DWS层建设实战-1

Day07_DWS层建设实战-1

资料文档

课程内容大纲与学习目标

#课程内容大纲
	1、聚合函数增强
		grouping sets
		cube、rollup
		grouping
		功能:针对分组聚合操作进行优化。
	2、DWS层搭建
    	目标与需求
    	销售主题统计宽表--简易模型分析 知识点：grouping sets
    	销售主题统计宽表--复杂模型分析 知识点：row_number去重
    	新零售项目销售主题统计宽表的实现
#学习目标
	掌握grouping sets等函数的功能、应用
	掌握使用row_number函数进行去重操作
	掌握数仓DWS层功能
	理解销售主题宽表的实现

聚合函数增强--grouping sets介绍与使用

• 背景
  • 数据环境准备

--在hive中建表操作
use test;

create table test.t_user(
    month string, 
    day string, 
    userid string) 
row format delimited fields terminated by ',';


--数据样例
2015-03,2015-03-10,user1
2015-03,2015-03-10,user5
2015-03,2015-03-12,user7
2015-04,2015-04-12,user3
2015-04,2015-04-13,user2
2015-04,2015-04-13,user4
2015-04,2015-04-16,user4
2015-03,2015-03-10,user2
2015-03,2015-03-10,user3
2015-04,2015-04-12,user5
2015-04,2015-04-13,user6
2015-04,2015-04-15,user3
2015-04,2015-04-15,user2
2015-04,2015-04-16,user1

• 需求

分别按照月（month）、天（day）、月和天（month,day）统计来访用户userid个数，并获取三者的结果集（一起插入到目标宽表中）。

目标表：month   day   cnt_nums

维度：
	天
	月
	天 + 月
指标：
   访问用户数
   
----------------------------
维度组合:
	日期
	日期+城市
	日期+城市+商圈
	日期+城市+商圈+店铺(自己写)
	
	日期+品牌
	
	日期+大类 
	日期+大类+中类
	日期+大类+类+小类

--3个分组统计而已，简单。统计完再使用union all合并结果集。
--注意union all合并结果集需要各个查询返回字段个数、类型一致，因此需要合理的使用null来填充返回结果。
select
    month,
    day,
    count(userid) as user_cnt
from test.t_user
group by month, day

union all

select
    null as month,
    day,
    count(userid) as user_cnt
from test.t_user
group by  day

union  all

select
     month,
    null as day,
    count(userid) as user_cnt
from test.t_user
group by  month;

• 执行结果如下

思考一下，这样有什么不妥的地方吗？

首先感受就是执行时间很长，很长；

另外从sql层面分析，会对test.t_user查询扫描3次，因为是3个查询的结果集合并。

假如这是10个维度的所有组合计算同一个指标呢？？

2^10  * 1    条select查询 union all？？？？？

image-20211012221755094.png

• grouping sets功能

根据不同的维度组合进行聚合，等价于将不同维度的GROUP BY结果集进行UNION ALL。

select 
    month,day,count(userid) 
from test.t_user 
    group by month,day 
grouping sets (month,day,(month,day));

image-20211012222448607.png

1、使用grouping sets，执行结果与使用多个分组查询union合并结果集一样； 2、grouping sets查询速度吊打分组查询结果union all。大家可以使用explain执行计划查看两条sql的执行逻辑差异。 3、使用grouping sets只会对表进行一次扫描。

• hive中grouping sets语法

https://cwiki.apache.org/confluence/display/Hive/Enhanced+Aggregation%2C+Cube%2C+Grouping+and+Rollup#EnhancedAggregation,Cube,GroupingandRollup-GROUPINGSETSclause

image-20211012222852943.png

特别注意：Presto的grouping sets语法和hive略有差异。

---下面这个是Hive SQL语法支持
select 
    month,day,count(userid) 
from test.t_user 
    group by month,day 
grouping sets (month,day,(month,day));

----下面这个是Presto SQL语法支持
select 
    month,day,count(userid) 
from test.t_user 
    group by
grouping sets (month,day,(month,day));

--区别就是在presto的语法中，group by后面不要再加上字段了。

---

聚合函数增强--cube、rollup介绍与使用

• cube
  • cube翻译过来叫做立方体，data cubes就是数据立方体。
  • cube的功能：实现多个任意维度的查询。也可以理解为所有维度组合。

公式：假如说有==N个维度，那么所有维度的组合的个数：2^N==

下面这个图，就显示了4个维度所有组合构成的数据立方体。

image-20211012223824098.png

• 语法

-- cube的语法在hive和presto中是通用的

select month,day,count(userid)
from test.t_user
group by
cube (month, day);  -- (month, day) ,month,day,() 如果有n个字段，则就是分组个数是2的n次方

--上述sql等价于
select month,day,count(userid)
from test.t_user
group by
grouping sets ((month,day), month, day, ());

image-20211012224133056.png

• rollup
  • 语法功能：实现从右到左递减多级的统计,显示统计某一层次结构的聚合。

即：rollup(a,b,c)等价于grouping sets((a,b,c),(a,b),(a),())。

rollup(日期，城市，商圈)

grouping sets((日期，城市，商圈),(日期，城市),(日期),())。

grouping sets((),(日期),(日期，城市),(日期，城市，商圈))。 !!!!!!!!!!!!!

-- rollup的语法在hive和presto中是通用的

select month,day,count(userid)
from test.t_user
group by
rollup (month,day);

--等价于
select month,day,count(userid)
from test.t_user
group by
grouping sets ((month,day), (month), ());

image-20211012224838605.png

---

聚合函数增强--grouping介绍与使用

• 功能：使用grouping操作来判断当前数据是按照哪个字段来分组的。

对于给定的分组，如果分组中包含相应的列，则将位设置为0，否则将其设置为1。

• 例子

--为了计算高效 切换至Presto引擎中进行计算

select month,
       day,
       count(userid),
       grouping(month)      as m,
       grouping(day)        as d,
       grouping(month, day) as m_d
from test.t_user
group by
   grouping sets (month, day, (month, day));

image-20211012232435567.png

• 解释说明

grouping(month)列为0时，可以看到month列都是有值的，为1时则相反，证明当前行是按照month来进行分组统计的；

grouping(day)同理，为0时day列有值，为1时day为空，证明当前行时按照day来进行分组统计的；

grouping(month, day)是grouping(month)、grouping(day)二进制数值组合后转换得到的数字：
a. 按照month分组，则month=0，day=1，组合后为01，二进制转换为十进制得到数字1；
b. 按照day分组，则month=1，day=0，组合后为10，二进制转换为十进制得到数字2；
c. 同时按照month和day分组，则month=0，day=0，组合后为00，二进制转换为十进制得到数字0。

