请以最详细的方式解释这段代码with a0 as ( select case when prodlinename in ('冷柜', '冰箱') then '制冷' when prodlinename in ('商空') then '楼宇' when prodlinename in ('家空') then '空调' else prodlinename end industry, mouldno, cast(avgintervals as double) as avgintervals, pt from dl_yf_seq.tt_hmzy_haier_mould_iot_fenqu where avgintervals is not null and avgintervals not in('', '0', '0.0') and prodlinename in('冷柜', '冰箱', '商空', '家空', '厨电', '洗涤', '热水器') and substr(pt, 1, 4) = from_unixtime(unix_timestamp(), 'yyyy') ), a1 as ( select model_code, cast(ratedcycle as double) as ratedcycle from dh_yf.dim_udo_model_dim_asset where ratedCycle is not null and ratedCycle not in('', '/', '0', '0.0') ), a2 as ( select industry, mouldno, avgintervals, b.ratedcycle, case when avgintervals<= ratedCycle then 1 else 0 end db, pt from a0 a left join a1 b on a.mouldno = b.model_code ), a3 as ( select pt, industry, count(mouldno) as kj_module_num, sum(db) as db_module_num from a2 group by pt, industry ) insert OVERWRITE table dh_yf.tg_dim_udo_model_scxldb select pt, industry, cast(kj_module_num as string) kj_module_num, cast(db_module_num as string) db_module_num, from_unixtime(unix_timestamp(),'yyyyMMdd') as dh_etl_date from a3
时间: 2023-12-26 19:06:46 浏览: 24
这是一段 SQL 代码,用于从数据库中查询数据并将结果插入到目标表格中。这段代码包含了四个子查询,分别是 a0、a1、a2 和 a3,并使用了 with 语句来创建这些子查询。下面是这些子查询的具体作用:
- a0 子查询:从表格 dl_yf_seq.tt_hmzy_haier_mould_iot_fenqu 中查询数据,并对 prodlinename 进行分类处理,将其映射成行业分类(制冷、楼宇、空调等)。然后按照 mouldno 分组,计算出 avgintervals 的平均值,并选取 pt 字段作为时间戳。
- a1 子查询:从表格 dh_yf.dim_udo_model_dim_asset 中查询数据,选取 ratedcycle 字段,并将其转换为 double 类型。
- a2 子查询:将 a0 和 a1 子查询的结果进行联接,然后根据 ratedCycle 和 avgintervals 的大小关系,计算出 db 字段的值(如果 avgintervals <= ratedCycle,则 db=1,否则 db=0)。
- a3 子查询:根据 pt 和 industry 分组,分别计算 kj_module_num 和 db_module_num 字段的值。
最终,将 a3 子查询的结果插入到表格 dh_yf.tg_dim_udo_model_scxldb 中,并设置 dh_etl_date 字段为当前日期。
相关问题
请以最详细的方式解释这段代码with a0 as ( select case when prodlinename in ('冷柜', '冰箱') then '制冷' when prodlinename in ('商空') then '楼宇' when prodlinename in ('家空') then '空调' else prodlinename end industry, mouldno, cast(avgintervals as double) as avgintervals, pt from dl_yf_seq.tt_hmzy_haier_mould_iot_fenqu where avgintervals is not null and avgintervals not in('', '0', '0.0') and prodlinename in('冷柜', '冰箱', '商空', '家空', '厨电', '洗涤', '热水器') and substr(pt, 1, 4) = from_unixtime(unix_timestamp(), 'yyyy') ), a1 as ( select model_code, cast(ratedcycle as double) as ratedcycle from dh_yf.dim_udo_model_dim_asset where ratedCycle is not null and ratedCycle not in('', '/', '0', '0.0') ), a2 as ( select industry, mouldno, avgintervals, b.ratedcycle, case when avgintervals<= ratedCycle then 1 else 0 end db, pt from a0 a left join a1 b on a.mouldno = b.model_code ), a3 as ( select pt, industry, count(mouldno) as kj_module_num, sum(db) as db_module_num from a2 group by pt, industry ) insert OVERWRITE table dh_yf.tg_dim_udo_model_scxldb select pt, industry, cast(kj_module_num as string) kj_module_num, cast(db_module_num as string) db_module_num, from_unixtime(unix_timestamp(),'yyyyMMdd') as dh_etl_date from a3
这段代码使用了 SQL 语言,主要包含了四个子查询,最终将结果插入到一个名为 dh_yf.tg_dim_udo_model_scxldb 的表中。
1. 第一个子查询
第一个子查询使用了 WITH 子句,创建了一个名为 a0 的临时表,其作用是将 tt_hmzy_haier_mould_iot_fenqu 表中的数据进行筛选和转换。具体操作如下:
```
with a0 as (
select
case
when prodlinename in ('冷柜', '冰箱') then '制冷'
when prodlinename in ('商空') then '楼宇'
when prodlinename in ('家空') then '空调'
else prodlinename
end industry,
mouldno,
cast(avgintervals as double) as avgintervals,
pt
from
dl_yf_seq.tt_hmzy_haier_mould_iot_fenqu
where
avgintervals is not null
