEN b.sharedepth = 2 AND a.machinecode <> b.machinecode         THEN b.machinecode END) AS b1
                    ,COUNT(DISTINCT CASE WHEN b.sharedepth = 3 AND a.machinecode <> b.machinecode         THEN b.machinecode END) AS b2
                    ,COUNT(DISTINCT CASE WHEN b.sharedepth = 4 AND a.machinecode <> b.machinecode         THEN b.machinecode END) AS b3
            FROM    (
                        SELECT  DISTINCT machinecode, shareobjectid AS videoid, recomTraceId,
                                subsessionid, sharedepth, shareid
                        FROM    loghubods.user_share_log
                        WHERE   dt = '${bizdate}'
                        AND     topic = 'share'
                        AND     pagesource REGEXP 'category$|recommend$|-pages/user-videos-detail$'
                    ) a
            LEFT JOIN (
                        SELECT  DISTINCT machinecode, clickobjectid, recomTraceId,
                                subsessionid, sharedepth, rootshareid
                        FROM    loghubods.user_share_log
                        WHERE   dt >= '${bizdate}'
                        AND     dt <= '${bizdate+1}'       -- T+1 跨天
                        AND     topic = 'click'
                    ) b
            ON      a.shareid = b.rootshareid
            GROUP BY a.machinecode, a.subsessionid, a.videoid
        ) k1
ON      g.mid          = k1.mid
AND     g.subsessionid = k1.subsessionid
AND     g.videoid      = k1.vid

-- [l] TOP10 推荐品类 (按播放量)
LEFT JOIN (
            SELECT  b.merge_leve2
                    ,COUNT(1) AS view
            FROM    loghubods.video_action_log_rp a
            LEFT JOIN loghubods.video_merge_tag b
            ON      a.videoid = b.videoid
            WHERE   dt = '${bizdate}'
            AND     businesstype = 'videoView'
            AND     pagesource REGEXP 'category$|recommend$|-pages/user-videos-detail$'
            AND     b.merge_leve2 IS NOT NULL
            GROUP BY b.merge_leve2
            ORDER BY view DESC
            LIMIT   10
        ) l
ON      h.merge_leve2 = l.merge_leve2

-- [m] TOP1 点击品类 (按点击人数)
LEFT JOIN (
            SELECT  b.merge_leve2
                    ,COUNT(DISTINCT machinecode) AS click
            FROM    loghubods.user_share_log a
            LEFT JOIN loghubods.video_merge_tag b
            ON      a.clickobjectid = b.videoid
            WHERE   dt = '${bizdate}'
            AND     topic = 'click'
            AND     b.merge_leve2 IS NOT NULL
            GROUP BY b.merge_leve2
            ORDER BY click DESC
            LIMIT   1
        ) m
ON      d.merge_leve2 = m.merge_leve2

-- [cc] C链: 二次分享 (分享→点击→再分享→再点击 + 视频播放)
LEFT JOIN (
            SELECT  a.machinecode                                                               AS mid
                    ,a.subsessionid
                    ,a.videoid                                                                  AS vid
                    ,COUNT(DISTINCT CASE WHEN b1.machinecode <> b2.machinecode THEN b2.machinecode END)  AS cn
                    ,COUNT(DISTINCT
                        CASE WHEN b2.sharedepth = 1 AND b1.machinecode <> b2.machinecode
                             THEN b2.machinecode
                        END
                    )                                                                           AS c
                    ,COUNT(c.mid)                                                               AS cviews
            FROM    (
                        -- 一次分享
                        SELECT  DISTINCT machinecode, shareobjectid AS videoid, recomTraceId,
                                subsessionid, sharedepth, shareid
                        FROM    loghubods.user_share_log
                        WHERE   dt = '${bizdate}'
                        AND     topic = 'share'
                        AND     pagesource REGEXP 'category$|recommend$|-pages/user-videos-detail$'
                    ) a
            LEFT JOIN (
                        -- 一次点击
                        SELECT  DISTINCT machinecode, clickobjectid, recomTraceId,
                                subsessionid, sharedepth, rootshareid
                        FROM    loghubods.user_share_log
                        WHERE   dt = '${bizdate}'
                        AND     topic = 'click'
                    ) b
            ON      a.shareid = b.rootshareid
            LEFT JOIN (
                        -- 二次分享 (点击者再分享)
                        SELECT  DISTINCT machinecode, shareobjectid, recomTraceId,
                                subsessionid, sharedepth, shareid
                        FROM    loghubods.user_share_log
                        WHERE   dt = '${bizdate}'
                        AND     topic = 'share'
                        AND     pagesource REGEXP 'category$|recommend$|-pages/user-videos-detail$'
                    ) b1
            ON      b.machinecode  = b1.machinecode
            AND     b.subsessionid = b1.subsessionid
            LEFT JOIN (
                        -- 二次点击
                        SELECT  DISTINCT machinecode, clickobjectid, recomTraceId,
                                subsessionid, sharedepth, shareid, rootshareid
                        FROM    loghubods.user_share_log
                        WHERE   dt = '${bizdate}'
                        AND     topic = 'click'
                    ) b2
            ON      b1.shareid = b2.rootshareid
            LEFT JOIN (
                        -- 二次点击者的视频播放
                        SELECT  DISTINCT mid, subsessionid, videoid
                        FROM    loghubods.video_action_log_rp
                        WHERE   dt = '${bizdate}'
                        AND     businesstype = 'videoView'
                        AND     pagesource REGEXP 'category$|recommend$|-pages/user-videos-detail$'
                    ) c
            ON      b2.machinecode = c.mid
            AND     b2.subsessionid = c.subsessionid
            GROUP BY a.machinecode, a.subsessionid, a.videoid
        ) cc
ON      g.mid          = cc.mid
AND     g.subsessionid = cc.subsessionid
AND     g.videoid      = cc.vid