因此可以使用grouping操作来判断当前数据是按照哪个字段来分组的。

---

目标与需求

• 新零售数仓分层图
• DWS
  • 名称：数据服务层  service
  • 功能：按主题划分，形成日统计的宽表，轻度汇总提前聚合操作。
  • 解释：轻度提前聚合说的是先聚合出日的指标，后续可以上卷出周、月、年的指标。

dws这里，主题终于出现了~~~

一个主题所需要的指标、维度，可能往往需要多个DWB层的宽表共同参与计算才能得出。甚至还需要之前层如dwd等参与计算。

• 使用DataGrip在Hive中创建dws层

注意，对于建库建表操作，需直接使用Hive，因为Presto只是一个数据分析的引擎，其语法不一定支持直接在Hive中建库建表。

drop database if exists yp_dws cascade ;
create database if not exists yp_dws;

---

销售主题宽表--需求与建表

• 主题需求
  • 指标

销售收入、平台收入、配送成交额、小程序成交额、安卓APP成交额、苹果APP成交额、PC商城成交额、订单量、参评单量、差评单量、配送单量、退款单量、小程序订单量、安卓APP订单量、苹果APP订单量、PC商城订单量

--共计: 16个指标

• 维度

日期、城市、商圈、店铺、品牌、商品大类、商品中类、商品小类

--共计:  8个维度
--cube所有组合:  2^8=256个

注意，其中日期这个维度很特殊，特殊在我们的表就是根据日期分区的，分区的字段是day天。
而dws这一层我们需要统计的也是按day统计，日统计宽表嘛
这也就意味着一个分区就是一天。

• 本主题需要维度组合

提示：256个组合都计算还是计算当中的一部分，主动权在于业务、需求，我们做的是技术实现。

日期
日期+城市
日期+城市+商圈
日期+城市+商圈+店铺

日期+品牌

日期+大类
日期+大类+中类
日期+大类+中类+小类

• 总计需要计算的指标

16*8=128

1、如果不加任何限制，只是求出每个指标，那么很简单，128个sql语句进行分组聚合操作。

2、实际中肯定不能那么做，需要一条sql完成128个指标的计算，并且把结果插入主题统计宽表中。

• Hive中建表

既然是把一个主题相关的数据统计数据都存储在一张表中，那么意味着这张统计宽表应该要清晰的记录出维度、指标，有的计算，没有的null补上。

CREATE TABLE yp_dws.dws_sale_daycount(
  --维度  
   city_id string COMMENT '城市id',
   city_name string COMMENT '城市name',
   trade_area_id string COMMENT '商圈id',
   trade_area_name string COMMENT '商圈名称',
   store_id string COMMENT '店铺的id',
   store_name string COMMENT '店铺名称',
   brand_id string COMMENT '品牌id',
   brand_name string COMMENT '品牌名称',
   max_class_id string COMMENT '商品大类id',
   max_class_name string COMMENT '大类名称',
   mid_class_id string COMMENT '中类id',
   mid_class_name string COMMENT '中类名称',
   min_class_id string COMMENT '小类id',
   min_class_name string COMMENT '小类名称',
   group_type string COMMENT '分组类型：store，trade_area，city，brand，min_class，mid_class，max_class，all',
   --   =======日统计=======
   --   销售收入
   sale_amt DECIMAL(38,2) COMMENT '销售收入',
   --   平台收入
   plat_amt DECIMAL(38,2) COMMENT '平台收入',
   -- 配送成交额
   deliver_sale_amt DECIMAL(38,2) COMMENT '配送成交额',
   -- 小程序成交额
   mini_app_sale_amt DECIMAL(38,2) COMMENT '小程序成交额',
   -- 安卓APP成交额
   android_sale_amt DECIMAL(38,2) COMMENT '安卓APP成交额',
   --  苹果APP成交额
   ios_sale_amt DECIMAL(38,2) COMMENT '苹果APP成交额',
   -- PC商城成交额
   pcweb_sale_amt DECIMAL(38,2) COMMENT 'PC商城成交额',
   -- 成交单量
   order_cnt BIGINT COMMENT '成交单量',
   -- 参评单量
   eva_order_cnt BIGINT COMMENT '参评单量comment=>cmt',
   -- 差评单量
   bad_eva_order_cnt BIGINT COMMENT '差评单量negtive-comment=>ncmt',
   -- 配送成交单量
   deliver_order_cnt BIGINT COMMENT '配送单量',
   -- 退款单量
   refund_order_cnt BIGINT COMMENT '退款单量',
   -- 小程序成交单量
   miniapp_order_cnt BIGINT COMMENT '小程序成交单量',
   -- 安卓APP订单量
   android_order_cnt BIGINT COMMENT '安卓APP订单量',
   -- 苹果APP订单量
   ios_order_cnt BIGINT COMMENT '苹果APP订单量',
   -- PC商城成交单量
   pcweb_order_cnt BIGINT COMMENT 'PC商城成交单量'
)
COMMENT '销售主题日统计宽表'
PARTITIONED BY(dt STRING)
ROW format delimited fields terminated BY '\t'
stored AS orc tblproperties ('orc.compress' = 'SNAPPY');

---

销售主题宽表--简易模型分析（分组聚合union）

为了更好的实现一条sql计算出所有的指标，这里我们先对数据模型进行简化操作。

这个模型理解了，销售主题宽表的计算就可以实现了。

• 需求
  • 订单宽表t_order_detail

--建表（在hive中创建）
create table test.t_order_detail(
    oid string comment '订单ID',
    goods_id string comment '商品ID',
    o_price int comment '订单总金额',
    g_num int comment '商品数量',
    g_price int comment '商品单价',
    brand_id string comment '品牌ID',
    dt string comment '日期'
) comment '订单详情宽表_简易模型'
row format delimited fields terminated by ',';

--加载数据
o01,g01,100,1,80,b01,2021-08-29
o01,g02,100,1,20,b02,2021-08-29
o02,g03,180,1,80,b01,2021-08-29
o02,g04,180,2,40,b02,2021-08-29
o02,g07,180,3,60,b01,2021-08-29
o03,g02,80,1,80,b02,2021-08-30
o04,g01,300,2,160,b01,2021-08-30
o04,g02,300,3,60,b02,2021-08-30
o04,g03,300,4,80,b01,2021-08-30

image-20211013225639853.png

• 需求
  • 指标：订单量、销售额
  • 维度：日期、日期+品牌
• 计算出结果
• 实现思路（在presto中计算）

立马想到：多条sql分组聚合+union合并结果集，没有的字段使用null进行填补。

• step1:统计每天的订单量、销售额

select
  dt,
  count(distinct oid) as "订单量",
  sum(g_price) as "销售额"
from test.t_order_detail
group by dt;

image-20211013230246919.png

• step2:统计每天每个品牌的订单量、销售额

select
  dt,
  brand_id,
  count(distinct oid) as "各品牌订单量",
  sum(g_price) as "各品牌销售额"
from test.t_order_detail
group by dt,brand_id;

image-20211013230507311.png

• step3:union all合并两个查询结果集

select
  dt as "日期",
  null as "品牌id",
  count(distinct oid) as "订单量",
  null as "各品牌订单量",
  sum(g_price) as "销售额",
  null as "各品牌销售额",
  1 as group_id
from test.t_order_detail
group by dt
union all
select
  dt as "日期",
  brand_id as "品牌id",
  null as "订单量",
  count(distinct oid) as "各品牌订单量",
  null as "销售额",
  sum(g_price) as "各品牌销售额",
  2 as group_id
from test.t_order_detail
group by dt,brand_id;

