系列文章目录
线上问诊：业务数据采集
线上问诊：数仓数据同步
线上问诊：数仓开发(一)
线上问诊：数仓开发(二)
文章目录
- 系列文章目录
- 前言
- 一、DWS
- 1.最近1日汇总表
- 1.交易域医院患者性别年龄段粒度问诊最近1日汇总表
- 2.交易域医院患者性别年龄段粒度问诊支付成功最近1日汇总表
- 3.交易域医院患者性别年龄段粒度处方开单最近1日汇总表
- 4.交易域医院患者性别年龄段粒度处方开单支付成功最近1日汇总表
- 5.交易域医生粒度问诊最近1日汇总表
- 6.首日装载脚本
- 7.每日数据装载
- 2.最近n日汇总表
- 1.交易域医院患者性别年龄段粒度问诊最近n日汇总表
- 2.交易域医院患者性别年龄段粒度问诊支付成功最近n日汇总表
- 3.交易域医院患者性别年龄段粒度处方开单最近n日汇总表
- 4.交易域医院患者性别年龄段粒度处方开单支付成功最近n日汇总表
- 5.交易域医生粒度问诊最近n日汇总表
- 6.首日装载脚本
- 3.历史至今汇总表
- 1.交易域医生粒度问诊历史至今汇总表
- 2.互动域医院用户粒度用户评价历史至今汇总表
- 3.互动域医院粒度用户评价历史至今汇总表
- 4.首日数据装载
- 5.每日数据装载
- 总结
前言
我们这次博客继续完成数仓的开发
一、DWS
1.最近1日汇总表
1.交易域医院患者性别年龄段粒度问诊最近1日汇总表
建表语句
CREATE EXTERNAL TABLE IF NOT EXISTS dws_trade_hospital_gender_age_group_consultation_1d
(
`hospital_id` STRING COMMENT '医院ID',
`hospital_name` STRING COMMENT '医院名称',
`gender_code` STRING COMMENT '患者性别编码',
`gender` STRING COMMENT '患者性别',
`age_group` STRING COMMENT '年龄段：[0,2]婴儿期, [3,5]幼儿期, [6,11]小学阶段, [12,17]青少年期(中学阶段), [18-29]青年期, [30-59]中年期, [60-122]老年期',
`consultation_amount` DECIMAL(16, 2) COMMENT '问诊金额',
`consultation_count` BIGINT COMMENT '问诊次数'
) COMMENT '交易域医院患者性别年龄段粒度问诊最近1日汇总表'
PARTITIONED BY (`dt` STRING)
STORED AS ORC
LOCATION '/warehouse/medical/dws/dws_trade_hospital_gender_age_group_consultation_1d'
TBLPROPERTIES ('orc.compress' = 'snappy');
2.交易域医院患者性别年龄段粒度问诊支付成功最近1日汇总表
建表语句
CREATE EXTERNAL TABLE IF NOT EXISTS dws_trade_hospital_gender_age_group_consultation_pay_suc_1d
(
`hospital_id` STRING COMMENT '医院ID',
`hospital_name` STRING COMMENT '医院名称',
`gender_code` STRING COMMENT '患者性别编码',
`gender` STRING COMMENT '患者性别',
`age_group` STRING COMMENT '年龄段：[0,2]婴儿期, [3,5]幼儿期, [6,11]小学阶段, [12,17]青少年期(中学阶段), [18-29]青年期, [30-59]中年期, [60-]老年期',
`consultation_pay_suc_amount` DECIMAL(16, 2) COMMENT '问诊支付成功金额',
`consultation_pay_suc_count` BIGINT COMMENT '问诊支付成功次数'
) COMMENT '交易域医院患者性别年龄段粒度问诊支付成功最近1日汇总表'
PARTITIONED BY (`dt` STRING)
STORED AS ORC
LOCATION '/warehouse/medical/dws/dws_trade_hospital_gender_age_group_consultation_pay_suc_1d'
TBLPROPERTIES ('orc.compress' = 'snappy');
3.交易域医院患者性别年龄段粒度处方开单最近1日汇总表
建表语句
CREATE EXTERNAL TABLE IF NOT EXISTS dws_trade_hospital_gender_age_group_prescription_1d
(
`hospital_id` STRING COMMENT '医院ID',
`hospital_name` STRING COMMENT '医院名称',
`gender_code` STRING COMMENT '患者性别编码',
`gender` STRING COMMENT '患者性别',
`age_group` STRING COMMENT '年龄段：[0,2]婴儿期, [3,5]幼儿期, [6,11]小学阶段, [12,17]青少年期(中学阶段), [18-29]青年期, [30-59]中年期, [60-]老年期',
`prescription_amount` DECIMAL(16, 2) COMMENT '处方开单金额',
`prescription_count` BIGINT COMMENT '处方开单次数'
) COMMENT '交易域医院患者性别年龄段粒度处方开单最近1日汇总表'
PARTITIONED BY (`dt` STRING)
STORED AS ORC
LOCATION '/warehouse/medical/dws/dws_trade_hospital_gender_age_group_prescription_1d'
TBLPROPERTIES ('orc.compress' = 'snappy');
4.交易域医院患者性别年龄段粒度处方开单支付成功最近1日汇总表
建表语句
CREATE EXTERNAL TABLE IF NOT EXISTS dws_trade_hospital_gender_age_group_prescription_pay_suc_1d
(
`hospital_id` STRING COMMENT '医院ID',
`hospital_name` STRING COMMENT '医院名称',
`gender_code` STRING COMMENT '患者性别编码',
`gender` STRING COMMENT '患者性别',
`age_group` STRING COMMENT '年龄段：[0,2]婴儿期, [3,5]幼儿期, [6,11]小学阶段, [12,17]青少年期(中学阶段), [18-29]青年期, [30-59]中年期, [60-]老年期',
`prescription_pay_suc_amount` DECIMAL(16, 2) COMMENT '处方开单支付成功金额',
`prescription_pay_suc_count` BIGINT COMMENT '处方开单支付成功次数'
) COMMENT '交易域医院患者性别年龄段粒度处方开单支付成功最近1日汇总表'
PARTITIONED BY (`dt` STRING)
STORED AS ORC
LOCATION '/warehouse/medical/dws/dws_trade_hospital_gender_age_group_prescription_pay_suc_1d'
TBLPROPERTIES ('orc.compress' = 'snappy');
5.交易域医生粒度问诊最近1日汇总表
建表语句
CREATE EXTERNAL TABLE IF NOT EXISTS dws_trade_doctor_consultation_1d
(
`doctor_id` STRING COMMENT '医生ID',
`doctor_name` STRING COMMENT '医生姓名',
`consultation_count` BIGINT COMMENT '接诊次数'
) COMMENT '交易域医生粒度问诊最近1日汇总表'
PARTITIONED BY (`dt` STRING)
STORED AS ORC
LOCATION '/warehouse/medical/dws/dws_trade_doctor_consultation_1d'
TBLPROPERTIES ('orc.compress' = 'snappy');
6.首日装载脚本
vim ~/bin/medical_dwd_to_dws_1d_init.sh
#!/bin/bash
APP=medical
if [ -n $2 ]
then
do_date=$2
else
echo "请传入日期参数！！！"
exit
fi
dws_trade_hospital_gender_age_group_consultation_1d="
