--存入每天数据

SELECT
    t1.partition_date as day_id,
    t1.device_os_type as device_os_type,
    t1.active_type as active_type,
    t2.card_content_type as card_content_type,
    t2.recommend_type as recommend_type,
    NVL(sum(t3.session_pv),0) as card_click,
    NVL(sum(t2.session_pv),0) as card_exposure,
    NVL(round(sum(page_stay)/count(distinct t4.cl_id)/60,2),0) as avg_page_stay,
    NVL(sum(navbar_pv),0) as navbar_search,
    NVL(sum(highlight_pv),0) as highlight_word,
    NVL(sum(self_wel_pv),0) as self_welfare_card,
    NVL(sum(recom_wel_pv),0)-NVL(sum(self_wel_pv),0) as recommend_welfare_card,--需要排除关联的商品卡片点击
    NVL(sum(recom_content_pv),0) as recommend_content_card,
    NULL as recommend_special_card,
    NVL(sum(referral_pv),0) as transfer_card,
    NVL(sum(video_pv),0) as video_consultation
FROM
    (
        SELECT partition_date
             ,device_os_type
             ,CASE WHEN active_type = '4'  THEN '老活'
                   WHEN active_type  IN ('1','2')  THEN '新增' END AS active_type
             ,device_id
        FROM online.ml_device_day_active_status
        WHERE partition_date=regexp_replace(DATE_SUB(current_date,1) ,'-','')
          AND active_type IN ('1','2','4')
          AND first_channel_source_type not IN ('yqxiu1','yqxiu2','yqxiu3','yqxiu4','yqxiu5','mxyc1','mxyc2','mxyc3'
            ,'wanpu','jinshan','jx','maimai','zhuoyi','huatian','suopingjingling','mocha','mizhe','meika','lamabang'
            ,'js-az1','js-az2','js-az3','js-az4','js-az5','jfq-az1','jfq-az2','jfq-az3','jfq-az4','jfq-az5','toufang1'
            ,'toufang2','toufang3','toufang4','toufang5','toufang6','TF-toufang1','TF-toufang2','TF-toufang3','TF-toufang4'
            ,'TF-toufang5','tf-toufang1','tf-toufang2','tf-toufang3','tf-toufang4','tf-toufang5','benzhan','promotion_aso100'
            ,'promotion_qianka','promotion_xiaoyu','promotion_dianru','promotion_malioaso','promotion_malioaso-shequ'
            ,'promotion_shike','promotion_julang_jl03','promotion_zuimei')
          AND first_channel_source_type not LIKE 'promotion\_jf\_%'
    )t1
        JOIN
    (--精准曝光，卡片id和session_id去重
        SELECT  partition_date,
                card_content_type,
                cl_id,
                recommend_type,
                card_id,
                count(distinct app_session_id) as session_pv
        FROM
        (
           SELECT partition_date,
                  cl_id,
                  case when card_content_type in ('qa','answer') then 'qa' else card_content_type end as card_content_type,
                  CASE when transaction_type in ('fmctr') then 'fmctr'
                       WHEN transaction_type like '%ctr' THEN 'ctr预估'
                       WHEN transaction_type like '%cvr' THEN 'cvr预估'
                       WHEN transaction_type in ('-1','smr') THEN 'smr'
                       when transaction_type in ('pgc','hotspot') then '热点卡片'
                       when transaction_type in ('newdata') then '保量卡片'
                       when transaction_type in ('hotspot_feed') then 'hotspot_feed'
                  END AS recommend_type,
                  card_id,
                  app_session_id
           from online.ml_community_precise_exposure_detail
           WHERE partition_date=regexp_replace(DATE_SUB(current_date,1) ,'-','')
           AND action in ('page_precise_exposure','home_choiceness_card_exposure') --7745版本action改为page_precise_exposure
           AND is_exposure = '1'  ----精准曝光
           AND page_name ='home'
           AND tab_name = '精选'
           AND (transaction_type in ('-1','smr','hotspot','pgc','newdata','hotspot_feed')
                or transaction_type like '%ctr' or transaction_type like '%cvr')
           AND card_content_type in ('qa','diary','user_post','answer')
           group by partition_date,
                  case when card_content_type in ('qa','answer') then 'qa' else card_content_type end,
                  cl_id,
                  CASE when transaction_type in ('fmctr') then 'fmctr'
                       WHEN transaction_type like '%ctr' THEN 'ctr预估'
                       WHEN transaction_type like '%cvr' THEN 'cvr预估'
                       WHEN transaction_type in ('-1','smr') THEN 'smr'
                       when transaction_type in ('pgc','hotspot') then '热点卡片'
                       when transaction_type in ('newdata') then '保量卡片'