---

销售主题宽表--简易模型分析（grouping sets增强聚合）

思路：采用grouping sets增强聚合计算，并且使用grouping函数判断分组中是否包含字段。

0表示有，1表示没有。

• sql实现

select
count(distinct oid),
sum(g_price)
from test.t_order_detail
group by grouping sets(dt,(dt,brand_id));

--直接这样写，结果如下显示，不友好，无法区分是哪一个分组聚合的结果

image-20211013232142281.png

• sql最终实现

可以考虑使用grouping函数判断分组中是否包含指定的字段，并且配合case when进行转换。

注意：grouping函数有为0，没有是1。

select
    dt as "日期",
    case when grouping(brand_id) =0
        then brand_id
    else null end as "品牌id",  -- 第二列，如果分组中有品牌id,就显示，没有就null
    count(distinct oid) as "订单量",
    sum(g_price)
from test.t_order_detail
group by grouping sets(dt,(dt,brand_id));

--执行上面sql，看看效果。
--下面是最终完整版
select
    dt as "日期",
    case when grouping(brand_id) =0  --判断是否包含brand_id
        then brand_id
        else null end as "品牌id",
    case when grouping(dt,brand_id) =1 --只包含日期 就是订单量
        then count(distinct oid)
        else null end as "订单量",
    case when grouping(brand_id) =0 --包含品牌 就是各品牌订单量
        then count(distinct oid)
        else null end as "各品牌订单量",
    case when grouping(brand_id) =1 --没有品牌，就是销售额
        then sum(g_price)
        else null end as "销售额",
    case when grouping(brand_id) =0 --包含品牌，就是各个品牌销售额
        then sum(g_price)
        else null end as "各品牌销售额",
    case when grouping(brand_id) = 1 --没有品牌 就是分组1 否则就是2
        then 1
        else 2 end as group_id
from test.t_order_detail
group by grouping sets(dt,(dt,brand_id));

image-20211013234823518.png

---

销售主题宽表--复杂模型分析（去重）

• 项目订单宽表梳理

根据上述的简易模型我们去梳理一下项目中的yp_dwb.dwb_order_detail订单明细宽表。

把属于同一笔订单的所有商品信息提取出来，验证一下数据是否匹配模型。

--根据订单id分组，找出订单商品数最多的
select
    order_id,
    count (order_id) as nums
from yp_dwb.dwb_order_detail
group by order_id
order by nums desc limit 10;

--查看订单ID为dd190227318021f41f的信息
select * from yp_dwb.dwb_order_detail where order_id = 'dd190227318021f41f';

• 问题

上述简易模型中，数据是没有重复的，直接grouping sets 统计没有问题；

假如数据是重复的又该如何处理呢？如何进行去重？

或者说不管数据有没有重复，会不会重复，能不能设计一种解决方案，不管重复如何，先过滤重复，保证计算一定是正确的？？

--建表（在hive中创建）
create table test.t_order_detail_dup(
    oid string comment '订单ID',
    goods_id string comment '商品ID',
    o_price int comment '订单总金额',
    g_num int comment '商品数量',
    g_price int comment '商品单价',
    brand_id string comment '品牌ID',
    dt string comment '日期'
) comment '订单详情宽表_复杂模型'
row format delimited fields terminated by ',';

--加载数据
o01,g01,100,1,80,b01,2021-08-29
o01,g02,100,1,20,b02,2021-08-29
o01,g01,100,1,80,b01,2021-08-29
o02,g03,180,1,80,b01,2021-08-29
o02,g04,180,2,40,b02,2021-08-29
o02,g04,180,2,40,b02,2021-08-29
o02,g07,180,3,60,b01,2021-08-29
o03,g02,80,1,80,b02,2021-08-30
o04,g01,300,2,160,b01,2021-08-30
o04,g02,300,3,60,b02,2021-08-30
o04,g03,300,4,80,b01,2021-08-30

image-20211014091841158.png

• 实现思路

1、ROW_NUMBER() OVER(PARTITION BY 需要去重字段 ) ，这样相同的就会分到一组；

2、为分组中指定的去重字段标上行号,如果有重复的,选中行号为1的就可以。

• 比如只以订单oid去重

select
    oid,
    row_number() over(partition by oid) as rn1
from test.t_order_detail_dup;

--去重过程
with tmp as (select
    oid,
    row_number() over(partition by oid) as rn1
from test.t_order_detail_dup)
select * from tmp where rn1 = 1;

image-20211014093802292.png

• 以订单oid+品牌brand_id去重

select
    oid,
    brand_id,
    row_number() over(partition by oid,brand_id) as rn2
from test.t_order_detail_dup;


with tmp1 as (select
    oid,
    brand_id,
    row_number() over(partition by oid,brand_id) as rn2
from test.t_order_detail_dup)
select * from tmp1 where rn2 = 1;

image-20211014093937149.png

• 再比如以订单oid+品牌brand_id+商品goods_id去重

select
    oid,
    brand_id,
    goods_id,
    row_number() over(partition by oid,brand_id,goods_id) as rn3
from test.t_order_detail_dup;


with tmp2 as (select
    oid,
    brand_id,
    goods_id,
    row_number() over(partition by oid,brand_id,goods_id) as rn3
from test.t_order_detail_dup)
select * from tmp2 where rn3 = 1;

image-20211014094232129.png

• 整合一起

select
    oid,
    brand_id,
    goods_id,
    row_number() over(partition by oid) as rn1,
    row_number() over(partition by oid,brand_id) as rn2,
    row_number() over(partition by oid,brand_id,goods_id) as rn3
from test.t_order_detail_dup;

image-20211014094518943.png

• 结论

当我们以不同维度进行组合统计的时候，为了避免重复数据对最终结果的影响，可以考虑配合使用row_number去重。

---

销售主题宽表--step1--字段抽取

• 表关系

一切的前提是，先了解原始数据的结构和关系。

对于销售主题宽表来说，其当中的指标和维度字段分别来源于DWB层：订单明细宽表、店铺明细宽表、商品明细宽表。

比如商圈、店铺等维度来自于店铺明细宽表；大中小分类来自于商品明细宽表；而成交额等指标需要依赖订单明细宽表。

--以订单为准，以goods_id关联商品，以store_id关联店铺
select *
from dwb_order_detail o
    left join dwb_goods_detail g on o.goods_id = g.id
    left join dwb_shop_detail s on o.store_id = s.id;