set hive.exec.dynamic.partition.mode=nonstrict;
insert overwrite table ${APP}.dws_trade_hospital_gender_age_group_consultation_1d
partition (dt)
select hospital_id,
hospital_name,
gender_code,
gender,
age_group,
sum(consultation_fee) consultation_amount,
count(*) consultation_count,
dt
from (select hospital_id,
hospital_name,
gender_code,
gender,
case
when age >= 0 and age <= 2 then '婴儿期'
when age >= 3 and age <= 5 then '幼儿期'
when age >= 6 and age <= 11 then '小学阶段'
when age >= 12 and age <= 17 then '青少年期（中学阶段）'
when age >= 18 and age <= 29 then '青年期'
when age >= 30 and age <= 59 then '中年期'
when age >= 60 and age <= 122 then '老年期'
else '年龄异常' end age_group,
consultation_fee,
dt
from (select doctor_id,
patient_id,
consultation_fee,
dt
from ${APP}.dwd_trade_consultation_inc) consul
left join
(select id,
hospital_id
from ${APP}.dim_doctor_full
where dt = '$do_date') doc
on doctor_id = doc.id
left join (select id,
name hospital_name
from ${APP}.dim_hospital_full
where dt = '$do_date') hos
on doc.hospital_id = hos.id
left join
(select id,
gender_code,
gender,
year('$do_date') - year(birthday) age
from ${APP}.dim_patient_full
where dt = '$do_date') patient
on patient_id = patient.id) with_group
group by hospital_id,
hospital_name,
gender_code,
gender,
age_group,
dt;
"
dws_trade_hospital_gender_age_group_consultation_pay_suc_1d="
set hive.exec.dynamic.partition.mode=nonstrict;
insert overwrite table ${APP}.dws_trade_hospital_gender_age_group_consultation_pay_suc_1d
partition (dt)
select hospital_id,
hospital_name,
gender_code,
gender,
age_group,
sum(consultation_fee) consultation_pay_suc_amount,
count(*) consultation_pay_suc_count,
dt
from (select hospital_id,
hospital_name,
gender_code,
gender,
case
when age >= 0 and age <= 2 then '婴儿期'
when age >= 3 and age <= 5 then '幼儿期'
when age >= 6 and age <= 11 then '小学阶段'
when age >= 12 and age <= 17 then '青少年期（中学阶段）'
when age >= 18 and age <= 29 then '青年期'
when age >= 30 and age <= 59 then '中年期'
when age >= 60 and age <= 122 then '老年期'
else '年龄异常' end age_group,
consultation_fee,
dt
from (select doctor_id,
patient_id,
consultation_fee,
dt
from ${APP}.dwd_trade_consultation_pay_suc_inc) consul
left join
(select id,
hospital_id
from ${APP}.dim_doctor_full
where dt = '$do_date') doc
on doctor_id = doc.id
left join (select id,
name hospital_name
from ${APP}.dim_hospital_full
where dt = '$do_date') hos
on doc.hospital_id = hos.id
left join
(select id,
gender_code,
gender,
year('$do_date') - year(birthday) age
from ${APP}.dim_patient_full
where dt = '$do_date') patient
on patient_id = patient.id) with_group
group by hospital_id,
hospital_name,
gender_code,
gender,
age_group,
dt;
"
dws_trade_hospital_gender_age_group_prescription_1d="
set hive.exec.dynamic.partition.mode=nonstrict;
insert overwrite table ${APP}.dws_trade_hospital_gender_age_group_prescription_1d
partition (dt)
select hospital_id,
hospital_name,
gender_code,
gender,
age_group,
sum(total_amount) prescription_amount,
count(*) prescription_count,
dt
from (select hospital_id,
hospital_name,
gender_code,
gender,
case
when age >= 0 and age <= 2 then '婴儿期'
when age >= 3 and age <= 5 then '幼儿期'
when age >= 6 and age <= 11 then '小学阶段'
when age >= 12 and age <= 17 then '青少年期（中学阶段）'
when age >= 18 and age <= 29 then '青年期'
when age >= 30 and age <= 59 then '中年期'
when age >= 60 and age <= 122 then '老年期'
else '年龄异常' end age_group,
total_amount,
dt
from (select max(doctor_id) doctor_id,
max(patient_id) patient_id,
max(total_amount) total_amount,
max(dt) dt
from ${APP}.dwd_trade_prescription_inc
group by prescription_id) prescr
left join
(select id,
hospital_id
from ${APP}.dim_doctor_full
where dt = '$do_date') doc
on doctor_id = doc.id
left join (select id,
name hospital_name
from ${APP}.dim_hospital_full
where dt = '$do_date') hos
on doc.hospital_id = hos.id
left join
(select id,
gender_code,
gender,
year('$do_date') - year(birthday) age
from ${APP}.dim_patient_full
where dt = '$do_date') patient
on patient_id = patient.id) with_group