                       when transaction_type in ('hotspot_feed') then 'hotspot_feed' END,
                  card_id,
                  app_session_id
        )a
        group by partition_date,card_content_type,cl_id,recommend_type,card_id
      )t2
    on t1.device_id=t2.cl_id and t1.partition_date=t2.partition_date
        LEFT JOIN
    (--卡片，卡片id和session_id去重
        SELECT  partition_date,
                card_content_type,
                cl_id,
                recommend_type,
                card_id,
                count(distinct app_session_id) as session_pv
        FROM
        (
           SELECT partition_date,
                  cl_id,
                  case when params['card_content_type'] in ('qa','answer') then 'qa' else params['card_content_type'] end as card_content_type,
                  CASE when params['transaction_type'] in ('fmctr') then 'fmctr'
                       WHEN params['transaction_type'] like '%ctr' THEN 'ctr预估'
                       WHEN params['transaction_type'] like '%cvr' THEN 'cvr预估'
                       WHEN params['transaction_type'] in ('-1','smr') THEN 'smr'
                       when params['transaction_type'] in ('pgc','hotspot') then '热点卡片'
                       when params['transaction_type'] in ('newdata') then '保量卡片'
                       when params['transaction_type'] in ('hotspot_feed') then 'hotspot_feed'
                  END AS recommend_type,
                  params['card_id'] as card_id,
                  app_session_id
           from online.bl_hdfs_maidian_updates
           WHERE partition_date=regexp_replace(DATE_SUB(current_date,1) ,'-','')
           AND action='on_click_card'
           AND params['page_name'] ='home'
           AND params['tab_name'] = '精选'
           AND (params['transaction_type'] in ('-1','smr','hotspot','pgc','newdata','hotspot_feed')
                or params['transaction_type'] like '%ctr' or params['transaction_type'] like '%cvr')
           AND params['card_content_type'] in ('qa','diary','user_post','answer')
           GROUP BY partition_date,
                  cl_id,
                  case when params['card_content_type'] in ('qa','answer') then 'qa' else params['card_content_type'] end,
                  CASE when params['transaction_type'] in ('fmctr') then 'fmctr'
                       WHEN params['transaction_type'] like '%ctr' THEN 'ctr预估'
                       WHEN params['transaction_type'] like '%cvr' THEN 'cvr预估'
                       WHEN params['transaction_type'] in ('-1','smr') THEN 'smr'
                       when params['transaction_type'] in ('pgc','hotspot') then '热点卡片'
                       when params['transaction_type'] in ('newdata') then '保量卡片'
                       when params['transaction_type'] in ('hotspot_feed') then 'hotspot_feed' END,
                  params['card_id'],
                  app_session_id
        )a
        group by partition_date,card_content_type,cl_id,recommend_type,card_id
      )t3
    on t2.partition_date=t3.partition_date
        and t2.cl_id=t3.cl_id
        and t2.card_id=t3.card_id
        and t2.card_content_type=t3.card_content_type
        and t2.recommend_type=t3.recommend_type
        LEFT JOIN
    (--页面浏览时长
          SELECT  partition_date,cl_id,business_id,
                  case when page_name in ('diary_detail','topic_detail') then 'diary'
                       when page_name in ('post_detail','user_post_detail','doctor_post_detail') then 'user_post'
                       when page_name in ('question_detail','answer_detail','question_answer_detail') then 'qa' else null end as page_name,
                  sum(page_stay) as page_stay
          FROM online.bl_hdfs_maidian_updates
          WHERE partition_date=regexp_replace(DATE_SUB(current_date,1) ,'-','')
          AND action='page_view'
          AND page_name IN ('diary_detail','topic_detail','post_detail','user_post_detail','doctor_post_detail','question_detail','answer_detail','question_answer_detail')
          AND referrer='home'
          AND page_stay>=0 AND page_stay<1000
          GROUP BY partition_date,cl_id,business_id,
                   case when page_name in ('diary_detail','topic_detail') then 'diary'
                       when page_name in ('post_detail','user_post_detail','doctor_post_detail') then 'user_post'