• 字段抽取

关联之后，字段非常多，但是并不意味着每一个字段都是销售主题宽表统计需要的；

因此需要根据销售主题宽表的计算指标和维度，把相关的字段抽取出来

select
--维度
        o.dt as create_date,--日期(注意，分区表的粒度就是按天分区)
		s.city_id,
		s.city_name, --城市
		s.trade_area_id,
		s.trade_area_name,  --商圈
		s.id as store_id,
		s.store_name, --店铺
		g.brand_id,
		g.brand_name, --品牌
		g.max_class_id,
		g.max_class_name, --商品大类
		g.mid_class_id,
		g.mid_class_name,-- 商品中类
		g.min_class_id,
		g.min_class_name,--商品小类
--订单量指标
		o.order_id, --订单id
		o.goods_id, --商品id
--金额指标
		o.order_amount, --订单金额
        o.total_price, --商品金额(商品数量*商品单价)
		o.plat_fee,   --平台分润
		o.dispatcher_money, --配送员的运费
--判断条件
		o.order_from, --订单来源渠道：安卓、苹果....
		o.evaluation_id, --评价单id,不为空表示有评价
		o.geval_scores,  --综合评分，差评的计算
		o.delievery_id, --配送单ID(如果不为null，表示是配送单，其他还有可能是自提、商家配送)
		o.refund_id --退款单id,不为空表示有退款

from dwb_order_detail o
    left join dwb_goods_detail g on o.goods_id = g.id
    left join dwb_shop_detail s on o.store_id = s.id;

---

销售主题宽表--step2--row_number去重

使用row_number分组去重的时候需要注意：

1、对于城市、商圈、店铺等维度的成交额计算，根据订单order_amount汇总求和即可；

2、而对于品牌、大类、中类、小类等维度成交额计算，需要根据goods_id计算。

• 以品牌为例

--上述表的数据中，如果计算不同品牌的成交额，就不能再根据订单金额相加了
--而是必须根据每个订单中，这个品牌的金额进行计算
--因为订单中可以有不同的商品品牌。

• 分组去重

row_number() over(partition by order_id) as order_rn,
row_number() over(partition by order_id,g.brand_id) as brand_rn,
row_number() over(partition by order_id,g.max_class_name) as maxclass_rn,
row_number() over(partition by order_id,g.max_class_name,g.mid_class_name) as midclass_rn,
row_number() over(partition by order_id,g.max_class_name,g.mid_class_name,g.min_class_name) as minclass_rn,

--下面分组加入goods_id
row_number() over(partition by order_id,g.brand_id,o.goods_id) as brand_goods_rn,
row_number() over(partition by order_id,g.max_class_name,o.goods_id) as maxclass_goods_rn,
row_number() over(partition by order_id,g.max_class_name,g.mid_class_name,o.goods_id) as midclass_goods_rn,
row_number() over(partition by order_id,g.max_class_name,g.mid_class_name,g.min_class_name,o.goods_id) as minclass_goods_rn

---

销售主题宽表--step3--grouping sets分组

• 使用CTE表达式针对上面抽取字段、分组去重的结果进行引导

with  temp as (
    select 抽取字段、row_number去重)

注意，到这一步为止，temp表的数据已经和之前的我们创建的简易模型、复杂模型差不多了。 后面的技术主要就是case when+grouoing判断。

• 根据业务需求进行维度组合，使用grouping sets进行分组。

日期
日期+城市
日期+城市+商圈
日期+城市+商圈+店铺
日期+品牌
日期+大类
日期+大类+中类
日期+大类+中类+小类

with  temp as (
    select 抽取字段、row_number去重)

select
	xxxxx
from temp
group by
    grouping sets(
        create_date, --日期
        (create_date,city_id,city_name),--日期+城市
        (create_date,city_id,city_name,trade_area_id,trade_area_name),--日期+城市+商圈
        (create_date,city_id,city_name,trade_area_id,trade_area_name,store_id,store_name), --日期+城市+商圈+店铺
        (create_date,brand_id,brand_name),--日期+品牌
        (create_date,max_class_id,max_class_name),--日期+大类
        (create_date,max_class_id,max_class_name,mid_class_id,mid_class_name),--日期+大类+中类
        (create_date,max_class_id,max_class_name,mid_class_id,mid_class_name,min_class_id,min_class_name)--日期+大类+中类+小类
    );

---

销售主题宽表--step4--维度字段判断

提示：可以根据待插入的目标表yp_dws.dws_sale_daycount的字段顺序，把结果返回。

image-20211014153211908.png

case when grouping(city_id) = 0   --如果分组中包含city_id 则grouping为0 那么就返回city_id
		then city_id
		else null end as city_id ,
	case when grouping(city_id) = 0
		then city_name
		else null end as city_name ,
	case when grouping(trade_area_id) = 0--商圈
		then trade_area_id
		else null end as trade_area_id ,
	case when grouping(trade_area_id) = 0
		then trade_area_name
		else null end as trade_area_name ,
	case when grouping(store_id) = 0 --店铺
		then store_id
		else null end as store_id ,
	case when grouping(store_id) = 0
		then store_name
		else null end as store_name ,
	case when grouping(brand_id) = 0 --品牌
		then brand_id
		else null end as brand_id ,
	case when grouping(brand_id) = 0
		then brand_name
		else null end as brand_name ,
	case when grouping(max_class_id) = 0 --大类
		then max_class_id
		else null end as max_class_id ,
	case when grouping(max_class_id) = 0
		then max_class_name
		else null end as max_class_name ,
	case when grouping(mid_class_id) = 0 --中类
		then mid_class_id
		else null end as mid_class_id ,
	case when grouping(mid_class_id) = 0
		then mid_class_name
		else null end as mid_class_name ,
	case when grouping(min_class_id) = 0--小类
		then min_class_id
		else null end as min_class_id ,
	case when grouping(min_class_id) = 0
		then min_class_name
		else null end as min_class_name ,

	case when grouping(store_id,store_name) = 0  --分组类型
		then 'store'
		when grouping(trade_area_id ,trade_area_name) = 0
		then 'trade_area'
		when grouping (city_id,city_name) = 0
		then 'city'
		when grouping (brand_id,brand_name) = 0
		then 'brand'
		when grouping (min_class_id,min_class_name) = 0
		then 'min_class'
		when grouping (mid_class_id,mid_class_name) = 0
		then 'mid_class'
		when grouping (max_class_id,max_class_name) = 0
		then 'max_class'
		when grouping (create_date) = 0
		then 'all'
		else 'other' end as group_type,

---

销售主题宽表--step5--销售收入统计

	--指标计算 注意每个指标都对应着8个分组维度的计算
	--1、销售收入指标 sale_amt
	case when grouping(store_id,store_name) =0  --如果分组中包含店铺,则分组为：日期+城市+商圈+店铺
		then sum(if( order_rn = 1 and store_id is not null ,order_amount,0)) --只有分组中标号为1的(去重)，店铺不为空的才参与计算
		--then sum(if( order_rn = 1 and store_id is not null ,coalesce(order_amount,0),0))  --使用coalesce函数更加成熟

		when grouping (trade_area_id ,trade_area_name) = 0 --日期+城市+商圈
		then sum(if( order_rn = 1 and trade_area_id is not null ,order_amount,0))

		when grouping (city_id,city_name) = 0 --日期+城市
		then sum(if( order_rn = 1 and city_id is not null,order_amount,0))

		when grouping (brand_id,brand_name) = 0 --日期+品牌
		then sum(if(brand_goods_rn = 1 and brand_id is not null,total_price,0))

		when grouping (min_class_id,min_class_name) = 0 --日期+大类+中类+小类
		then sum(if(minclass_goods_rn = 1 and min_class_id is not null ,total_price,0))

		when grouping (mid_class_id,mid_class_name) = 0 --日期+大类+中类
		then sum(if(midclass_goods_rn = 1 and mid_class_id is not null,total_price,0))

		when grouping (max_class_id,max_class_name) = 0 ----日期+大类
		then sum(if(maxclass_goods_rn = 1 and max_class_id is not null ,total_price,0))

		when grouping (create_date) = 0 --日期
		then sum(if(order_rn=1 and create_date is not null,order_amount,0))
	else null end  as sale_amt,