group by hospital_id,
hospital_name,
gender_code,
gender,
age_group,
dt;
"
dws_trade_hospital_gender_age_group_prescription_pay_suc_1d="
set hive.exec.dynamic.partition.mode=nonstrict;
insert overwrite table ${APP}.dws_trade_hospital_gender_age_group_prescription_pay_suc_1d
partition (dt)
select hospital_id,
hospital_name,
gender_code,
gender,
age_group,
sum(total_amount) prescription_pay_suc_amount,
count(*) prescription_pay_suc_count,
dt
from (select hospital_id,
hospital_name,
gender_code,
gender,
case
when age >= 0 and age <= 2 then '婴儿期'
when age >= 3 and age <= 5 then '幼儿期'
when age >= 6 and age <= 11 then '小学阶段'
when age >= 12 and age <= 17 then '青少年期（中学阶段）'
when age >= 18 and age <= 29 then '青年期'
when age >= 30 and age <= 59 then '中年期'
when age >= 60 and age <= 122 then '老年期'
else '年龄异常' end age_group,
total_amount,
dt
from (select max(doctor_id) doctor_id,
max(patient_id) patient_id,
max(total_amount) total_amount,
max(dt) dt
from ${APP}.dwd_trade_prescription_pay_suc_inc
group by prescription_id) prescr
left join
(select id,
hospital_id
from ${APP}.dim_doctor_full
where dt = '$do_date') doc
on doctor_id = doc.id
left join (select id,
name hospital_name
from ${APP}.dim_hospital_full
where dt = '$do_date') hos
on doc.hospital_id = hos.id
left join
(select id,
gender_code,
gender,
year('$do_date') - year(birthday) age
from ${APP}.dim_patient_full
where dt = '$do_date') patient
on patient_id = patient.id) with_group
group by hospital_id,
hospital_name,
gender_code,
gender,
age_group,
dt;
"
dws_trade_doctor_consultation_1d="
set hive.exec.dynamic.partition.mode=nonstrict;
insert overwrite table ${APP}.dws_trade_doctor_consultation_1d
partition (dt)
select doctor_id,
name doctor_name,
consultation_count,
dt
from (select doctor_id,
dt,
count(*) consultation_count
from ${APP}.dwd_trade_consultation_inc
group by doctor_id,
dt) avg
left join (select id,
name
from ${APP}.dim_doctor_full
where dt = '$do_date') doc
on avg.doctor_id = doc.id;
"
case $1 in
dws_trade_hospital_gender_age_group_consultation_1d | dws_trade_hospital_gender_age_group_consultation_pay_suc_1d | dws_trade_hospital_gender_age_group_prescription_1d | dws_trade_hospital_gender_age_group_prescription_pay_suc_1d | dws_trade_doctor_consultation_1d)
hive -e "${!1}"
;;
"all")
hive -e "$dws_trade_hospital_gender_age_group_consultation_1d$dws_trade_hospital_gender_age_group_consultation_pay_suc_1d$dws_trade_hospital_gender_age_group_prescription_1d$dws_trade_hospital_gender_age_group_prescription_pay_suc_1d$dws_trade_doctor_consultation_1d"
;;
esac
添加权限
chmod +x ~/bin/medical_dwd_to_dws_1d_init.sh
数据载入
medical_dwd_to_dws_1d_init.sh all 2023-05-09
随便找一个查看一下最后的日期
7.每日数据装载
vim ~/bin/medical_dwd_to_dws_1d.sh
#!/bin/bash
APP=medical
if [ -n $2 ]
then
do_date=$2
else
echo "请传入日期参数！！！"
exit
fi
dws_trade_hospital_gender_age_group_consultation_1d="
insert overwrite table ${APP}.dws_trade_hospital_gender_age_group_consultation_1d
partition (dt = '$do_date')
select hospital_id,
hospital_name,
gender_code,
gender,
age_group,
sum(consultation_fee) consultation_amount,
count(*) consultation_count
from (select hospital_id,
hospital_name,
gender_code,
gender,
case
when age >= 0 and age <= 2 then '婴儿期'
when age >= 3 and age <= 5 then '幼儿期'
when age >= 6 and age <= 11 then '小学阶段'
when age >= 12 and age <= 17 then '青少年期（中学阶段）'
when age >= 18 and age <= 29 then '青年期'
when age >= 30 and age <= 59 then '中年期'
when age >= 60 and age <= 122 then '老年期'
else '年龄异常' end age_group,
consultation_fee
from (select doctor_id,
patient_id,
consultation_fee
from ${APP}.dwd_trade_consultation_inc
where dt = '$do_date') consul
left join
(select id,
hospital_id
from ${APP}.dim_doctor_full
where dt = '$do_date') doc
on doctor_id = doc.id
left join (select id,
name hospital_name
from ${APP}.dim_hospital_full
where dt = '$do_date') hos
on doc.hospital_id = hos.id
left join
(select id,
gender_code,
gender,
year('$do_date') - year(birthday) age
from ${APP}.dim_patient_full
where dt = '$do_date') patient
on patient_id = patient.id) with_group
