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设备导入修改及最新值

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wanghao
2025-12-18 17:25:00 +08:00
parent 5d66a58af9
commit 66bb39bc18
4 changed files with 148 additions and 100 deletions
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health-watch/health-watch-biz/src/main/java/com/renkang/watch/mapper/xml/WatchStatUserInfoDayHeartRateMapper.xml
+27 -15
View File
@@ -358,21 +358,33 @@
<update id="updateStat"> <update id="updateStat">
update watch_stat_user_info_day_heart_rate stat update watch_stat_user_info_day_heart_rate stat
left join (select bind_user_id, left join (
ifnull(max(data_value), 0) as max_value, select
ifnull(min(data_value), 0) as min_value, wd.bind_user_id,
ifnull(avg(data_value), 0) as avg_value, ifnull(max(wd.data_value), 0) as max_value,
ifnull(max(silence_value), 0) as silence_max_value, ifnull(min(wd.data_value), 0) as min_value,
ifnull(min(silence_value), 0) as silence_min_value, ifnull(avg(wd.data_value), 0) as avg_value,
ifnull(avg(silence_value), 0) as silence_avg_value, ifnull(max(wd.silence_value), 0) as silence_max_value,
ifnull(max(time_stamp), NOW()) as last_upload_time, ifnull(min(wd.silence_value), 0) as silence_min_value,
ifnull(data_value, 0) as new_value, ifnull(avg(wd.silence_value), 0) as silence_avg_value,
ifnull(silence_value, 0) as silence_new_value, ifnull(max(wd.time_stamp), NOW()) as last_upload_time,
data_date 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 from watch_data_heart_rate
where bind_user_id = #{userId,jdbcType=VARCHAR} group by bind_user_id, data_date
and data_date = #{dataDate,jdbcType=DATE} )
group by bind_user_id, data_date) data on stat.user_id = data.bind_user_id ) 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, set stat.max_value = data.max_value,
stat.min_value = data.min_value, stat.min_value = data.min_value,
stat.avg_value = data.avg_value, stat.avg_value = data.avg_value,
@@ -381,7 +393,7 @@
stat.silence_avg_value = data.silence_avg_value, stat.silence_avg_value = data.silence_avg_value,
stat.last_upload_time = data.last_upload_time, stat.last_upload_time = data.last_upload_time,
stat.new_value = data.new_value, 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} stat.org_code = #{orgCode,jdbcType=VARCHAR}
where stat.user_id = #{userId,jdbcType=VARCHAR} where stat.user_id = #{userId,jdbcType=VARCHAR}
and stat.data_date = #{dataDate,jdbcType=DATE}; and stat.data_date = #{dataDate,jdbcType=DATE};
health-watch/health-watch-biz/src/main/java/com/renkang/watch/mapper/xml/WatchStatUserInfoDaySpo2Mapper.xml
+22 -10
View File
@@ -55,17 +55,29 @@
<update id="updateStat"> <update id="updateStat">
update watch_stat_user_info_day_spo2 stat update watch_stat_user_info_day_spo2 stat
left join (select bind_user_id, left join (
ifnull(max(data_value), 0) as max_value, select
ifnull(min(data_value), 0) as min_value, wd.bind_user_id,
ifnull(avg(data_value), 0) as avg_value, ifnull(max(wd.data_value), 0) as max_value,
ifnull(max(time_stamp), 0) as last_upload_time, ifnull(min(wd.data_value), 0) as min_value,
ifnull(data_value, 0) as new_value, ifnull(avg(wd.data_value), 0) as avg_value,
data_date 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 from watch_data_spo2
where bind_user_id = #{userId,jdbcType=VARCHAR} group by bind_user_id, data_date
and data_date = #{dataDate,jdbcType=DATE} )
group by bind_user_id, data_date) data on stat.user_id = data.bind_user_id ) 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, set stat.max_value = data.max_value,
stat.min_value = data.min_value, stat.min_value = data.min_value,
stat.avg_value = data.avg_value, stat.avg_value = data.avg_value,
health-watch/health-watch-biz/src/main/java/com/renkang/watch/mapper/xml/WatchStatUserInfoDayStressMapper.xml
