diff --git a/health-watch/health-watch-biz/src/main/java/com/renkang/watch/mapper/xml/WatchStatUserInfoDayHeartRateMapper.xml b/health-watch/health-watch-biz/src/main/java/com/renkang/watch/mapper/xml/WatchStatUserInfoDayHeartRateMapper.xml
index 32b0f5b..30eef6b 100644
--- a/health-watch/health-watch-biz/src/main/java/com/renkang/watch/mapper/xml/WatchStatUserInfoDayHeartRateMapper.xml
+++ b/health-watch/health-watch-biz/src/main/java/com/renkang/watch/mapper/xml/WatchStatUserInfoDayHeartRateMapper.xml
@@ -334,68 +334,75 @@
             AND wsd.data_date = temp.latest_date;
     </select>
 
+    <!-- 切记 此代码不能直接平移至四合一项目 ,该sql只适用mysql8.0及以上版本 ,四合一项目开发测试环境的mysql版本过低 , 但不影响正式环境-->
     <insert id="insertStat">
-        insert into watch_stat_user_info_day_heart_rate(id, user_id, max_value, min_value, avg_value, silence_max_value,
-                                                        silence_min_value, silence_avg_value,  last_upload_time, new_value, silence_new_value, data_date, org_code)
-            (select #{id,jdbcType=VARCHAR},
-                    bind_user_id,
-                    ifnull(max(data_value), 0),
-                    ifnull(min(data_value), 0),
-                    ifnull(avg(data_value), 0),
-                    ifnull(max(silence_value), 0),
-                    ifnull(min(silence_value), 0),
-                    ifnull(avg(silence_value), 0),
-                    ifnull(max(time_stamp), NOW()),
-                    ifnull(data_value, 0),
-                    ifnull(silence_value, 0),
-                    data_date,
-                    #{orgCode,jdbcType=VARCHAR}
-             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);
+        INSERT INTO watch_stat_user_info_day_heart_rate ( id, user_id, max_value, min_value, avg_value, silence_max_value, silence_min_value, silence_avg_value, last_upload_time, new_value, silence_new_value, data_date, org_code ) (
+            SELECT
+                #{id,jdbcType=VARCHAR},
+                bind_user_id,
+                IFNULL( MAX( wd.data_value ), 0 ),
+                IFNULL( MIN( wd.data_value ), 0 ),
+                IFNULL( AVG( wd.data_value ), 0 ),
+                IFNULL( MAX( wd.silence_value ), 0 ),
+                IFNULL( MIN( wd.silence_value ), 0 ),
+                IFNULL( AVG( wd.silence_value ), 0 ),
+                IFNULL(MAX( wd.time_stamp ),NOW()),
+                MAX( CASE WHEN wd.rn = 1 THEN wd.data_value END ),
+                MAX( CASE WHEN wd.rn = 1 THEN wd.silence_value END ),
+                data_date,
+                #{orgCode,jdbcType=VARCHAR}
+            FROM
+                (
+                    SELECT
+                        *,
+                        ROW_NUMBER() OVER ( PARTITION BY bind_user_id, data_date ORDER BY time_stamp DESC ) AS rn
+                    FROM
+                        watch_data_heart_rate
+                    WHERE
+                        bind_user_id = #{userId,jdbcType=VARCHAR}
+                      and data_date = #{dataDate,jdbcType=DATE}
+                ) wd
+            GROUP BY
+                wd.bind_user_id,
+                wd.data_date
+        );
     </insert>
 
+    <!-- 切记 此代码不能直接平移至四合一项目 ,该sql只适用mysql8.0及以上版本 ,四合一项目开发测试环境的mysql版本过低 , 但不影响正式环境-->
     <update id="updateStat">
-        update watch_stat_user_info_day_heart_rate stat
-            left join (
-            select
+        UPDATE watch_stat_user_info_day_heart_rate stat
+            LEFT JOIN (
+            SELECT
+            wd.bind_user_id,
+            wd.data_date,
+            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,
+            MAX( CASE WHEN wd.rn = 1 THEN wd.data_value END ) AS new_value,
+            MAX( CASE WHEN wd.rn = 1 THEN wd.silence_value END ) AS silence_new_value
+            FROM
+            ( SELECT *, ROW_NUMBER() OVER ( PARTITION BY bind_user_id, data_date ORDER BY time_stamp DESC ) AS rn FROM watch_data_heart_rate where bind_user_id = #{userId,jdbcType=VARCHAR}
+            and data_date = #{dataDate,jdbcType=DATE} ) wd
+            GROUP BY
             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
-            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,
-                stat.silence_max_value = data.silence_max_value,
-                stat.silence_min_value = data.silence_min_value,
-                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 = 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}
+            ) 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,
+                stat.silence_max_value = DATA.silence_max_value,
+                stat.silence_min_value = DATA.silence_min_value,
+                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 = COALESCE ( NULLIF( DATA.silence_new_value, 0 ), stat.silence_new_value ),
+                stat.org_code = #{orgCode,jdbcType=VARCHAR}
         where stat.user_id = #{userId,jdbcType=VARCHAR}
-          and stat.data_date = #{dataDate,jdbcType=DATE};
+        and stat.data_date = #{dataDate,jdbcType=DATE};
     </update>
 </mapper>
\ No newline at end of file
diff --git a/health-watch/health-watch-biz/src/main/java/com/renkang/watch/mapper/xml/WatchStatUserInfoDaySpo2Mapper.xml b/health-watch/health-watch-biz/src/main/java/com/renkang/watch/mapper/xml/WatchStatUserInfoDaySpo2Mapper.xml
index 66f28aa..b32285d 100644
--- a/health-watch/health-watch-biz/src/main/java/com/renkang/watch/mapper/xml/WatchStatUserInfoDaySpo2Mapper.xml
+++ b/health-watch/health-watch-biz/src/main/java/com/renkang/watch/mapper/xml/WatchStatUserInfoDaySpo2Mapper.xml
@@ -36,54 +36,53 @@
         group by user_id
     </select>
 