group by hospital_id,
hospital_name,
gender_code,
gender,
age_group;"
dws_trade_hospital_gender_age_group_consultation_pay_suc_1d="
insert overwrite table ${APP}.dws_trade_hospital_gender_age_group_consultation_pay_suc_1d
partition (dt = '$do_date')
select hospital_id,
hospital_name,
gender_code,
gender,
age_group,
sum(consultation_fee) consultation_pay_suc_amount,
count(*) consultation_pay_suc_count
from (select hospital_id,
hospital_name,
gender_code,
gender,
case
when age >= 0 and age <= 2 then '婴儿期'
when age >= 3 and age <= 5 then '幼儿期'
when age >= 6 and age <= 11 then '小学阶段'
when age >= 12 and age <= 17 then '青少年期（中学阶段）'
when age >= 18 and age <= 29 then '青年期'
when age >= 30 and age <= 59 then '中年期'
when age >= 60 and age <= 122 then '老年期'
else '年龄异常' end age_group,
consultation_fee
from (select doctor_id,
patient_id,
consultation_fee
from ${APP}.dwd_trade_consultation_pay_suc_inc
where dt = '$do_date') consul
left join
(select id,
hospital_id
from ${APP}.dim_doctor_full
where dt = '$do_date') doc
on doctor_id = doc.id
left join (select id,
name hospital_name
from ${APP}.dim_hospital_full
where dt = '$do_date') hos
on doc.hospital_id = hos.id
left join
(select id,
gender_code,
gender,
year('$do_date') - year(birthday) age
from ${APP}.dim_patient_full
where dt = '$do_date') patient
on patient_id = patient.id) with_group
group by hospital_id,
hospital_name,
gender_code,
gender,
age_group;"
dws_trade_hospital_gender_age_group_prescription_1d="
insert overwrite table ${APP}.dws_trade_hospital_gender_age_group_prescription_1d
partition (dt = '$do_date')
select hospital_id,
hospital_name,
gender_code,
gender,
age_group,
sum(total_amount) prescription_amount,
count(*) prescription_count
from (select hospital_id,
hospital_name,
gender_code,
gender,
case
when age >= 0 and age <= 2 then '婴儿期'
when age >= 3 and age <= 5 then '幼儿期'
when age >= 6 and age <= 11 then '小学阶段'
when age >= 12 and age <= 17 then '青少年期（中学阶段）'
when age >= 18 and age <= 29 then '青年期'
when age >= 30 and age <= 59 then '中年期'
when age >= 60 and age <= 122 then '老年期'
else '年龄异常' end age_group,
total_amount
from (select max(doctor_id) doctor_id,
max(patient_id) patient_id,
max(total_amount) total_amount
from ${APP}.dwd_trade_prescription_inc
where dt = '$do_date'
group by prescription_id) prescr
left join
(select id,
hospital_id
from ${APP}.dim_doctor_full
where dt = '$do_date') doc
on doctor_id = doc.id
left join (select id,
name hospital_name
from ${APP}.dim_hospital_full
where dt = '$do_date') hos
on doc.hospital_id = hos.id
left join
(select id,
gender_code,
gender,
year('$do_date') - year(birthday) age
from ${APP}.dim_patient_full
where dt = '$do_date') patient
on patient_id = patient.id) with_group
group by hospital_id,
hospital_name,
gender_code,
gender,
age_group;"
dws_trade_hospital_gender_age_group_prescription_pay_suc_1d="
insert overwrite table ${APP}.dws_trade_hospital_gender_age_group_prescription_pay_suc_1d
partition (dt = '$do_date')
select hospital_id,
hospital_name,
gender_code,
gender,
age_group,
sum(total_amount) prescription_pay_suc_amount,
count(*) prescription_pay_suc_count
from (select hospital_id,
hospital_name,
gender_code,
gender,
case
when age >= 0 and age <= 2 then '婴儿期'
when age >= 3 and age <= 5 then '幼儿期'
when age >= 6 and age <= 11 then '小学阶段'
when age >= 12 and age <= 17 then '青少年期（中学阶段）'
when age >= 18 and age <= 29 then '青年期'
when age >= 30 and age <= 59 then '中年期'
when age >= 60 and age <= 122 then '老年期'
else '年龄异常' end age_group,
total_amount
from (select max(doctor_id) doctor_id,
max(patient_id) patient_id,
max(total_amount) total_amount
from ${APP}.dwd_trade_prescription_inc
where dt = '$do_date'
group by prescription_id) prescr
left join
(select id,
hospital_id
from ${APP}.dim_doctor_full
where dt = '$do_date') doc
on doctor_id = doc.id
left join (select id,
name hospital_name
from ${APP}.dim_hospital_full
where dt = '$do_date') hos
on doc.hospital_id = hos.id
left join
(select id,
gender_code,
gender,
year('$do_date') - year(birthday) age