+23 -11
View File
@@ -27,9 +27,9 @@
ifnull(max(data_value), 0), ifnull(max(data_value), 0),
ifnull(min(data_value), 0), ifnull(min(data_value), 0),
ifnull(avg(data_value), 0), ifnull(avg(data_value), 0),
data_date,
ifnull(max(end_time_stamp), NOW()), ifnull(max(end_time_stamp), NOW()),
ifnull(data_value, 0), ifnull(data_value, 0),
data_date,
#{orgCode,jdbcType=VARCHAR} #{orgCode,jdbcType=VARCHAR}
from watch_data_stress from watch_data_stress
where bind_user_id = #{userId,jdbcType=VARCHAR} where bind_user_id = #{userId,jdbcType=VARCHAR}
@@ -39,17 +39,29 @@
<update id="updateStat"> <update id="updateStat">
update watch_stat_user_info_day_stress stat update watch_stat_user_info_day_stress stat
left join (select bind_user_id, left join (
ifnull(max(data_value), 0) as max_value, select
ifnull(min(data_value), 0) as min_value, wd.bind_user_id,
ifnull(avg(data_value), 0) as avg_value, ifnull(max(wd.data_value), 0) as max_value,
ifnull(max(end_time_stamp), NOW()) as last_upload_time, ifnull(min(wd.data_value), 0) as min_value,
ifnull(data_value, 0) as new_value, ifnull(avg(wd.data_value), 0) as avg_value,
data_date 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 from watch_data_stress
where bind_user_id = #{userId,jdbcType=VARCHAR} group by bind_user_id, data_date
and data_date = #{dataDate,jdbcType=DATE} )
group by bind_user_id, data_date) data on stat.user_id = data.bind_user_id ) 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, set stat.max_value = data.max_value,
stat.min_value = data.min_value, stat.min_value = data.min_value,
stat.avg_value = data.avg_value, stat.avg_value = data.avg_value,
health-watch/health-watch-biz/src/main/java/com/renkang/watch/mapper/xml/WatchStatUserInfoDayTempMapper.xml
+27 -15
View File
@@ -58,21 +58,33 @@
<update id="updateStat"> <update id="updateStat">
update watch_stat_user_info_day_temp stat update watch_stat_user_info_day_temp stat
left join (select bind_user_id, left join (
ifnull(max(data_value), 0) as max_value, select
ifnull(min(data_value), 0) as min_value, wd.bind_user_id,
ifnull(avg(data_value), 0) as avg_value, ifnull(max(wd.data_value), 0) as max_value,
ifnull(max(skin_tempera), 0) as skin_max_value, ifnull(min(wd.data_value), 0) as min_value,
ifnull(min(skin_tempera), 0) as skin_min_value, ifnull(avg(wd.data_value), 0) as avg_value,
ifnull(avg(skin_tempera), 0) as skin_avg_value, ifnull(max(wd.skin_tempera), 0) as skin_max_value,
ifnull(max(time_stamp), NOW()) as last_upload_time, ifnull(min(wd.skin_tempera), 0) as skin_min_value,
ifnull(data_value, 0) as new_value, ifnull(avg(wd.skin_tempera), 0) as skin_avg_value,
ifnull(skin_tempera, 0) as skin_new_value, ifnull(max(wd.time_stamp), NOW()) as last_upload_time,
data_date 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 from watch_data_temperature
where bind_user_id = #{userId,jdbcType=VARCHAR} group by bind_user_id, data_date
and data_date = #{dataDate,jdbcType=DATE} )
group by bind_user_id, data_date) data on stat.user_id = data.bind_user_id ) 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, set stat.max_value = data.max_value,
stat.min_value = data.min_value, stat.min_value = data.min_value,
stat.avg_value = data.avg_value, stat.avg_value = data.avg_value,
@@ -81,7 +93,7 @@
stat.skin_avg_value = data.skin_avg_value, stat.skin_avg_value = data.skin_avg_value,
stat.last_upload_time = data.last_upload_time, stat.last_upload_time = data.last_upload_time,
stat.new_value = data.new_value, 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} stat.org_code = #{orgCode,jdbcType=VARCHAR}
where stat.user_id = #{userId,jdbcType=VARCHAR} where stat.user_id = #{userId,jdbcType=VARCHAR}
and stat.data_date = #{dataDate,jdbcType=DATE}; and stat.data_date = #{dataDate,jdbcType=DATE};