and avgintervals not in('', '0', '0.0')
and prodlinename in('冷柜', '冰箱', '商空', '家空', '厨电', '洗涤', '热水器')
and substr(pt, 1, 4) = from_unixtime(unix_timestamp(), 'yyyy')
)
```
- 首先使用 CASE WHEN 语句对 prodlinename 进行分类转换,将其转换为行业类型。
- 然后将 avgintervals 字段转换为 double 类型。
- 最后筛选出符合条件的数据,其中 substr(pt, 1, 4) = from_unixtime(unix_timestamp(), 'yyyy') 表示只选择当年的数据,pt 表示时间戳。
2. 第二个子查询
第二个子查询创建了一个名为 a1 的临时表,其作用是从 dim_udo_model_dim_asset 表中筛选出 ratedCycle 不为空的数据,并将其转换为 double 类型。
```
with a1 as (
select
model_code,
cast(ratedcycle as double) as ratedcycle
from
dh_yf.dim_udo_model_dim_asset
where
ratedCycle is not null
and ratedCycle not in('', '/', '0', '0.0')
)
```
3. 第三个子查询
第三个子查询将 a0 和 a1 两个临时表进行了关联,计算出每个模具的 db 值。
```
with a2 as (
select
industry,
mouldno,
avgintervals,
b.ratedcycle,
case
when avgintervals<= ratedCycle then 1
else 0
end db,
pt
from
a0 a
left join a1 b on a.mouldno = b.model_code
)
```
- 首先对 a0 和 a1 两个临时表进行了左连接。
- 然后使用 CASE WHEN 语句计算出每个模具的 db 值,如果 avgintervals <= ratedCycle,则 db 值为 1,否则为 0。
4. 第四个子查询
第四个子查询将 a2 表按照时间和行业进行分组,计算出每个行业的 kj_module_num 和 db_module_num 值,并将结果插入到 dh_yf.tg_dim_udo_model_scxldb 表中。
```
with a3 as (
select
pt,
industry,
count(mouldno) as kj_module_num,
sum(db) as db_module_num
from
a2
group by
pt,
industry
)
insert OVERWRITE table dh_yf.tg_dim_udo_model_scxldb
select
pt,
industry,
cast(kj_module_num as string) kj_module_num,
cast(db_module_num as string) db_module_num,
from_unixtime(unix_timestamp(),'yyyyMMdd') as dh_etl_date
from
a3
```
- 首先将 a2 表按照时间和行业进行分组,计算出每个行业的 kj_module_num 和 db_module_num 值。
- 然后将结果插入到 dh_yf.tg_dim_udo_model_scxldb 表中,其中 kj_module_num 和 db_module_num 被转换为 string 类型,dh_etl_date 表示当前日期。
请详细解释下这段代码with a0 as ( select case when prodlinename in ('冷柜', '冰箱') then '制冷' when prodlinename in ('商空') then '楼宇' when prodlinename in ('家空') then '空调' else prodlinename end industry, mouldno, cast(avgintervals as double) as avgintervals, pt from dl_yf_seq.tt_hmzy_haier_mould_iot_fenqu where avgintervals is not null and avgintervals not in('', '0', '0.0') and prodlinename in('冷柜', '冰箱', '商空', '家空', '厨电', '洗涤', '热水器') and substr(pt, 1, 4) = from_unixtime(unix_timestamp(), 'yyyy') ), a1 as ( select model_code, cast(ratedcycle as double) as ratedcycle from dh_yf.dim_udo_model_dim_asset where ratedCycle is not null and ratedCycle not in('', '/', '0', '0.0') ), a2 as ( select industry, mouldno, avgintervals, b.ratedcycle, case when avgintervals<= ratedCycle then 1 else 0 end db, pt from a0 a left join a1 b on a.mouldno = b.model_code ), a3 as ( select pt, industry, count(mouldno) as kj_module_num, sum(db) as db_module_num from a2 group by pt, industry ) insert OVERWRITE table dh_yf.tg_dim_udo_model_scxldb select pt, industry, cast(kj_module_num as string) kj_module_num, cast(db_module_num as string) db_module_num, from_unixtime(unix_timestamp(),'yyyyMMdd') as dh_etl_date from a3
这段代码是一个SQL查询语句,主要是从表tt_hmzy_haier_mould_iot_fenqu中筛选出符合条件的数据,然后与表dim_udo_model_dim_asset进行左连接,最终将结果插入表tg_dim_udo_model_scxldb中。
具体来说,这段代码首先使用with关键字定义了三个子查询a0、a1和a2。其中,a0子查询通过对prodlinename进行分类转换,筛选出冷柜、冰箱、商空、家空、厨电、洗涤、热水器等产品线的数据,并计算出平均间隔时间avgintervals。a1子查询从dim_udo_model_dim_asset表中筛选出ratedCycle不为空的数据。a2子查询通过左连接a0和a1两个子查询的结果,计算出每个模具的db值。
接着,使用a3子查询对a2查询结果进行聚合分析,统计出每个行业下的kj_module_num和db_module_num值。最后,将结果插入表tg_dim_udo_model_scxldb中,包括pt、industry、kj_module_num、db_module_num和dh_etl_date等字段。其中,pt表示时间戳,industry表示行业,kj_module_num表示空间模块数量,db_module_num表示电泵模块数量,dh_etl_date表示数据的ETL日期。
总的来说,这段代码的主要作用是对冷柜、冰箱、商空、家空、厨电、洗涤、热水器等产品线下的模具数据进行分析,统计出每个行业下的空间模块数量和电泵模块数量,以便后续的数据分析和业务决策。