+    <!-- 切记 此代码不能直接平移至四合一项目 ,该sql只适用mysql8.0及以上版本 ,四合一项目开发测试环境的mysql版本过低 , 但不影响正式环境-->
     <insert id="insertStat">
-        insert into watch_stat_user_info_day_spo2(id, user_id, max_value, min_value, avg_value, last_upload_time, new_value, data_date, org_code)
-        (select #{id,jdbcType=VARCHAR},
-        bind_user_id,
-        ifnull(max(data_value), 0),
-        ifnull(min(data_value), 0),
-        ifnull(avg(data_value), 0),
-        ifnull(max(time_stamp), NOW()),
-        ifnull(data_value, 0),
-        data_date,
-        #{orgCode,jdbcType=VARCHAR}
-        from watch_data_spo2
-        where bind_user_id = #{userId,jdbcType=VARCHAR}
-        and data_date = #{dataDate,jdbcType=DATE}
-        group by bind_user_id, data_date);
+        insert into watch_stat_user_info_day_spo2(id, user_id, max_value, min_value, avg_value, last_upload_time,
+                                                  new_value, data_date, org_code)
+            (SELECT #{id,jdbcType=VARCHAR},
+                    bind_user_id,
+                    IFNULL(MAX(wd.data_value), 0),
+                    IFNULL(MIN(wd.data_value), 0),
+                    IFNULL(AVG(wd.data_value), 0),
+                    IFNULL(MAX(wd.time_stamp), 0),
+                    MAX(CASE WHEN wd.rn = 1 THEN wd.data_value END),
+                    data_date,
+                    #{orgCode,jdbcType=VARCHAR}
+             FROM (SELECT *, ROW_NUMBER() OVER ( PARTITION BY bind_user_id, data_date ORDER BY time_stamp DESC ) AS rn
+                   FROM watch_data_spo2
+                   where bind_user_id = #{userId,jdbcType=VARCHAR}
+                     and data_date = #{dataDate,jdbcType=DATE}) wd
+             GROUP BY wd.bind_user_id,
+                      wd.data_date);
     </insert>
 
+    <!-- 切记 此代码不能直接平移至四合一项目 ,该sql只适用mysql8.0及以上版本 ,四合一项目开发测试环境的mysql版本过低 , 但不影响正式环境-->
     <update id="updateStat">
-        update watch_stat_user_info_day_spo2 stat
-            left join (
-            select
+        UPDATE watch_stat_user_info_day_spo2 stat
+            LEFT JOIN (
+            SELECT
+            wd.bind_user_id,
+            wd.data_date,
+            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,
+            MAX( CASE WHEN wd.rn = 1 THEN wd.data_value END ) AS new_value
+            FROM
+            ( SELECT *, ROW_NUMBER() OVER ( PARTITION BY bind_user_id, data_date ORDER BY time_stamp DESC ) AS rn FROM watch_data_spo2  where bind_user_id = #{userId,jdbcType=VARCHAR}
+            and data_date = #{dataDate,jdbcType=DATE}) wd
+            GROUP BY
             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
-            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,
-                stat.last_upload_time  = data.last_upload_time,
-                stat.new_value         = data.new_value,
-                stat.org_code          = #{orgCode,jdbcType=VARCHAR}
+            ) 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,
+                stat.last_upload_time = DATA.last_upload_time,
+                stat.new_value = DATA.new_value,
+                stat.org_code = #{orgCode,jdbcType=VARCHAR}
         where stat.user_id = #{userId,jdbcType=VARCHAR}
           and stat.data_date = #{dataDate,jdbcType=DATE};
     </update>
diff --git a/health-watch/health-watch-biz/src/main/java/com/renkang/watch/mapper/xml/WatchStatUserInfoDayStressMapper.xml b/health-watch/health-watch-biz/src/main/java/com/renkang/watch/mapper/xml/WatchStatUserInfoDayStressMapper.xml
index d89eb45..4360bce 100644
--- a/health-watch/health-watch-biz/src/main/java/com/renkang/watch/mapper/xml/WatchStatUserInfoDayStressMapper.xml
+++ b/health-watch/health-watch-biz/src/main/java/com/renkang/watch/mapper/xml/WatchStatUserInfoDayStressMapper.xml
@@ -19,56 +19,58 @@
             user_id=#{userId}
     </select>
 
