update20260427

THC/02 dm_ext_thc_sales_bakup_20260327.sql

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+-- Databricks notebook source
+-- create table dm.dm_ext_thc_sales
+-- (
+-- yyyymm STRING,
+-- audit_cod STRING,
+-- pack_cod STRING,
+-- corp_cod STRING,
+-- sales_value_cal decimal(38,10),
+-- sales_unit_cal decimal(38,10),
+-- counting_unit decimal(38,10),
+-- sales_value_cal_ly decimal(38,10),
+-- sales_unit_cal_ly decimal(38,10),
+-- counting_unit_ly decimal(38,10)
+-- )
+-- using delta
+
+-- COMMAND ----------
+
+--------------------------------------------------------------------------
+--修改时间：20241106
+--修改人：Fanxujia
+--修改内容：
+--THC原本只有全国数据，现在增加14个省份的数据。
+--但是全国数据是半年提供一次，省份数据一个季度提供一次
+--目前需求是将季度数据放入模型，而全国数据单独成一个事实表，供PBI单独展示
+--这里生成的事实表里全国和省份都包含了，在写入模型的时候用where条件筛选
+---------------------------------------------------------------------------
+--rawdata年月处理
+with thc_rawdata1 as (
+select case when right(yq,2) = 'Q1' then concat(left(yq,4),'03')
+            when right(yq,2) = 'Q2' then concat(left(yq,4),'06')
+            when right(yq,2) = 'Q3' then concat(left(yq,4),'09')
+            when right(yq,2) = 'Q4' then concat(left(yq,4),'12')
+            else yq
+        end as yyyymm,
+        city_c,
+        pack_cod,
+        prod_cod,
+        value,
+        totalunit,
+        countingunit
+from dwd.dwd_gnd_ext_thc_rawdata
+)
+--CHPA渠道对应的公司编码以及名称
+,chpa_corp as (
+select distinct
+PACK_COD,
+CORP_COD,
+CORP_DES
+from dm.dm_ims_td_pack_property
+)
+--从thc渠道的pack_property里取到对应的iqvia_pack_code、countingunit
+--然后corp_cod优先取CHPA渠道的
+,thc_corp as (
+select t1.pack_cod,
+t1.iqvia_pack_code,
+t1.countingunit,
+coalesce(t2.CORP_COD, t1.CORP_COD) as CORP_COD ,
+coalesce(t2.CORP_DES,t1.CORP_DES ) as CORP_DES
+from dwd.dwd_gnd_ext_thc_pack_property t1
+left join chpa_corp t2
+on t1.iqvia_pack_code = t2.PACK_COD
+)
+--编辑thc渠道的audit_cod
+--全国数据设置成CHT
+--省份数据使用公共的地理维表里的省份编码作为audit_cod
+,thc_geo as (
+select 
+t1.city_c,
+t1.city_e,
+t1.province_c,
+t1.province_e,
+case when t1.province_c = '全国' then 'CHT'
+     when t2.geo_key is null then t1.province_e
+     else t2.geo_key
+end as AUDIT_COD
+from dwd.dwd_gnd_ext_thc_geo t1
+left join dm.dm_td_geography t2
+--THC最细到省，用省关联
+on t1.province_c = t2.province_name
+and t2.geo_key = t2.province_code
+)
+--将上面的rawdata、corp、audit信息合到一起
+,thc_rawdata2 as (
+select t1.yyyymm,
+t1.city_c,
+t1.pack_cod as pack_cod_old,
+t2.iqvia_pack_code as pack_cod,
+t2.CORP_COD,
+t3.AUDIT_COD,
+t1.prod_cod,
+t1.value,
+t1.totalunit,
+t1.totalunit * t2.countingunit as countingunit
+from thc_rawdata1 t1
+left join thc_corp t2
+on t1.pack_cod = t2.pack_cod
+left join thc_geo t3
+on t1.city_c = t3.city_c
+)
+--最大的月份，计算ly时会需要
+,max_thc_rawdata as (
+select max(cast(yyyymm as int)) as max_ym
+from thc_rawdata2
+)
+--计算ly
+,thc_rawdata3 as (
+select yyyymm,
+AUDIT_COD,
+pack_cod,
+CORP_COD,
+value,
+totalunit,
+countingunit,
+0 as value_ly,
+0 as totalunit_ly,
+0 as countingunit_ly
+from thc_rawdata2
+union all
+select cast(t1.yyyymm as int) + 100 as yyyymm,
+t1.AUDIT_COD,
+t1.pack_cod,
+t1.CORP_COD,
+0 as value,
+0 as totalunit,
+0 as countingunit,
+t1.value as value_ly,
+t1.totalunit as totalunit_ly,
+t1.countingunit as countingunit_ly
+from thc_rawdata2 t1
+cross join max_thc_rawdata t2
+where cast(t1.yyyymm as int) + 100 <= t2.max_ym
+)
+--按年月、audit_cod、pack_cod、Corp_cod汇总
+,thc_rawdata4 as (
+select yyyymm,
+AUDIT_COD,
+pack_cod,
+CORP_COD,
+sum(value) as SALES_VALUE_CAL,
+sum(totalunit) as SALES_UNIT_CAL,
+sum(countingunit) as COUNTING_UNIT,
+sum(value_ly) as SALES_VALUE_CAL_LY,
+sum(totalunit_ly) as SALES_UNIT_CAL_LY,
+sum(countingunit_ly) as COUNTING_UNIT_LY
+from thc_rawdata3
+group by yyyymm,
+AUDIT_COD,
+pack_cod,
+CORP_COD
+)
+
+insert overwrite table dm.dm_ext_thc_sales
+(
+yyyymm,
+AUDIT_COD,
+pack_cod,
+CORP_COD,
+SALES_VALUE_CAL,
+SALES_UNIT_CAL,
+COUNTING_UNIT,
+SALES_VALUE_CAL_LY,
+SALES_UNIT_CAL_LY,
+COUNTING_UNIT_LY
+)
+select yyyymm,
+AUDIT_COD,
+pack_cod,
+CORP_COD,
+SALES_VALUE_CAL,
+SALES_UNIT_CAL,
+COUNTING_UNIT,
+SALES_VALUE_CAL_LY,
+SALES_UNIT_CAL_LY,
+COUNTING_UNIT_LY
+from thc_rawdata4
+--取2018年之后的数
+where yyyymm >= '201801'