from ${APP}.dim_patient_full
where dt = '$do_date') patient
on patient_id = patient.id) with_group
group by hospital_id,
hospital_name,
gender_code,
gender,
age_group;"
dws_trade_doctor_consultation_1d="
insert overwrite table ${APP}.dws_trade_doctor_consultation_1d
partition (dt = '$do_date')
select doctor_id,
name doctor_name,
consultation_count
from (select doctor_id,
count(*) consultation_count
from ${APP}.dwd_trade_consultation_inc
where dt = '$do_date'
group by doctor_id) avg
left join (select id,
name
from ${APP}.dim_doctor_full
where dt = '$do_date') doc
on avg.doctor_id = doc.id;"
case $1 in
dws_trade_hospital_gender_age_group_consultation_1d | dws_trade_hospital_gender_age_group_consultation_pay_suc_1d | dws_trade_hospital_gender_age_group_prescription_1d | dws_trade_hospital_gender_age_group_prescription_pay_suc_1d | dws_trade_doctor_consultation_1d)
hive -e "${!1}"
;;
"all")
hive -e "$dws_trade_hospital_gender_age_group_consultation_1d$dws_trade_hospital_gender_age_group_consultation_pay_suc_1d$dws_trade_hospital_gender_age_group_prescription_1d$dws_trade_hospital_gender_age_group_prescription_pay_suc_1d$dws_trade_doctor_consultation_1d"
;;
esac
添加权限
chmod +x ~/bin/medical_dwd_to_dws_1d.sh
2.最近n日汇总表
1.交易域医院患者性别年龄段粒度问诊最近n日汇总表
建表语句
CREATE EXTERNAL TABLE IF NOT EXISTS dws_trade_hospital_gender_age_group_consultation_nd
(
`hospital_id` STRING COMMENT '医院ID',
`hospital_name` STRING COMMENT '医院名称',
`gender_code` STRING COMMENT '患者性别编码',
`gender` STRING COMMENT '患者性别',
`age_group` STRING COMMENT '年龄段：[0,2]婴儿期, [3,5]幼儿期, [6,11]小学阶段, [12,17]青少年期(中学阶段), [18-29]青年期, [30-59]中年期, [60-122]老年期',
`consultation_amount_7d` DECIMAL(16, 2) COMMENT '最近 7 日问诊金额',
`consultation_count_7d` BIGINT COMMENT '最近 7 日问诊次数',
`consultation_amount_30d` DECIMAL(16, 2) COMMENT '最近 30 日问诊金额',
`consultation_count_30d` BIGINT COMMENT '最近 30 日问诊次数'
) COMMENT '交易域医院患者性别年龄段粒度问诊最近n日汇总表'
PARTITIONED BY (`dt` STRING)
STORED AS ORC
LOCATION '/warehouse/medical/dws/dws_trade_hospital_gender_age_group_consultation_nd'
TBLPROPERTIES ('orc.compress' = 'snappy');
2.交易域医院患者性别年龄段粒度问诊支付成功最近n日汇总表
建表语句
CREATE EXTERNAL TABLE IF NOT EXISTS dws_trade_hospital_gender_age_group_consultation_pay_suc_nd
(
`hospital_id` STRING COMMENT '医院ID',
`hospital_name` STRING COMMENT '医院名称',
`gender_code` STRING COMMENT '患者性别编码',
`gender` STRING COMMENT '患者性别',
`age_group` STRING COMMENT '年龄段：[0,2]婴儿期, [3,5]幼儿期, [6,11]小学阶段, [12,17]青少年期(中学阶段), [18-29]青年期, [30-59]中年期, [60-]老年期',
`consultation_pay_suc_amount_7d` DECIMAL(16, 2) COMMENT '最近 7 日问诊支付成功金额',
`consultation_pay_suc_count_7d` BIGINT COMMENT '最近 7 日问诊支付成功次数',
`consultation_pay_suc_amount_30d` DECIMAL(16, 2) COMMENT '最近 30 日问诊支付成功金额',
`consultation_pay_suc_count_30d` BIGINT COMMENT '最近 30 日问诊支付成功次数'
) COMMENT '交易域医院患者性别年龄段粒度问诊支付成功最近n日汇总表'
PARTITIONED BY (`dt` STRING)
STORED AS ORC
LOCATION '/warehouse/medical/dws/dws_trade_hospital_gender_age_group_consultation_pay_suc_nd'
TBLPROPERTIES ('orc.compress' = 'snappy');
3.交易域医院患者性别年龄段粒度处方开单最近n日汇总表
建表语句
CREATE EXTERNAL TABLE IF NOT EXISTS dws_trade_hospital_gender_age_group_prescription_nd
(
`hospital_id` STRING COMMENT '医院ID',
`hospital_name` STRING COMMENT '医院名称',
`gender_code` STRING COMMENT '患者性别编码',
`gender` STRING COMMENT '患者性别',
`age_group` STRING COMMENT '年龄段：[0,2]婴儿期, [3,5]幼儿期, [6,11]小学阶段, [12,17]青少年期(中学阶段), [18-29]青年期, [30-59]中年期, [60-]老年期',
`prescription_amount_7d` DECIMAL(16, 2) COMMENT '最近 7 日处方开单金额',
`prescription_count_7d` BIGINT COMMENT '最近 7 日处方开单次数',
`prescription_amount_30d` DECIMAL(16, 2) COMMENT '最近 30 日处方开单金额',
`prescription_count_30d` BIGINT COMMENT '最近 30 日处方开单次数'
) COMMENT '交易域医院患者性别年龄段粒度处方开单最近n日汇总表'
PARTITIONED BY (`dt` STRING)
STORED AS ORC
LOCATION '/warehouse/medical/dws/dws_trade_hospital_gender_age_group_prescription_nd'
TBLPROPERTIES ('orc.compress' = 'snappy');
4.交易域医院患者性别年龄段粒度处方开单支付成功最近n日汇总表
建表语句
CREATE EXTERNAL TABLE IF NOT EXISTS dws_trade_hospital_gender_age_group_prescription_pay_suc_nd
(
`hospital_id` STRING COMMENT '医院ID',
`hospital_name` STRING COMMENT '医院名称',