                       when page_name in ('question_detail','answer_detail','question_answer_detail') then 'qa' else null end
      )t4
    on t4.partition_date=t3.partition_date
        and t4.cl_id=t3.cl_id
        and t4.business_id=t3.card_id
        and t4.page_name=t3.card_content_type
        LEFT JOIN
    (--搜索框和点击行为
          SELECT partition_date,cl_id,business_id,
                 case when page_name in ('diary_detail','topic_detail') then 'diary'
                       when page_name in ('post_detail','user_post_detail','doctor_post_detail') then 'user_post'
                       when page_name in ('question_detail','answer_detail','question_answer_detail') then 'qa' else null end as page_name,
                 count(1) as navbar_pv
          FROM online.bl_hdfs_maidian_updates
          WHERE partition_date=regexp_replace(DATE_SUB(current_date,1) ,'-','')
          AND action in ('on_click_navbar_search','do_search')
          AND page_name IN ('diary_detail','topic_detail','post_detail','user_post_detail','doctor_post_detail','question_detail','answer_detail','question_answer_detail')
          AND (referrer='home' or
                  (params['referrer_link'] like '%[%' and
                   json_split(params['referrer_link'])[size(json_split(params['referrer_link']))-1]='home'))
          group by partition_date,cl_id,business_id,
                 case when page_name in ('diary_detail','topic_detail') then 'diary'
                       when page_name in ('post_detail','user_post_detail','doctor_post_detail') then 'user_post'
                       when page_name in ('question_detail','answer_detail','question_answer_detail') then 'qa' else null end
      )t5
    on t5.partition_date=t3.partition_date
        and t5.cl_id=t3.cl_id
        and t5.business_id=t3.card_id
        and t5.page_name=t3.card_content_type
        LEFT JOIN
    (--点击高亮词
          SELECT partition_date,cl_id,business_id,
                 case when page_name in ('diary_detail','topic_detail') then 'diary'
                       when page_name in ('post_detail','user_post_detail','doctor_post_detail') then 'user_post'
                       when page_name in ('question_detail','answer_detail','question_answer_detail') then 'qa' else null end as page_name,
                 count(1) as highlight_pv
          FROM online.bl_hdfs_maidian_updates
          WHERE partition_date=regexp_replace(DATE_SUB(current_date,1) ,'-','')
          AND action='on_click_card'
          and params['card_type']='highlight_word'
          AND page_name IN ('diary_detail','topic_detail','post_detail','user_post_detail','doctor_post_detail','question_detail','answer_detail','question_answer_detail')
          AND (referrer='home' or
                  (params['referrer_link'] like '%[%' and
                   json_split(params['referrer_link'])[size(json_split(params['referrer_link']))-1]='home'))
          group by partition_date,cl_id,business_id,
                 case when page_name in ('diary_detail','topic_detail') then 'diary'
                       when page_name in ('post_detail','user_post_detail','doctor_post_detail') then 'user_post'
                       when page_name in ('question_detail','answer_detail','question_answer_detail') then 'qa' else null end
      )t6
    on t6.partition_date=t3.partition_date
        and t6.cl_id=t3.cl_id
        and t6.business_id=t3.card_id
        and t6.page_name=t3.card_content_type
        LEFT JOIN
    (--关联的美购卡片
        SELECT partition_date,cl_id,business_id,page_name,count(distinct app_session_id) as self_wel_pv
        FROM
        (
            SELECT  partition_date,cl_id,business_id,app_session_id,params['card_id'] as card_id,
                    case when page_name in ('diary_detail','topic_detail') then 'diary'
                         when page_name in ('post_detail','user_post_detail','doctor_post_detail') then 'user_post'
                         when page_name in ('question_detail','answer_detail','question_answer_detail') then 'qa' else null end as page_name,
                    count(1) as pv
            FROM online.bl_hdfs_maidian_updates
            WHERE partition_date=regexp_replace(DATE_SUB(current_date,1) ,'-','')
            AND (get_json_object(params['extra_param'], '$.type')='交互栏'
           or get_json_object(params['extra_param'], '$.jump_from')='msg_link'
           or params['in_page_pos']='top'