---

销售主题宽表--step6--金额指标统计

    --2、平台收入 plat_amt
		case when grouping(store_id,store_name) =0
			then sum(if( order_rn = 1 and store_id is not null ,plat_fee,0))
			when grouping (trade_area_id ,trade_area_name) = 0
			then sum(if( order_rn = 1 and trade_area_id is not null ,plat_fee,0))
			when grouping (city_id,city_name) = 0
			then sum(if( order_rn = 1 and city_id is not null,plat_fee,0))
			when grouping (brand_id,brand_name) = 0
			then null
			when grouping (min_class_id,min_class_name) = 0
			then null
			when grouping (mid_class_id,mid_class_name) = 0
			then null
			when grouping (max_class_id,max_class_name) = 0
			then null
			when grouping (create_date) = 0
			then sum(if(order_rn=1 and create_date is not null,plat_fee,0))
			else null end  as plat_amt ,

	-- 3、配送成交额 deliver_sale_amt
		case when grouping(store_id,store_name) =0
			then sum(if( order_rn = 1 and store_id is not null and delievery_id is not null ,dispatcher_money,0))
			when grouping (trade_area_id ,trade_area_name) = 0
			then sum(if( order_rn = 1 and trade_area_id is not null and delievery_id is not null,dispatcher_money,0))
			when grouping (city_id,city_name) = 0
			then sum(if( order_rn = 1 and city_id is not null and delievery_id is not null,dispatcher_money,0))
			when grouping (brand_id,brand_name) = 0
			then null
			when grouping (min_class_id,min_class_name) = 0
			then null
			when grouping (mid_class_id,mid_class_name) = 0
			then null
			when grouping (max_class_id,max_class_name) = 0
			then null
			when grouping (create_date) = 0
			then sum(if(order_rn=1 and create_date is not null and delievery_id is not null ,dispatcher_money,0))
			else null end  as deliver_sale_amt ,

	-- 4、小程序成交额 mini_app_sale_amt
		case when grouping(store_id,store_name) =0
			then sum(if( order_rn = 1 and store_id is not null and order_from='miniapp' ,order_amount,0))
			when grouping (trade_area_id ,trade_area_name) = 0
			then sum(if( order_rn = 1 and trade_area_id is not null and order_from='miniapp',order_amount,0))
			when grouping (city_id,city_name) = 0
			then sum(if( order_rn = 1 and city_id is not null and order_from='miniapp',order_amount,0))
			when grouping (brand_id,brand_name) = 0
			then sum(if(brand_goods_rn = 1 and brand_id is not null and order_from='miniapp',total_price,0))
			when grouping (min_class_id,min_class_name) = 0
			then sum(if(minclass_goods_rn = 1 and min_class_id is not null and order_from='miniapp',total_price,0))
			when grouping (mid_class_id,mid_class_name) = 0
			then sum(if(midclass_goods_rn = 1 and mid_class_id is not null and order_from='miniapp',total_price,0))
			when grouping (max_class_id,max_class_name) = 0
			then sum(if(maxclass_goods_rn = 1 and max_class_id is not null and order_from='miniapp',total_price,0))
			when grouping (create_date) = 0
			then sum(if(order_rn=1 and create_date is not null and order_from='miniapp',order_amount ,0))
			else null end  as mini_app_sale_amt ,

	-- 5、安卓成交额 android_sale_amt
		case when grouping(store_id,store_name) =0
			then sum(if( order_rn = 1 and store_id is not null and order_from='android' ,order_amount,0))
			when grouping (trade_area_id ,trade_area_name) = 0
			then sum(if( order_rn = 1 and trade_area_id is not null and order_from='android',order_amount,0))
			when grouping (city_id,city_name) = 0
			then sum(if( order_rn = 1 and city_id is not null and order_from='android',order_amount,0))
			when grouping (brand_id,brand_name) = 0
			then sum(if(brand_goods_rn = 1 and brand_id is not null and order_from='android',total_price,0))
			when grouping (min_class_id,min_class_name) = 0
			then sum(if(minclass_goods_rn = 1 and min_class_id is not null and order_from='android',total_price,0))
			when grouping (mid_class_id,mid_class_name) = 0
			then sum(if(midclass_goods_rn = 1 and mid_class_id is not null and order_from='android',total_price,0))
			when grouping (max_class_id,max_class_name) = 0
			then sum(if(maxclass_goods_rn = 1 and max_class_id is not null and order_from='android',total_price,0))
			when grouping (create_date) = 0
			then sum(if(order_rn=1 and create_date is not null and order_from='android',order_amount ,0))
			else null end  as android_sale_amt ,

	-- 6、苹果成交额 ios_sale_amt
		case when grouping(store_id,store_name) =0
			then sum(if( order_rn = 1 and store_id is not null and order_from='ios' ,order_amount,0))
			when grouping (trade_area_id ,trade_area_name) = 0
			then sum(if( order_rn = 1 and trade_area_id is not null and order_from='ios',order_amount,0))
			when grouping (city_id,city_name) = 0
			then sum(if( order_rn = 1 and city_id is not null and order_from='ios',order_amount,0))
			when grouping (brand_id,brand_name) = 0
			then sum(if(brand_goods_rn = 1 and brand_id is not null and order_from='ios',total_price,0))
			when grouping (min_class_id,min_class_name) = 0
			then sum(if(minclass_goods_rn = 1 and min_class_id is not null and order_from='ios',total_price,0))
			when grouping (mid_class_id,mid_class_name) = 0
			then sum(if(midclass_goods_rn = 1 and mid_class_id is not null and order_from='ios',total_price,0))
			when grouping (max_class_id,max_class_name) = 0
			then sum(if(maxclass_goods_rn = 1 and max_class_id is not null and order_from='ios',total_price,0))
			when grouping (create_date) = 0
			then sum(if(order_rn=1 and create_date is not null and order_from='ios',order_amount ,0))
			else null end  as ios_sale_amt ,