`gender_code` STRING COMMENT '患者性别编码',
`gender` STRING COMMENT '患者性别',
`age_group` STRING COMMENT '年龄段：[0,2]婴儿期, [3,5]幼儿期, [6,11]小学阶段, [12,17]青少年期(中学阶段), [18-29]青年期, [30-59]中年期, [60-]老年期',
`prescription_pay_suc_amount_7d` DECIMAL(16, 2) COMMENT '最近 7 日处方开单支付成功金额',
`prescription_pay_suc_count_7d` BIGINT COMMENT '最近 7 日处方开单支付成功次数',
`prescription_pay_suc_amount_30d` DECIMAL(16, 2) COMMENT '最近 30 日处方开单支付成功金额',
`prescription_pay_suc_count_30d` BIGINT COMMENT '最近 30 日处方开单支付成功次数'
) COMMENT '交易域医院患者性别年龄段粒度处方开单支付成功最近n日汇总表'
PARTITIONED BY (`dt` STRING)
STORED AS ORC
LOCATION '/warehouse/medical/dws/dws_trade_hospital_gender_age_group_prescription_pay_suc_nd'
TBLPROPERTIES ('orc.compress' = 'snappy');
5.交易域医生粒度问诊最近n日汇总表
建表语句
CREATE EXTERNAL TABLE IF NOT EXISTS dws_trade_doctor_consultation_nd
(
`doctor_id` STRING COMMENT '医生ID',
`doctor_name` STRING COMMENT '医生姓名',
`consultation_count_7d` BIGINT COMMENT '最近 7 日接诊次数',
`consultation_count_30d` BIGINT COMMENT '最近 30 日接诊次数'
) COMMENT '交易域医生粒度问诊最近n日汇总表'
PARTITIONED BY (`dt` STRING)
STORED AS ORC
LOCATION '/warehouse/medical/dws/dws_trade_doctor_consultation_nd'
TBLPROPERTIES ('orc.compress' = 'snappy');
6.首日装载脚本
vim ~/bin/medical_dws_1d_to_dws_nd.sh
#!/bin/bash
APP=medical
if [ -n $2 ]
then
do_date=$2
else
echo "请传入日期参数！！！"
exit
fi
dws_trade_hospital_gender_age_group_consultation_nd="
insert overwrite table ${APP}.dws_trade_hospital_gender_age_group_consultation_nd
partition (dt = '$do_date')
select hospital_id,
hospital_name,
gender_code,
gender,
age_group,
sum(if(dt >= date_add('$do_date', -6), consultation_amount, 0)) consultation_amount_7d,
sum(if(dt >= date_add('$do_date', -6), consultation_count, 0)) consultation_count_7d,
sum(consultation_amount) consultation_amount_30d,
sum(consultation_count) consultation_count_30d
from ${APP}.dws_trade_hospital_gender_age_group_consultation_1d
where dt >= date_add('$do_date', -29)
group by hospital_id,
hospital_name,
gender_code,
gender,
age_group;
"
dws_trade_hospital_gender_age_group_consultation_pay_suc_nd="
insert overwrite table ${APP}.dws_trade_hospital_gender_age_group_consultation_pay_suc_nd
partition (dt = '$do_date')
select hospital_id,
hospital_name,
gender_code,
gender,
age_group,
sum(if(dt >= date_add('$do_date', -6), consultation_pay_suc_amount, 0)) consultation_pay_suc_amount_7d,
sum(if(dt >= date_add('$do_date', -6), consultation_pay_suc_count, 0)) consultation_pay_suc_count_7d,
sum(consultation_pay_suc_amount) consultation_pay_suc_amount_30d,
sum(consultation_pay_suc_count) consultation_pay_suc_count_30d
from ${APP}.dws_trade_hospital_gender_age_group_consultation_pay_suc_1d
where dt >= date_add('$do_date', -29)
group by hospital_id,
hospital_name,
gender_code,
gender,
age_group;
"
dws_trade_hospital_gender_age_group_prescription_nd="
insert overwrite table ${APP}.dws_trade_hospital_gender_age_group_prescription_nd
partition (dt = '$do_date')
select hospital_id,
hospital_name,
gender_code,
gender,
age_group,
sum(if(dt >= date_add('$do_date', -6), prescription_amount, 0)) prescription_amount_7d,
sum(if(dt >= date_add('$do_date', -6), prescription_count, 0)) prescription_count_7d,
sum(prescription_amount) prescription_amount_30d,
sum(prescription_count) prescription_count_30d
from ${APP}.dws_trade_hospital_gender_age_group_prescription_1d
where dt >= date_add('$do_date', -29)
group by hospital_id,
hospital_name,
gender_code,
gender,
age_group;
"
dws_trade_hospital_gender_age_group_prescription_pay_suc_nd="
insert overwrite table ${APP}.dws_trade_hospital_gender_age_group_prescription_pay_suc_nd
partition (dt = '$do_date')
select hospital_id,
hospital_name,
gender_code,
gender,
age_group,
sum(if(dt >= date_add('$do_date', -6), prescription_pay_suc_amount, 0)) prescription_pay_suc_amount_7d,
sum(if(dt >= date_add('$do_date', -6), prescription_pay_suc_count, 0)) prescription_pay_suc_count_7d,
sum(prescription_pay_suc_amount) prescription_pay_suc_amount_30d,
sum(prescription_pay_suc_count) prescription_pay_suc_count_30d