-
+    <!-- 切记 此代码不能直接平移至四合一项目 ,该sql只适用mysql8.0及以上版本 ,四合一项目开发测试环境的mysql版本过低 , 但不影响正式环境-->
     <insert id="insertStat">
         insert into watch_stat_user_info_day_stress(id, user_id, max_value, min_value, avg_value, data_date, last_upload_time, new_value, org_code)
-            (select #{id,jdbcType=VARCHAR},
+            (
+                SELECT
+                    #{id,jdbcType=VARCHAR},
                     bind_user_id,
-                    ifnull(max(data_value), 0),
-                    ifnull(min(data_value), 0),
-                    ifnull(avg(data_value), 0),
+                    IFNULL( MAX( wd.data_value ), 0 ),
+                    IFNULL( MIN( wd.data_value ), 0 ),
+                    IFNULL( AVG( wd.data_value ), 0 ),
                     data_date,
-                    ifnull(max(end_time_stamp), NOW()),
-                    ifnull(data_value, 0),
+                    IFNULL(MAX( wd.end_time_stamp ),NOW()),
+                    MAX( CASE WHEN wd.rn = 1 THEN wd.data_value END ),
                     #{orgCode,jdbcType=VARCHAR}
-             from watch_data_stress
-             where bind_user_id = #{userId,jdbcType=VARCHAR}
-               and data_date = #{dataDate,jdbcType=DATE}
-             group by bind_user_id, data_date);
+                FROM
+                    ( SELECT *, ROW_NUMBER() OVER ( PARTITION BY bind_user_id, data_date ORDER BY end_time_stamp DESC ) AS rn FROM watch_data_stress
+                      where bind_user_id = #{userId,jdbcType=VARCHAR}
+                        and data_date = #{dataDate,jdbcType=DATE}) wd
+                GROUP BY
+                    wd.bind_user_id,
+                    wd.data_date
+             );
     </insert>
 
+    <!-- 切记 此代码不能直接平移至四合一项目 ,该sql只适用mysql8.0及以上版本 ,四合一项目开发测试环境的mysql版本过低 , 但不影响正式环境-->
     <update id="updateStat">
-        update watch_stat_user_info_day_stress stat
-            left join (
-            select
+        UPDATE watch_stat_user_info_day_stress stat
+            LEFT JOIN (
+            SELECT
+            wd.bind_user_id,
+            wd.data_date,
+            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,
+            MAX( CASE WHEN wd.rn = 1 THEN wd.data_value END ) AS new_value
+            FROM
+            ( SELECT *, ROW_NUMBER() OVER ( PARTITION BY bind_user_id, data_date ORDER BY end_time_stamp DESC ) AS rn FROM watch_data_stress
+            where bind_user_id = #{userId,jdbcType=VARCHAR}
+            and data_date = #{dataDate,jdbcType=DATE}) wd
+            GROUP BY
             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
-            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,
-                stat.last_upload_time  = data.last_upload_time,
-                stat.new_value         = data.new_value,
-                stat.org_code          = #{orgCode,jdbcType=VARCHAR}
-        where stat.user_id = #{userId,jdbcType=VARCHAR}
-          and stat.data_date = #{dataDate,jdbcType=DATE};
+            ) 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,
+                stat.last_upload_time = DATA.last_upload_time,
+                stat.new_value = DATA.new_value,
+                stat.org_code = #{orgCode,jdbcType=VARCHAR}
+            where stat.user_id = #{userId,jdbcType=VARCHAR}
+            and stat.data_date = #{dataDate,jdbcType=DATE};
     </update>
 </mapper>
\ No newline at end of file
diff --git a/health-watch/health-watch-biz/src/main/java/com/renkang/watch/mapper/xml/WatchStatUserInfoDayTempMapper.xml b/health-watch/health-watch-biz/src/main/java/com/renkang/watch/mapper/xml/WatchStatUserInfoDayTempMapper.xml
index faed779..92acf79 100644
--- a/health-watch/health-watch-biz/src/main/java/com/renkang/watch/mapper/xml/WatchStatUserInfoDayTempMapper.xml
+++ b/health-watch/health-watch-biz/src/main/java/com/renkang/watch/mapper/xml/WatchStatUserInfoDayTempMapper.xml
@@ -34,68 +34,70 @@
         order by data_date
     </select>
 