	-- 7、pc成交额 pcweb_sale_amt
		case when grouping(store_id,store_name) =0
			then sum(if( order_rn = 1 and store_id is not null and order_from='pcweb' ,order_amount,0))
			when grouping (trade_area_id ,trade_area_name) = 0
			then sum(if( order_rn = 1 and trade_area_id is not null and order_from='pcweb',order_amount,0))
			when grouping (city_id,city_name) = 0
			then sum(if( order_rn = 1 and city_id is not null and order_from='pcweb',order_amount,0))
			when grouping (brand_id,brand_name) = 0
			then sum(if(brand_goods_rn = 1 and brand_id is not null and order_from='pcweb',total_price,0))
			when grouping (min_class_id,min_class_name) = 0
			then sum(if(minclass_goods_rn = 1 and min_class_id is not null and order_from='pcweb',total_price,0))
			when grouping (mid_class_id,mid_class_name) = 0
			then sum(if(midclass_goods_rn = 1 and mid_class_id is not null and order_from='pcweb',total_price,0))
			when grouping (max_class_id,max_class_name) = 0
			then sum(if(maxclass_goods_rn = 1 and max_class_id is not null and order_from='pcweb',total_price,0))
			when grouping (create_date) = 0
			then sum(if(order_rn=1 and create_date is not null and order_from='pcweb',order_amount ,0))
			else null end  as pcweb_sale_amt ,

---

销售主题宽表--step7--订单量指标统计

    -- 8、订单量 order_cnt
		case when grouping(store_id,store_name) =0
			then count(if(order_rn=1 and store_id is not null , order_id,null))
			when grouping (trade_area_id ,trade_area_name) = 0
			then count(if(order_rn=1 and trade_area_id is not null , order_id,null))
			when grouping (city_id,city_name) = 0
			then count(if(order_rn=1 and city_id is not null , order_id,null))
			when grouping (brand_id,brand_name) = 0
			then count(if(brand_rn=1 and brand_id is not null , order_id,null))
			when grouping (min_class_id,min_class_name) = 0
			then count(if(minclass_rn=1 and min_class_id is not null , order_id,null))
			when grouping (mid_class_id,mid_class_name) = 0
			then count(if(midclass_rn=1 and mid_class_id is not null , order_id,null))
			when grouping (max_class_id,max_class_name) = 0
			then count(if(maxclass_rn=1 and max_class_id is not null , order_id,null))
			when grouping (create_date) = 0
			then count(if(order_rn=1 , order_id,null))
			else null end  as order_cnt ,

	--9、 参评单量 eva_order_cnt
		case when grouping(store_id,store_name) =0
			then count(if(order_rn=1 and store_id is not null and evaluation_id is not null , order_id,null))
			when grouping (trade_area_id ,trade_area_name) = 0
			then count(if(order_rn=1 and trade_area_id is not null and evaluation_id is not null , order_id,null))
			when grouping (city_id,city_name) = 0
			then count(if(order_rn=1 and city_id is not null and evaluation_id is not null , order_id,null))
			when grouping (brand_id,brand_name) = 0
			then count(if(brand_rn=1 and brand_id is not null and evaluation_id is not null , order_id,null))
			when grouping (min_class_id,min_class_name) = 0
			then count(if(minclass_rn=1 and min_class_id is not null and evaluation_id is not null , order_id,null))
			when grouping (mid_class_id,mid_class_name) = 0
			then count(if(midclass_rn=1 and mid_class_id is not null  and evaluation_id is not null, order_id,null))
			when grouping (max_class_id,max_class_name) = 0
			then count(if(maxclass_rn=1 and max_class_id is not null  and evaluation_id is not null, order_id,null))
			when grouping (create_date) = 0
			then count(if(order_rn=1 and evaluation_id is not null, order_id,null))
			else null end  as eva_order_cnt ,
	--10、差评单量 bad_eva_order_cnt
		case when grouping(store_id,store_name) =0
			then count(if(order_rn=1 and store_id is not null and evaluation_id is not null and coalesce(geval_scores,0) <6 , order_id,null))
			when grouping (trade_area_id ,trade_area_name) = 0
			then count(if(order_rn=1 and trade_area_id is not null and evaluation_id is not null and coalesce(geval_scores,0) <6, order_id,null))
			when grouping (city_id,city_name) = 0
			then count(if(order_rn=1 and city_id is not null and evaluation_id is not null and coalesce(geval_scores,0) <6, order_id,null))
			when grouping (brand_id,brand_name) = 0
			then count(if(brand_rn=1 and brand_id is not null and evaluation_id is not null and coalesce(geval_scores,0) <6, order_id,null))
			when grouping (min_class_id,min_class_name) = 0
			then count(if(minclass_rn=1 and min_class_id is not null and evaluation_id is not null and coalesce(geval_scores,0) <6, order_id,null))
			when grouping (mid_class_id,mid_class_name) = 0
			then count(if(midclass_rn=1 and mid_class_id is not null  and evaluation_id is not null and coalesce(geval_scores,0) <6, order_id,null))
			when grouping (max_class_id,max_class_name) = 0
			then count(if(maxclass_rn=1 and max_class_id is not null  and evaluation_id is not null and coalesce(geval_scores,0) <6, order_id,null))
			when grouping (create_date) = 0
			then count(if(order_rn=1 and evaluation_id is not null and coalesce(geval_scores,0) <6, order_id,null))
			else null end  as bad_eva_order_cnt ,

	--11、配送单量 deliver_order_cnt
		case when grouping(store_id,store_name) =0
			then count(if(order_rn=1 and store_id is not null and delievery_id is not null, order_id,null))
			when grouping (trade_area_id ,trade_area_name) = 0
			then count(if(order_rn=1 and trade_area_id is not null and delievery_id is not null, order_id,null))
			when grouping (city_id,city_name) = 0
			then count(if(order_rn=1 and city_id is not null and delievery_id is not null, order_id,null))
			when grouping (brand_id,brand_name) = 0
			then count(if(brand_rn=1 and brand_id is not null and delievery_id is not null, order_id,null))
			when grouping (min_class_id,min_class_name) = 0
			then count(if(minclass_rn=1 and min_class_id is not null and delievery_id is not null, order_id,null))
			when grouping (mid_class_id,mid_class_name) = 0
			then count(if(midclass_rn=1 and mid_class_id is not null  and delievery_id is not null, order_id,null))
			when grouping (max_class_id,max_class_name) = 0
			then count(if(maxclass_rn=1 and max_class_id is not null and delievery_id is not null, order_id,null))
			when grouping (create_date) = 0
			then count(if(order_rn=1 and delievery_id is not null, order_id,null))
			else null end  as deliver_order_cnt ,

	--12、退款单量 refund_order_cnt
		case when grouping(store_id,store_name) =0
			then count(if(order_rn=1 and store_id is not null and refund_id is not null, order_id,null))
			when grouping (trade_area_id ,trade_area_name) = 0
			then count(if(order_rn=1 and trade_area_id is not null and refund_id is not null, order_id,null))
			when grouping (city_id,city_name) = 0
			then count(if(order_rn=1 and city_id is not null and refund_id is not null, order_id,null))
			when grouping (brand_id,brand_name) = 0
			then count(if(brand_rn=1 and brand_id is not null and refund_id is not null, order_id,null))
			when grouping (min_class_id,min_class_name) = 0
			then count(if(minclass_rn=1 and min_class_id is not null and refund_id is not null, order_id,null))
			when grouping (mid_class_id,mid_class_name) = 0
			then count(if(midclass_rn=1 and mid_class_id is not null  and refund_id is not null, order_id,null))
			when grouping (max_class_id,max_class_name) = 0
			then count(if(maxclass_rn=1 and max_class_id is not null and refund_id is not null, order_id,null))
			when grouping (create_date) = 0
			then count(if(order_rn=1 and refund_id is not null, order_id,null))
			else null end  as refund_order_cnt ,