-- [dd] D链: session内后续曝光传播 (窗口函数累计后续拉回)
LEFT JOIN (
            SELECT  *
                    ,COALESCE(
                        SUM(回流)  OVER (PARTITION BY mid, subsessionid ORDER BY rn ROWS BETWEEN 1 FOLLOWING AND UNBOUNDED FOLLOWING)
                    , 0) AS dn
                    ,COALESCE(
                        SUM(回流1) OVER (PARTITION BY mid, subsessionid ORDER BY rn ROWS BETWEEN 1 FOLLOWING AND UNBOUNDED FOLLOWING)
                    , 0) AS d1
            FROM    (
                        SELECT  a.mid                                                           AS mid
                                ,a.subsessionid
                                ,a.videoid                                                      AS vid
                                ,COUNT(DISTINCT b.shareid)                                      AS 分享次数
                                ,COUNT(DISTINCT
                                    CASE WHEN c.machinecode <> b.machinecode
                                         THEN c.machinecode
                                    END
                                )                                                               AS 回流
                                ,COUNT(DISTINCT
                                    CASE WHEN c.machinecode <> b.machinecode AND c.sharedepth = 1
                                         THEN c.machinecode
                                    END
                                )                                                               AS 回流1
                                ,ROW_NUMBER() OVER (PARTITION BY a.subsessionid ORDER BY a.logtimestamp DESC) AS rn
                        FROM    (
                                    SELECT  DISTINCT mid, subsessionid, videoid, logtimestamp
                                    FROM    loghubods.video_action_log_rp
                                    WHERE   dt = '${bizdate}'
                                    AND     businesstype = 'videoView'
                                    AND     pagesource REGEXP 'category$|recommend$|-pages/user-videos-detail$'
                                ) a
                        LEFT JOIN (
                                    SELECT  DISTINCT machinecode, shareobjectid AS videoid, recomTraceId,
                                            subsessionid, sharedepth, shareid, clienttimestamp
                                    FROM    loghubods.user_share_log
                                    WHERE   dt = '${bizdate}'
                                    AND     topic = 'share'
                                    AND     pagesource REGEXP 'category$|recommend$|-pages/user-videos-detail$'
                                ) b
                        ON      a.mid          = b.machinecode
                        AND     a.subsessionid = b.subsessionid
                        AND     a.videoid      = b.videoid
                        LEFT JOIN (
                                    SELECT  DISTINCT machinecode, clickobjectid, recomTraceId,
                                            subsessionid, sharedepth, rootshareid
                                    FROM    loghubods.user_share_log
                                    WHERE   dt = '${bizdate}'
                                    AND     topic = 'click'
                                ) c
                        ON      b.shareid = c.rootshareid
                        GROUP BY a.mid, a.subsessionid, a.videoid, a.logtimestamp
                    )
        ) dd
ON      g.mid          = dd.mid
AND     g.subsessionid = dd.subsessionid
AND     g.videoid      = dd.vid


-- =====================================================================
-- GROUP BY CUBE: 全维度组合聚合
-- =====================================================================

GROUP BY CUBE(
            -- 用户拉活量分层
            COALESCE(
                CASE
                    WHEN e.type IS NULL OR e.type = 'R_0'                       THEN 'R0&新用户'
                    WHEN e.type IN ('R_1','R_2_10','R_10_50')                    THEN 'R1-50'
                    WHEN e.type IN ('R_50_100','R_100_180','R_180_330')           THEN 'R_180_330'
                    ELSE e.type
                END
            , '-')

            -- 进入小时
            ,COALESCE(
                CASE
                    WHEN in_hour >= 1  AND in_hour <= 4  THEN '1-4'
                    WHEN in_hour >= 5  AND in_hour <= 8  THEN '5-8'
                    WHEN in_hour >= 9  AND in_hour <= 12 THEN '9-12'
                    WHEN in_hour >= 13 AND in_hour <= 16 THEN '13-16'
                    WHEN in_hour >= 17 AND in_hour <= 20 THEN '17-20'
                    WHEN in_hour >= 21 AND in_hour <= 24 THEN '21-24'
                    ELSE '-'
                END
            , '-')

            -- 进入场景
            ,CASE WHEN f.scene_id IS NOT NULL THEN f.scene_desc ELSE '其他' END

            -- 进入内容品类
            ,CASE WHEN m.merge_leve2 IS NOT NULL THEN d.merge_leve2 ELSE '其他' END

            -- 推荐内容品类
            ,CASE WHEN l.merge_leve2 IS NOT NULL THEN h.merge_leve2 ELSE '其他' END

            -- 内容id
            ,COALESCE(CASE WHEN i.merge_leve2 IS NOT NULL THEN i.videoid ELSE '其他' END, '-')
        )

ORDER BY 访问人数 DESC
;