           or (params['in_page_pos']='bottom' and params['position'] is null and cl_type='android')
        or (params['in_page_pos']='bottom' and params['card_but_pos'] is not null and cl_type='ios'))
            AND action='on_click_card'
            and params['card_content_type']='service'
            AND page_name IN ('diary_detail','topic_detail')
            AND (referrer='home' or
                  (params['referrer_link'] like '%[%' and
                   json_split(params['referrer_link'])[size(json_split(params['referrer_link']))-1]='home'))
            group by partition_date,cl_id,business_id,app_session_id,params['card_id'],
                    case when page_name in ('diary_detail','topic_detail') then 'diary'
                         when page_name in ('post_detail','user_post_detail','doctor_post_detail') then 'user_post'
                         when page_name in ('question_detail','answer_detail','question_answer_detail') then 'qa' else null end
        )a
        group by partition_date,cl_id,business_id,page_name
      )t7
    on t7.partition_date=t3.partition_date
        and t7.cl_id=t3.cl_id
        and t7.business_id=t3.card_id
        and t7.page_name=t3.card_content_type
        LEFT JOIN
    (--推荐的美购卡片(需要排除作者消费的美购)
        SELECT partition_date,cl_id,business_id,page_name,count(distinct app_session_id) as recom_wel_pv
        FROM
        (
            SELECT  partition_date,cl_id,business_id,app_session_id,params['card_id'] as card_id,
                    case when page_name in ('diary_detail','topic_detail') then 'diary'
                         when page_name in ('post_detail','user_post_detail','doctor_post_detail') then 'user_post'
                         when page_name in ('question_detail','answer_detail','question_answer_detail') then 'qa' else null end as page_name,
                    count(1) as service_pv
            FROM online.bl_hdfs_maidian_updates
            WHERE partition_date=regexp_replace(DATE_SUB(current_date,1) ,'-','')
            AND (action='on_click_card'and  params['card_content_type']='service'
                   or action='on_click_button' and params['button_name']='unfold' and page_name in ('diary_detail','topic_detail','post_detail','user_post_detail','doctor_post_detail')
                   or action='on_click_button' and params['button_name'] = 'more_recommendations')
            AND page_name IN ('diary_detail','topic_detail','post_detail','user_post_detail','doctor_post_detail','question_detail','answer_detail','question_answer_detail')
            AND (referrer='home' or
                  (params['referrer_link'] like '%[%' and
                   json_split(params['referrer_link'])[size(json_split(params['referrer_link']))-1]='home'))
            group by partition_date,cl_id,business_id,app_session_id,params['card_id'],
                    case when page_name in ('diary_detail','topic_detail') then 'diary'
                         when page_name in ('post_detail','user_post_detail','doctor_post_detail') then 'user_post'
                         when page_name in ('question_detail','answer_detail','question_answer_detail') then 'qa' else null end
        )a
        group by partition_date,cl_id,business_id,page_name
      )t8
    on t8.partition_date=t3.partition_date
        and t8.cl_id=t3.cl_id
        and t8.business_id=t3.card_id
        and t8.page_name=t3.card_content_type
        LEFT JOIN
    (--推荐的内容卡片
        SELECT partition_date,cl_id,business_id,page_name,count(distinct app_session_id) as recom_content_pv
        FROM
        (
            SELECT  partition_date,cl_id,business_id,app_session_id,params['card_id'] as card_id,
                    case when page_name in ('diary_detail','topic_detail') then 'diary'
                         when page_name in ('post_detail','user_post_detail','doctor_post_detail') then 'user_post'
                         when page_name in ('question_detail','answer_detail','question_answer_detail') then 'qa' else null end as page_name,
                    count(1) as service_pv
            FROM online.bl_hdfs_maidian_updates
            WHERE partition_date=regexp_replace(DATE_SUB(current_date,1) ,'-','')
            AND action='on_click_card'
            and params['card_content_type'] in ('qa','diary','user_post','answer')
