设备导入修改及最新值

health-watch/health-watch-biz/src/main/java/com/renkang/watch/mapper/xml/WatchStatUserInfoDayHeartRateMapper.xml

@@ -358,21 +358,33 @@
 
     <update id="updateStat">
         update watch_stat_user_info_day_heart_rate stat
-            left join (select bind_user_id,
-                              ifnull(max(data_value), 0)    as max_value,
-                              ifnull(min(data_value), 0)    as min_value,
-                              ifnull(avg(data_value), 0)    as avg_value,
-                              ifnull(max(silence_value), 0) as silence_max_value,
-                              ifnull(min(silence_value), 0) as silence_min_value,
-                              ifnull(avg(silence_value), 0) as silence_avg_value,
-                              ifnull(max(time_stamp), NOW()) as last_upload_time,
-                              ifnull(data_value, 0) as new_value,
-                              ifnull(silence_value, 0) as silence_new_value,
-                              data_date
+            left join (
+            select
+            wd.bind_user_id,
+            ifnull(max(wd.data_value), 0)        as max_value,
+            ifnull(min(wd.data_value), 0)        as min_value,
+            ifnull(avg(wd.data_value), 0)        as avg_value,
+            ifnull(max(wd.silence_value), 0)     as silence_max_value,
+            ifnull(min(wd.silence_value), 0)     as silence_min_value,
+            ifnull(avg(wd.silence_value), 0)     as silence_avg_value,
+            ifnull(max(wd.time_stamp), NOW())    as last_upload_time,
+            latest.new_value,
+            latest.silence_new_value,
+            wd.data_date
+            from watch_data_heart_rate wd
+            left join (
+            select bind_user_id, data_date, data_value as new_value, silence_value as silence_new_value
+            from watch_data_heart_rate t1
+            where (bind_user_id, data_date, time_stamp) in (
+            select bind_user_id, data_date, max(time_stamp)
             from watch_data_heart_rate
-                       where bind_user_id = #{userId,jdbcType=VARCHAR}
-                         and data_date = #{dataDate,jdbcType=DATE}
-                       group by bind_user_id, data_date) data on stat.user_id = data.bind_user_id
+            group by bind_user_id, data_date
+            )
+            ) latest on wd.bind_user_id = latest.bind_user_id and wd.data_date = latest.data_date
+            where wd.bind_user_id = #{userId,jdbcType=VARCHAR}
+            and wd.data_date = #{dataDate,jdbcType=DATE}
+            group by wd.bind_user_id, wd.data_date, latest.new_value, latest.silence_new_value
+            ) data on stat.user_id = data.bind_user_id and stat.data_date = data.data_date
             set stat.max_value         = data.max_value,
                 stat.min_value         = data.min_value,
                 stat.avg_value         = data.avg_value,
@@ -381,7 +393,7 @@
                 stat.silence_avg_value = data.silence_avg_value,
                 stat.last_upload_time  = data.last_upload_time,
                 stat.new_value         = data.new_value,
-            stat.silence_new_value = data.silence_new_value,
+                stat.silence_new_value = IF(data.silence_new_value IS NULL OR data.silence_new_value = 0, stat.silence_new_value, data.silence_new_value),
                 stat.org_code          = #{orgCode,jdbcType=VARCHAR}
         where stat.user_id = #{userId,jdbcType=VARCHAR}
           and stat.data_date = #{dataDate,jdbcType=DATE};

health-watch/health-watch-biz/src/main/java/com/renkang/watch/mapper/xml/WatchStatUserInfoDaySpo2Mapper.xml

@@ -55,17 +55,29 @@
 
     <update id="updateStat">
         update watch_stat_user_info_day_spo2 stat
-        left join (select bind_user_id,
-        ifnull(max(data_value), 0)    as max_value,
-        ifnull(min(data_value), 0)    as min_value,
-        ifnull(avg(data_value), 0)    as avg_value,
-        ifnull(max(time_stamp), 0)    as last_upload_time,
-        ifnull(data_value, 0)    as new_value,
-        data_date
+            left join (
+            select
+            wd.bind_user_id,
+            ifnull(max(wd.data_value), 0)    as max_value,
+            ifnull(min(wd.data_value), 0)    as min_value,
+            ifnull(avg(wd.data_value), 0)    as avg_value,
+            ifnull(max(wd.time_stamp), 0)    as last_upload_time,
+            latest.new_value,
+            wd.data_date
+            from watch_data_spo2 wd
+            left join (
+            select bind_user_id, data_date, data_value as new_value
+            from watch_data_spo2 t1
+            where (bind_user_id, data_date, time_stamp) in (
+            select bind_user_id, data_date, max(time_stamp)
             from watch_data_spo2
-        where bind_user_id = #{userId,jdbcType=VARCHAR}
-        and data_date = #{dataDate,jdbcType=DATE}
-        group by bind_user_id, data_date) data on stat.user_id = data.bind_user_id
+            group by bind_user_id, data_date
+            )
+            ) latest on wd.bind_user_id = latest.bind_user_id and wd.data_date = latest.data_date
+            where wd.bind_user_id = #{userId,jdbcType=VARCHAR}
+            and wd.data_date = #{dataDate,jdbcType=DATE}
+            group by wd.bind_user_id, wd.data_date, latest.new_value
+            ) data on stat.user_id = data.bind_user_id and stat.data_date = data.data_date
             set stat.max_value         = data.max_value,
                 stat.min_value         = data.min_value,
                 stat.avg_value         = data.avg_value,

health-watch/health-watch-biz/src/main/java/com/renkang/watch/mapper/xml/WatchStatUserInfoDayStressMapper.xml