from ${APP}.dws_trade_hospital_gender_age_group_prescription_pay_suc_1d
where dt >= date_add('$do_date', -29)
group by hospital_id,
hospital_name,
gender_code,
gender,
age_group;
"
dws_trade_doctor_consultation_nd="
insert overwrite table ${APP}.dws_trade_doctor_consultation_nd
partition (dt = '$do_date')
select doctor_id,
doctor_name,
sum(if(dt >= date_add('$do_date', -6), consultation_count, 0)) consultation_count_7d,
sum(consultation_count) consultation_count_30d
from ${APP}.dws_trade_doctor_consultation_1d
where dt >= date_add('$do_date', -29)
group by doctor_id,
doctor_name;
"
case $1 in
dws_trade_hospital_gender_age_group_consultation_nd | dws_trade_hospital_gender_age_group_consultation_pay_suc_nd | dws_trade_hospital_gender_age_group_prescription_nd | dws_trade_hospital_gender_age_group_prescription_pay_suc_nd | dws_trade_doctor_consultation_nd)
hive -e "${!1}"
;;
"all")
hive -e "$dws_trade_hospital_gender_age_group_consultation_nd$dws_trade_hospital_gender_age_group_consultation_pay_suc_nd$dws_trade_hospital_gender_age_group_prescription_nd$dws_trade_hospital_gender_age_group_prescription_pay_suc_nd$dws_trade_doctor_consultation_nd"
;;
"*")
echo "非法参数！！！"
;;
esac
添加权限
chmod +x ~/bin/medical_dws_1d_to_dws_nd.sh
数据装载
medical_dws_1d_to_dws_nd.sh all 2023-05-09
3.历史至今汇总表
1.交易域医生粒度问诊历史至今汇总表
建表语句
CREATE TABLE IF NOT EXISTS dws_trade_doctor_consultation_td(
`doctor_id` STRING COMMENT '医生ID',
`doctor_name` STRING COMMENT '医生姓名',
`first_consultation_dt` STRING COMMENT '首次接诊日期'
) COMMENT '交易域医生粒度问诊历史至今汇总表'
PARTITIONED BY (`dt` STRING)
STORED AS ORC
LOCATION '/warehouse/medical/dws/dws_trade_doctor_consultation_td'
TBLPROPERTIES ('orc.compress' = 'snappy');
2.互动域医院用户粒度用户评价历史至今汇总表
建表语句
CREATE TABLE IF NOT EXISTS dws_interaction_hospital_user_review_td(
`hospital_id` STRING COMMENT '医院ID',
`hospital_name` STRING COMMENT '医院名称',
`user_id` STRING COMMENT '用户ID',
`username` STRING COMMENT '用户姓名',
`first_review_dt` STRING COMMENT '首次评价日期'
) COMMENT '互动域医院用户粒度用户评价历史至今汇总表'
PARTITIONED BY (`dt` STRING)
STORED AS ORC
LOCATION '/warehouse/medical/dws/dws_interaction_hospital_user_review_td'
TBLPROPERTIES ('orc.compress' = 'snappy');
3.互动域医院粒度用户评价历史至今汇总表
建表语句
CREATE TABLE IF NOT EXISTS dws_interaction_hospital_review_td(
`hospital_id` STRING COMMENT '医院ID',
`hospital_name` STRING COMMENT '医院名称',
`review_count` BIGINT COMMENT '评价次数',
`good_review_count` BIGINT COMMENT '好评次数'
) COMMENT '互动域医院粒度用户评价历史至今汇总表'
PARTITIONED BY (`dt` STRING)
STORED AS ORC
LOCATION '/warehouse/medical/dws/dws_interaction_hospital_review_td'
TBLPROPERTIES ('orc.compress' = 'snappy');
4.首日数据装载
vim ~/bin/medical_dws_1d_to_dws_td_init.sh
#!/bin/bash
APP=medical
if [ -n $2 ]
then
do_date=$2
else
echo "请传入日期参数！！！"
exit
fi
dws_trade_doctor_consultation_td="
insert overwrite table ${APP}.dws_trade_doctor_consultation_td
partition (dt = '$do_date')
select doctor_id,
doctor_name,
min(dt) first_consultation_dt
from ${APP}.dws_trade_doctor_consultation_1d
group by doctor_id,
doctor_name;
"
dws_interaction_hospital_user_review_td="
insert overwrite table ${APP}.dws_interaction_hospital_user_review_td
partition (dt = '$do_date')
select hospital_id,
name hospital_name,
user_id,
username,
first_review_dt
from (select hospital_id,
user_id,
min(review.dt) first_review_dt
from (select doctor_id,
user_id,
dt
from ${APP}.dwd_interaction_review_inc) review
left join (select id,
hospital_id
from ${APP}.dim_doctor_full
where dt = '$do_date') doc
on review.doctor_id = doc.id
group by hospital_id,
user_id) avg
left join (select id,
name
from ${APP}.dim_hospital_full
where dt = '$do_date') hos
on avg.hospital_id = hos.id
left join (select id,
username
from ${APP}.dim_user_full
where dt = '$do_date') \`user\`
on avg.user_id = \`user\`.id;
"
dws_interaction_hospital_review_td="
insert overwrite table ${APP}.dws_interaction_hospital_review_td
partition (dt = '$do_date')
select hospital_id,
name hospital_name,
review_count,
good_review_count
from (select hospital_id,
count(*) review_count,
sum(if(rating = 5, 1, 0)) good_review_count