            AND page_name IN ('diary_detail','topic_detail','post_detail','user_post_detail','doctor_post_detail','question_detail','answer_detail','question_answer_detail')
            AND (referrer='home' or
                  (params['referrer_link'] like '%[%' and
                   json_split(params['referrer_link'])[size(json_split(params['referrer_link']))-1]='home'))
            group by partition_date,cl_id,business_id,app_session_id,params['card_id'],
                    case when page_name in ('diary_detail','topic_detail') then 'diary'
                         when page_name in ('post_detail','user_post_detail','doctor_post_detail') then 'user_post'
                         when page_name in ('question_detail','answer_detail','question_answer_detail') then 'qa' else null end
        )a
        group by partition_date,cl_id,business_id,page_name
      )t9
    on t9.partition_date=t3.partition_date
        and t9.cl_id=t3.cl_id
        and t9.business_id=t3.card_id
        and t9.page_name=t3.card_content_type
        LEFT JOIN
    (--转诊点击，视频面诊点击
        SELECT partition_date,cl_id,business_id,
                 case when page_name in ('diary_detail','topic_detail') then 'diary'
                       when page_name in ('post_detail','user_post_detail','doctor_post_detail') then 'user_post'
                       when page_name in ('question_detail','answer_detail','question_answer_detail') then 'qa' else null end as page_name,
                 count(1) as video_pv
          FROM online.bl_hdfs_maidian_updates
          WHERE partition_date=regexp_replace(DATE_SUB(current_date,1) ,'-','')
          AND action='on_click_button'
          and params['button_name']='video_interview'
          AND page_name IN ('diary_detail','topic_detail','post_detail','user_post_detail','doctor_post_detail','question_detail','answer_detail','question_answer_detail')
          AND (referrer='home' or
                  (params['referrer_link'] like '%[%' and
                   json_split(params['referrer_link'])[size(json_split(params['referrer_link']))-1]='home'))
          group by partition_date,cl_id,business_id,
                 case when page_name in ('diary_detail','topic_detail') then 'diary'
                       when page_name in ('post_detail','user_post_detail','doctor_post_detail') then 'user_post'
                       when page_name in ('question_detail','answer_detail','question_answer_detail') then 'qa' else null end
      )t10
    on t10.partition_date=t3.partition_date
        and t10.cl_id=t3.cl_id
        and t10.business_id=t3.card_id
        and t10.page_name=t3.card_content_type
        LEFT JOIN
    (--推荐的内容卡片
        SELECT partition_date,cl_id,business_id,
                 case when page_name in ('diary_detail','topic_detail') then 'diary'
                       when page_name in ('post_detail','user_post_detail','doctor_post_detail') then 'user_post'
                       when page_name in ('question_detail','answer_detail','question_answer_detail') then 'qa' else null end as page_name,
                 count(1) as referral_pv
          FROM online.bl_hdfs_maidian_updates
          WHERE partition_date=regexp_replace(DATE_SUB(current_date,1) ,'-','')
          AND action='on_click_button'
          and params['button_name']='referral'
          AND page_name IN ('diary_detail','topic_detail','post_detail','user_post_detail','doctor_post_detail','question_detail','answer_detail','question_answer_detail')
          AND (referrer='home' or
                  (params['referrer_link'] like '%[%' and
                   json_split(params['referrer_link'])[size(json_split(params['referrer_link']))-1]='home'))
          group by partition_date,cl_id,business_id,
                 case when page_name in ('diary_detail','topic_detail') then 'diary'
                       when page_name in ('post_detail','user_post_detail','doctor_post_detail') then 'user_post'
                       when page_name in ('question_detail','answer_detail','question_answer_detail') then 'qa' else null end
      )t11
    on t11.partition_date=t3.partition_date
        and t11.cl_id=t3.cl_id
        and t11.business_id=t3.card_id
        and t11.page_name=t3.card_content_type
        LEFT JOIN
    (
        select distinct device_id
        from ml.ml_d_ct_dv_devicespam_d  --去除机构刷单设备，即作弊设备（浏览和曝光事件去除）
        WHERE partition_day=regexp_replace(DATE_SUB(current_date,1) ,'-','')