+    <!-- 切记 此代码不能直接平移至四合一项目 ,该sql只适用mysql8.0及以上版本 ,四合一项目开发测试环境的mysql版本过低 , 但不影响正式环境-->
     <insert id="insertStat">
         insert into watch_stat_user_info_day_temp(id, user_id, max_value, min_value, avg_value, skin_max_value,
-        skin_min_value, skin_avg_value, last_upload_time, new_value, skin_new_value, data_date, org_code)
-        (select #{id,jdbcType=VARCHAR},
-        bind_user_id,
-        ifnull(max(data_value), 0),
-        ifnull(min(data_value), 0),
-        ifnull(avg(data_value), 0),
-        ifnull(max(skin_tempera), 0),
-        ifnull(min(skin_tempera), 0),
-        ifnull(avg(skin_tempera), 0),
-        ifnull(max(time_stamp), NOW()),
-        ifnull(data_value, 0),
-        ifnull(skin_tempera, 0),
-        data_date,
-        #{orgCode,jdbcType=VARCHAR}
-        from watch_data_temperature
-        where bind_user_id = #{userId,jdbcType=VARCHAR}
-        and data_date = #{dataDate,jdbcType=DATE}
-        group by bind_user_id, data_date);
+                                                  skin_min_value, skin_avg_value, last_upload_time, new_value,
+                                                  skin_new_value, data_date, org_code)
+            (SELECT #{id,jdbcType=VARCHAR},
+                    bind_user_id,
+                    IFNULL(MAX(wd.data_value), 0),
+                    IFNULL(MIN(wd.data_value), 0),
+                    IFNULL(AVG(wd.data_value), 0),
+                    IFNULL(MAX(wd.skin_tempera), 0),
+                    IFNULL(MIN(wd.skin_tempera), 0),
+                    IFNULL(AVG(wd.skin_tempera), 0),
+                    IFNULL(MAX(wd.time_stamp), NOW()),
+                    MAX(CASE WHEN wd.rn = 1 THEN wd.data_value END),
+                    MAX(CASE WHEN wd.rn = 1 THEN wd.skin_tempera END),
+                    data_date,
+                    #{orgCode,jdbcType=VARCHAR}
+             FROM (SELECT *, ROW_NUMBER() OVER ( PARTITION BY bind_user_id, data_date ORDER BY time_stamp DESC ) AS rn
+                   FROM watch_data_temperature
+                   where bind_user_id = #{userId,jdbcType=VARCHAR}
+                     and data_date = #{dataDate,jdbcType=DATE}) wd
+             GROUP BY wd.bind_user_id,
+                      wd.data_date);
     </insert>
 
+    <!-- 切记 此代码不能直接平移至四合一项目 ,该sql只适用mysql8.0及以上版本 ,四合一项目开发测试环境的mysql版本过低 , 但不影响正式环境-->
     <update id="updateStat">
-        update watch_stat_user_info_day_temp stat
-            left join (
-            select
+        UPDATE watch_stat_user_info_day_temp stat
+            LEFT JOIN (
+            SELECT
+            wd.bind_user_id,
+            wd.data_date,
+            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,
+            MAX( CASE WHEN wd.rn = 1 THEN wd.data_value END ) AS new_value,
+            MAX( CASE WHEN wd.rn = 1 THEN wd.skin_tempera END ) AS skin_new_value
+            FROM
+            ( SELECT *, ROW_NUMBER() OVER ( PARTITION BY bind_user_id, data_date ORDER BY time_stamp DESC ) AS rn FROM watch_data_temperature
+            where bind_user_id = #{userId,jdbcType=VARCHAR}
+            and data_date = #{dataDate,jdbcType=DATE}) wd
+            GROUP BY
             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
-            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,
-                stat.skin_max_value    = data.skin_max_value,
-                stat.skin_min_value    = data.skin_min_value,
-                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    = 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};
+            ) 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,
+                stat.skin_max_value = DATA.skin_max_value,
+                stat.skin_min_value = DATA.skin_min_value,
+                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 = COALESCE ( NULLIF( DATA.skin_new_value, 0 ), stat.skin_new_value ),
+                stat.org_code = #{orgCode,jdbcType=VARCHAR}
+             where stat.user_id = #{userId,jdbcType=VARCHAR}
+            and stat.data_date = #{dataDate,jdbcType=DATE};
     </update>
 </mapper>