	-- 13、小程序订单量 miniapp_order_cnt
		case when grouping(store_id,store_name) =0
			then count(if(order_rn=1 and store_id is not null and order_from = 'miniapp', order_id,null))
			when grouping (trade_area_id ,trade_area_name) = 0
			then count(if(order_rn=1 and trade_area_id is not null and order_from = 'miniapp', order_id,null))
			when grouping (city_id,city_name) = 0
			then count(if(order_rn=1 and city_id is not null and order_from = 'miniapp', order_id,null))
			when grouping (brand_id,brand_name) = 0
			then count(if(brand_rn=1 and brand_id is not null and order_from = 'miniapp', order_id,null))
			when grouping (min_class_id,min_class_name) = 0
			then count(if(minclass_rn=1 and min_class_id is not null and order_from = 'miniapp', order_id,null))
			when grouping (mid_class_id,mid_class_name) = 0
			then count(if(midclass_rn=1 and mid_class_id is not null  and order_from = 'miniapp', order_id,null))
			when grouping (max_class_id,max_class_name) = 0
			then count(if(maxclass_rn=1 and max_class_id is not null and order_from = 'miniapp', order_id,null))
			when grouping (create_date) = 0
			then count(if(order_rn=1 and order_from = 'miniapp', order_id,null))
			else null end  as miniapp_order_cnt ,

	-- 14、android订单量 android_order_cnt
		case when grouping(store_id,store_name) =0
			then count(if(order_rn=1 and store_id is not null and order_from = 'android', order_id,null))
			when grouping (trade_area_id ,trade_area_name) = 0
			then count(if(order_rn=1 and trade_area_id is not null and order_from = 'android', order_id,null))
			when grouping (city_id,city_name) = 0
			then count(if(order_rn=1 and city_id is not null and order_from = 'android', order_id,null))
			when grouping (brand_id,brand_name) = 0
			then count(if(brand_rn=1 and brand_id is not null and order_from = 'android', order_id,null))
			when grouping (min_class_id,min_class_name) = 0
			then count(if(minclass_rn=1 and min_class_id is not null and order_from = 'android', order_id,null))
			when grouping (mid_class_id,mid_class_name) = 0
			then count(if(midclass_rn=1 and mid_class_id is not null  and order_from = 'android', order_id,null))
			when grouping (max_class_id,max_class_name) = 0
			then count(if(maxclass_rn=1 and max_class_id is not null and order_from = 'android', order_id,null))
			when grouping (create_date) = 0
			then count(if(order_rn=1 and order_from = 'android', order_id,null))
			else null end  as android_order_cnt ,

	-- 15、ios订单量 ios_order_cnt
		case when grouping(store_id,store_name) =0
			then count(if(order_rn=1 and store_id is not null and order_from = 'ios', order_id,null))
			when grouping (trade_area_id ,trade_area_name) = 0
			then count(if(order_rn=1 and trade_area_id is not null and order_from = 'ios', order_id,null))
			when grouping (city_id,city_name) = 0
			then count(if(order_rn=1 and city_id is not null and order_from = 'ios', order_id,null))
			when grouping (brand_id,brand_name) = 0
			then count(if(brand_rn=1 and brand_id is not null and order_from = 'ios', order_id,null))
			when grouping (min_class_id,min_class_name) = 0
			then count(if(minclass_rn=1 and min_class_id is not null and order_from = 'ios', order_id,null))
			when grouping (mid_class_id,mid_class_name) = 0
			then count(if(midclass_rn=1 and mid_class_id is not null  and order_from = 'ios', order_id,null))
			when grouping (max_class_id,max_class_name) = 0
			then count(if(maxclass_rn=1 and max_class_id is not null and order_from = 'ios', order_id,null))
			when grouping (create_date) = 0
			then count(if(order_rn=1 and order_from = 'ios', order_id,null))
			else null end  as ios_order_cnt ,

	--16、pcweb订单量 pcweb_order_cnt
		case when grouping(store_id,store_name) =0
			then count(if(order_rn=1 and store_id is not null and order_from = 'pcweb', order_id,null))
			when grouping (trade_area_id ,trade_area_name) = 0
			then count(if(order_rn=1 and trade_area_id is not null and order_from = 'pcweb', order_id,null))
			when grouping (city_id,city_name) = 0
			then count(if(order_rn=1 and city_id is not null and order_from = 'pcweb', order_id,null))
			when grouping (brand_id,brand_name) = 0
			then count(if(brand_rn=1 and brand_id is not null and order_from = 'pcweb', order_id,null))
			when grouping (min_class_id,min_class_name) = 0
			then count(if(minclass_rn=1 and min_class_id is not null and order_from = 'pcweb', order_id,null))
			when grouping (mid_class_id,mid_class_name) = 0
			then count(if(midclass_rn=1 and mid_class_id is not null  and order_from = 'pcweb', order_id,null))
			when grouping (max_class_id,max_class_name) = 0
			then count(if(maxclass_rn=1 and max_class_id is not null and order_from = 'pcweb', order_id,null))
			when grouping (create_date) = 0
			then count(if(order_rn=1 and order_from = 'pcweb', order_id,null))
			else null end  as pcweb_order_cnt ,

---

销售主题宽表--最终完整版sql实现

-------------------------------老师课堂代码----------------------------------------
insert into   yp_dws.dws_sale_daycount
select * from(
with temp as (
    select
           o.dt as create_time  ,  --o.dt,
           sd.province_id,
           sd.province_name,
           sd.city_id,
           sd.city_name,
           sd.trade_area_id,
           sd.trade_area_name,
           sd.store_name,
           o.store_id,
           gd.brand_id,
           gd.brand_name,
           gd.max_class_id,
           gd.max_class_name,
           gd.mid_class_id,
           gd.mid_class_name,
           gd.min_class_id,
           gd.min_class_name,