        union all

        select distinct device_id
        from dim.dim_device_user_staff   --去除内网用户
    )spam_pv
    on spam_pv.device_id=t2.cl_id
        LEFT JOIN
    (
        SELECT partition_date,device_id
        FROM
            (--找出user_id当天活跃的第一个设备id
          SELECT user_id,partition_date,
                  if(size(device_list) > 0, device_list [ 0 ], '') AS device_id
            FROM online.ml_user_updates
            WHERE partition_date=regexp_replace(DATE_SUB(current_date,1) ,'-','')
        )t1
                JOIN
            (  --医生账号
          SELECT distinct user_id
          FROM online.tl_hdfs_doctor_view
          WHERE partition_date = regexp_replace(DATE_SUB(current_date,1) ,'-','')

          --马甲账号/模特用户
          UNION ALL
          SELECT user_id
          FROM ml.ml_c_ct_ui_user_dimen_d
          WHERE partition_day = regexp_replace(DATE_SUB(current_date,1) ,'-','')
          AND (is_puppet = 'true' or is_classifyuser = 'true')

          UNION ALL
          --公司内网覆盖用户
          select distinct user_id
          from dim.dim_device_user_staff

          UNION ALL
          --登陆过医生设备
          SELECT distinct t1.user_id
            FROM
            (
                SELECT user_id, v.device_id as device_id
                FROM online.ml_user_history_detail
                    LATERAL VIEW EXPLODE(device_history_list) v AS device_id
                WHERE partition_date = regexp_replace(DATE_SUB(current_date,1) ,'-','')
            ) t1
            JOIN
            (
                SELECT device_id
                FROM online.ml_device_history_detail
                WHERE partition_date = regexp_replace(DATE_SUB(current_date,1) ,'-','')
                AND is_login_doctor = '1'
            ) t2
                ON t1.device_id = t2.device_id
        )t2
            on t1.user_id=t2.user_id
        group by partition_date,device_id
    )dev
    on t2.partition_date=dev.partition_date and t2.cl_id=dev.device_id
WHERE spam_pv.device_id IS NULL
  and dev.device_id is null
GROUP BY t1.partition_date,t1.device_os_type,t1.active_type,t2.card_content_type,t2.recommend_type
order by day_id,device_os_type,active_type,card_content_type,recommend_type;






--引用2020年1月至今数据

SELECT
    day_id as `日期`,
    device_os_type as `设备类型`,
    active_type as `活跃类型`,
    card_content_type as `卡片类型`,
    recommend_type as `推荐类型`,
    NVL(CONCAT(ROUND((navbar_search+highlight_word+self_welfare_card+recommend_welfare_card+recommend_content_card*0.2+transfer_card+video_consultation)/card_exposure*100,2),'%'),0) as `来自首页推荐内容卡片的的有效二跳pv/首页卡片精准曝光PV`,
    NVL(CONCAT(ROUND(card_click/card_exposure*100,2),'%'),0) as `首页卡片点击PV/首页卡片精准曝光PV`,
    NVL(CONCAT(ROUND((navbar_search+highlight_word+self_welfare_card+recommend_welfare_card+recommend_content_card*0.2+transfer_card+video_consultation)/card_click*100,2),'%'),0) as `来自首页推荐内容卡片的的有效二跳pv/首页卡片点击PV`,
    card_click as `首页卡片点击PV`,
    card_exposure as `首页卡片精准曝光PV`,
    (navbar_search+highlight_word+self_welfare_card+recommend_welfare_card+recommend_content_card*0.2+transfer_card+video_consultation)as `有效二跳pv`,
    avg_page_stay as `来自I的单PV平均浏览时长`,
    navbar_search as `来自I的搜索框+搜索按钮点击PV`,
    highlight_word as `来自I的文内搜索点击PV`,
    self_welfare_card as `来自I的商品卡片点击PV`,
    recommend_welfare_card as `来自I的推荐商品+查看全部商品点击pv`,
    recommend_content_card as `来自I的推荐内容点击pv`,
--    '未配置' as `来自I的推荐专题点击pv`,
    transfer_card as `来自I的转诊点击pv`,
    video_consultation as `来自I的视频面诊点击pv`FROM pm.tl_pm_recommend_strategy_d
WHERE partition_day>='20200627' and partition_day<=regexp_replace(DATE_SUB(current_date,1) ,'-','')
and day_id>='20200101'
order by `日期` desc ,`设备类型`,`活跃类型`,`卡片类型`,`推荐类型`;

select *,ROUND(cast(card_click as double) /cast(card_exposure as double),4) as card_click_divide_card_exposure from pm.tl_pm_recommend_strategy_d where device_os_type = 'android' and active_type = '新增' and recommend_type = 'ctr预估' order by day_id desc



CREATE TABLE recommend_strategy_d_fix(
   day_id varchar(100),
   device_os_type varchar(100),
   active_type varchar(100),
   card_content_type varchar(100),
   	recommend_type varchar(100),
   card_click BIGINT(20),
   card_exposure BIGINT(20),
   avg_page_stay double,
   navbar_search BIGINT(20),
   highlight_word BIGINT(20),
   self_welfare_card BIGINT(20),
   recommend_welfare_card BIGINT(20),
   	recommend_content_card BIGINT(20),
   recommend_special_card BIGINT(20),
   transfer_card BIGINT(20),
   video_consultation BIGINT(20),
   partition_day varchar(100),
   recommend_ctr FLOAT,
   second_jump_ctr FLOAT,
   click_ctr FLOAT,
   page_pv_20_percent FLOAT,

   pid varchar(100),
   PRIMARY KEY ( pid )
)ENGINE=InnoDB DEFAULT CHARSET=utf8;

alert 
ALTER TABLE recommend_strategy_d ADD recommend_ctr FLOAT;
ALTER TABLE recommend_strategy_d ADD second_jump_ctr FLOAT;
ALTER TABLE recommend_strategy_d_fix ADD page_pv_20_percent FLOAT;