@@ -27,9 +27,9 @@
                     ifnull(max(data_value), 0),
                     ifnull(min(data_value), 0),
                     ifnull(avg(data_value), 0),
+                    data_date,
                     ifnull(max(end_time_stamp), NOW()),
                     ifnull(data_value, 0),
-        data_date,
                     #{orgCode,jdbcType=VARCHAR}
              from watch_data_stress
              where bind_user_id = #{userId,jdbcType=VARCHAR}
@@ -39,17 +39,29 @@
 
     <update id="updateStat">
         update watch_stat_user_info_day_stress stat
-        left join (select bind_user_id,
-        ifnull(max(data_value), 0)    as max_value,
-        ifnull(min(data_value), 0)    as min_value,
-        ifnull(avg(data_value), 0)    as avg_value,
-        ifnull(max(end_time_stamp), NOW()) as last_upload_time,
-        ifnull(data_value, 0)    as new_value,
-        data_date
+            left join (
+            select
+            wd.bind_user_id,
+            ifnull(max(wd.data_value), 0)    as max_value,
+            ifnull(min(wd.data_value), 0)    as min_value,
+            ifnull(avg(wd.data_value), 0)    as avg_value,
+            ifnull(max(wd.end_time_stamp), NOW()) as last_upload_time,
+            latest.new_value,
+            wd.data_date
+            from watch_data_stress wd
+            left join (
+            select bind_user_id, data_date, data_value as new_value
+            from watch_data_stress t1
+            where (bind_user_id, data_date, end_time_stamp) in (
+            select bind_user_id, data_date, max(end_time_stamp)
             from watch_data_stress
-        where bind_user_id = #{userId,jdbcType=VARCHAR}
-        and data_date = #{dataDate,jdbcType=DATE}
-        group by bind_user_id, data_date) data on stat.user_id = data.bind_user_id
+            group by bind_user_id, data_date
+            )
+            ) latest on wd.bind_user_id = latest.bind_user_id and wd.data_date = latest.data_date
+            where wd.bind_user_id = #{userId,jdbcType=VARCHAR}
+            and wd.data_date = #{dataDate,jdbcType=DATE}
+            group by wd.bind_user_id, wd.data_date, latest.new_value
+            ) data on stat.user_id = data.bind_user_id and stat.data_date = data.data_date
             set stat.max_value         = data.max_value,
                 stat.min_value         = data.min_value,
                 stat.avg_value         = data.avg_value,

health-watch/health-watch-biz/src/main/java/com/renkang/watch/mapper/xml/WatchStatUserInfoDayTempMapper.xml

@@ -58,21 +58,33 @@
 
     <update id="updateStat">
         update watch_stat_user_info_day_temp stat
-        left join (select bind_user_id,
-        ifnull(max(data_value), 0)    as max_value,
-        ifnull(min(data_value), 0)    as min_value,
-        ifnull(avg(data_value), 0)    as avg_value,
-        ifnull(max(skin_tempera), 0) as skin_max_value,
-        ifnull(min(skin_tempera), 0) as skin_min_value,
-        ifnull(avg(skin_tempera), 0) as skin_avg_value,
-        ifnull(max(time_stamp), NOW()) as last_upload_time,
-        ifnull(data_value, 0)    as new_value,
-        ifnull(skin_tempera, 0) as skin_new_value,
-        data_date
+            left join (
+            select
+            wd.bind_user_id,
+            ifnull(max(wd.data_value), 0)    as max_value,
+            ifnull(min(wd.data_value), 0)    as min_value,
+            ifnull(avg(wd.data_value), 0)    as avg_value,
+            ifnull(max(wd.skin_tempera), 0) as skin_max_value,
+            ifnull(min(wd.skin_tempera), 0) as skin_min_value,
+            ifnull(avg(wd.skin_tempera), 0) as skin_avg_value,
+            ifnull(max(wd.time_stamp), NOW()) as last_upload_time,
+            latest.new_value,
+            latest.skin_new_value,
+            wd.data_date
+            from watch_data_temperature wd
+            left join (
+            select bind_user_id, data_date, data_value as new_value, skin_tempera as skin_new_value
+            from watch_data_temperature t1
+            where (bind_user_id, data_date, time_stamp) in (
+            select bind_user_id, data_date, max(time_stamp)
             from watch_data_temperature
-        where bind_user_id = #{userId,jdbcType=VARCHAR}
-        and data_date = #{dataDate,jdbcType=DATE}
-        group by bind_user_id, data_date) data on stat.user_id = data.bind_user_id
+            group by bind_user_id, data_date
+            )
+            ) latest on wd.bind_user_id = latest.bind_user_id and wd.data_date = latest.data_date
+            where wd.bind_user_id = #{userId,jdbcType=VARCHAR}
+            and wd.data_date = #{dataDate,jdbcType=DATE}
+            group by wd.bind_user_id, wd.data_date, latest.new_value, latest.skin_new_value
+            ) data on stat.user_id = data.bind_user_id and stat.data_date = data.data_date
             set stat.max_value         = data.max_value,
                 stat.min_value         = data.min_value,
                 stat.avg_value         = data.avg_value,
@@ -81,7 +93,7 @@
                 stat.skin_avg_value    = data.skin_avg_value,
                 stat.last_upload_time  = data.last_upload_time,
                 stat.new_value         = data.new_value,
-        stat.skin_new_value = data.skin_new_value,
+                stat.skin_new_value    = IF(data.skin_new_value IS NULL OR data.skin_new_value = 0, stat.skin_new_value, data.skin_new_value),
                 stat.org_code          = #{orgCode,jdbcType=VARCHAR}
         where stat.user_id = #{userId,jdbcType=VARCHAR}
           and stat.data_date = #{dataDate,jdbcType=DATE};