from (select doctor_id,
rating
from ${APP}.dwd_interaction_review_inc) review
left join
(select id,
hospital_id
from ${APP}.dim_doctor_full
where dt = '$do_date') doc
on review.doctor_id = doc.id
group by hospital_id) avg
left join (select id,
name
from ${APP}.dim_hospital_full
where dt = '$do_date') hos
on hospital_id = hos.id;
"
case $1 in
dws_trade_doctor_consultation_td | dws_interaction_hospital_user_review_td | dws_interaction_hospital_review_td)
hive -e "${!1}"
;;
"all")
hive -e "$dws_trade_doctor_consultation_td$dws_interaction_hospital_user_review_td$dws_interaction_hospital_review_td"
;;
"*")
echo "非法参数！！！"
;;
esac
添加权限
chmod +x ~/bin/medical_dws_1d_to_dws_td_init.sh
数据装载
medical_dws_1d_to_dws_td_init.sh all 2023-05-09
5.每日数据装载
vim ~/bin/medical_dws_1d_to_dws_td.sh
#!/bin/bash
APP=medical
if [ -n $2 ]
then
do_date=$2
else
echo "请传入时间参数！！！"
exit
fi
dws_trade_doctor_consultation_td="
insert overwrite table ${APP}.dws_trade_doctor_consultation_td
partition (dt = '$do_date')
select nvl(old.doctor_id, new.doctor_id) doctor_id,
nvl(old.doctor_name, new.doctor_name) doctor_name,
if(old.doctor_id is null, '$do_date', first_consultation_dt) first_consultation_dt
from (select doctor_id,
doctor_name,
first_consultation_dt
from ${APP}.dws_trade_doctor_consultation_td
where dt = date_add('$do_date', -1)) old
full outer join
(select doctor_id,
doctor_name
from ${APP}.dws_trade_doctor_consultation_1d
where dt = '$do_date') new
on old.doctor_id = new.doctor_id
and old.doctor_name = new.doctor_name;
"
dws_interaction_hospital_user_review_td="
insert overwrite table ${APP}.dws_interaction_hospital_user_review_td
partition (dt = '$do_date')
select hospital_id,
hospital_name,
user_id,
username,
min(first_review_dt) first_review_dt
from (select hospital_id,
hospital_name,
user_id,
username,
first_review_dt
from ${APP}.dws_interaction_hospital_user_review_td
where dt = date_add('$do_date', -1)
union
select hospital_id,
name hospital_name,
user_id,
username,
first_reveiw_dt
from (select hospital_id,
user_id,
'$do_date' first_reveiw_dt
from (select doctor_id,
user_id
from ${APP}.dwd_interaction_review_inc
where dt = '$do_date') reivew
left join (select id,
hospital_id
from ${APP}.dim_doctor_full) doc
on reivew.doctor_id = doc.id
group by user_id,
hospital_id) avg
left join (select id,
name
from ${APP}.dim_hospital_full
where dt = '$do_date') hos
on avg.hospital_id = hos.id
left join (select id,
username
from ${APP}.dim_user_full
where dt = '$do_date') \`user\`
on avg.user_id = \`user\`.id) \`all\`
group by hospital_id,
hospital_name,
user_id,
username;
"
dws_interaction_hospital_review_td="
insert overwrite table ${APP}.dws_interaction_hospital_review_td
partition (dt = '$do_date')
select hospital_id,
hospital_name,
sum(review_count) review_count,
sum(good_review_count) good_review_count
from (select hospital_id,
hospital_name,
review_count,
good_review_count
from ${APP}.dws_interaction_hospital_review_td
where dt = date_add('$do_date', -1)
union
select hospital_id,
name hospital_name,
review_count,
good_review_count
from (select hospital_id,
count(*) review_count,
sum(if(rating = 5, 1, 0)) good_review_count
from (select doctor_id,
rating
from ${APP}.dwd_interaction_review_inc
where dt = '$do_date') review
left join (select id,
hospital_id
from ${APP}.dim_doctor_full
where dt = '$do_date') doc
group by hospital_id) avg
left join (select id,
name
from ${APP}.dim_hospital_full
where dt = '$do_date') hos
on hospital_id = hos.id) \`all\`
group by hospital_id,
hospital_name;
"
case $1 in
dws_trade_doctor_consultation_td | dws_interaction_hospital_user_review_td | dws_interaction_hospital_review_td)
hive -e "${!1}"
;;
"all")
hive -e "$dws_trade_doctor_consultation_td$dws_interaction_hospital_user_review_td$dws_interaction_hospital_review_td"
;;
"*")
echo "非法参数！！！"
;;
esac
添加权限
chmod +x ~/bin/medical_dws_1d_to_dws_td.sh
总结
内容有点多，可能还要一次才能完成。
![[管理与领导-65]：IT基层管理者 - 辅助技能 - 4- 乌卡时代(VUCA )](https://img-blog.csdnimg.cn/bd74b0eaebd74ba7b678af58b858d5f1.png)