           -- 指标字段:
           o.order_id,                                                -- 订单id 计算订单量
           o.order_amount,                                            -- 订单销售收入
           o.goods_amount,                                            -- 商品销售金额
           o.plat_fee,                                                -- 平台利润
           o.delivery_fee,                                            -- 配送运费
           -- 用于判断的字段
           o.order_from,
           o.evaluation_id,                                           -- 评价表 id  如果不为null, 说明订单有评价信息的
           o.delievery_id,                                            -- 配送表id
           o.geval_scores,                                            -- 评分信息
           o.refund_id,
           row_number() over (partition by order_id)          as rk1, -- 去重
           row_number() over (partition by order_id,goods_id) as rk2  -- 去重
    from (select * from yp_dwb.dwb_order_detail where is_pay = 1 and order_state not in (1, 7)) as o
             left join yp_dwb.dwb_goods_detail gd on o.goods_id = gd.id
             left join yp_dwb.dwb_shop_detail sd on o.store_id = sd.id
)
select
  -- 维度
    city_id,
    city_name,
    trade_area_id,
    trade_area_name,
    store_id,
    store_name,
    brand_id,
    brand_name,
    max_class_id,
    max_class_name,
    mid_class_id,
    mid_class_name,
    min_class_id,
    min_class_name,
    case when grouping(store_id) = 0
           then 'store'
         when grouping(trade_area_id) = 0
           then 'trade_area'
         when grouping(city_id) = 0
           then 'city'
         when grouping(min_class_id)  = 0
           then 'min_class'
         when grouping(mid_class_id)  = 0
           then 'mid_class'
         when grouping(max_class_id)  = 0
           then 'max_class'
         when grouping(brand_id)  = 0
           then 'brand'
         when grouping(create_time) = 0
           then 'all'
         else
            'other'
    end as group_type,

   -- 指标
   case when grouping(store_id) = 0    -- 总成交额
         then sum(if(rk1 = 1 and store_id is not null, coalesce(order_amount,0),0))
        when grouping(trade_area_id) = 0
         then sum(if(rk1 = 1 and trade_area_id is not null, coalesce(order_amount,0),0))
        when grouping(city_id) = 0
         then sum(if(rk1 = 1 and city_id is not null, coalesce(order_amount,0),0))
        when grouping(min_class_id)  = 0
         then sum(if(rk2 = 1 and min_class_id is not null,coalesce(goods_amount,0),0))
        when grouping(mid_class_id)  = 0
         then sum(if(rk2 = 1 and mid_class_id is not null,coalesce(goods_amount,0),0))
        when grouping(max_class_id)  = 0
         then sum(if(rk2 = 1 and max_class_id is not null,coalesce(goods_amount,0),0))
        when grouping(brand_id)  = 0
         then sum(if(rk2 = 1 and brand_id is not null,coalesce(goods_amount,0),0))
        when grouping(create_time) = 0
         then sum(if(rk1 = 1 and create_time is not null,coalesce(order_amount,0),0)) -- 日期
   end as sale_amt,

   case when grouping(store_id) = 0    -- 平台收入
         then sum(if(rk1 = 1 and store_id is not null, coalesce(plat_fee,0),0))
        when grouping(trade_area_id) = 0
         then sum(if(rk1 = 1 and trade_area_id is not null, coalesce(plat_fee,0),0))
        when grouping(city_id) = 0
         then sum(if(rk1 = 1 and city_id is not null, coalesce(plat_fee,0),0))
        when grouping(min_class_id)  = 0
         then sum(if(rk2 = 1 and min_class_id is not null,coalesce(plat_fee,0),0))
        when grouping(mid_class_id)  = 0
         then sum(if(rk2 = 1 and mid_class_id is not null,coalesce(plat_fee,0),0))
        when grouping(max_class_id)  = 0
         then sum(if(rk2 = 1 and max_class_id is not null,coalesce(plat_fee,0),0))
        when grouping(brand_id)  = 0
         then sum(if(rk2 = 1 and brand_id is not null,coalesce(plat_fee,0),0))
        when grouping(create_time) = 0
         then sum(if(rk1 = 1 and create_time is not null,coalesce(plat_fee,0),0)) -- 日期
   end   as plat_amt,

   case when grouping(store_id) = 0    -- 配送成交额
         then sum(if(rk1 = 1 and store_id is not null, coalesce(delivery_fee,0),0))
        when grouping(trade_area_id) = 0
         then sum(if(rk1 = 1 and trade_area_id is not null, coalesce(delivery_fee,0),0))
        when grouping(city_id) = 0
         then sum(if(rk1 = 1 and city_id is not null, coalesce(delivery_fee,0),0))
        when grouping(min_class_id)  = 0
         then sum(if(rk2 = 1 and min_class_id is not null,coalesce(delivery_fee,0),0))
        when grouping(mid_class_id)  = 0
         then sum(if(rk2 = 1 and mid_class_id is not null,coalesce(delivery_fee,0),0))
        when grouping(max_class_id)  = 0
         then sum(if(rk2 = 1 and max_class_id is not null,coalesce(delivery_fee,0),0))
        when grouping(brand_id)  = 0
         then sum(if(rk2 = 1 and brand_id is not null,coalesce(delivery_fee,0),0))
        when grouping(create_time) = 0
         then sum(if(rk1 = 1 and create_time is not null,coalesce(delivery_fee,0),0)) -- 日期
   end   as  deliver_sale_amt,

   case when grouping(store_id) = 0    -- 小程序miniapp成交额
         then sum(if(rk1 = 1 and store_id is not null and order_from = 'miniapp', coalesce(order_amount,0),0))
        when grouping(trade_area_id) = 0
         then sum(if(rk1 = 1 and trade_area_id is not null and order_from = 'miniapp', coalesce(order_amount,0),0))
        when grouping(city_id) = 0
         then sum(if(rk1 = 1 and city_id is not null and order_from = 'miniapp', coalesce(order_amount,0),0))
        when grouping(min_class_id)  = 0
         then sum(if(rk2 = 1 and min_class_id is not null  and order_from = 'miniapp',coalesce(goods_amount,0),0))
        when grouping(mid_class_id)  = 0
         then sum(if(rk2 = 1 and mid_class_id is not null  and order_from = 'miniapp',coalesce(goods_amount,0),0))
        when grouping(max_class_id)  = 0
         then sum(if(rk2 = 1 and max_class_id is not null  and order_from = 'miniapp',coalesce(goods_amount,0),0))
        when grouping(brand_id)  = 0
         then sum(if(rk2 = 1 and brand_id is not null  and order_from = 'miniapp',coalesce(goods_amount,0),0))
        when grouping(create_time) = 0
         then sum(if(rk1 = 1 and create_time is not null  and order_from = 'miniapp',coalesce(order_amount,0),0)) -- 日期
   end as   mini_app_sale_amt,

    case when grouping(store_id) = 0    -- android成交额
         then sum(if(rk1 = 1 and store_id is not null and order_from = 'android', coalesce(order_amount,0),0))
        when grouping(trade_area_id) = 0
         then sum(if(rk1 = 1 and trade_area_id is not null and order_from = 'android', coalesce(order_amount,0),0))
        when grouping(city_id) = 0
         then sum(if(rk1 = 1 and city_id is not null and order_from = 'android', coalesce(order_amount,0),0))
        when grouping(min_class_id)  = 0
         then sum(if(rk2 = 1 and min_class_id is not null  and order_from = 'android',coalesce(goods_amount,0),0))
        when grouping(mid_class_id)  = 0
         then sum(if(rk2 = 1 and mid_class_id is not null  and order_from = 'android',coalesce(goods_amount,0),0))
        when grouping(max_class_id)  = 0
         then sum(if(rk2 = 1 and max_class_id is not null  and order_from = 'android',coalesce(goods_amount,0),0))
        when grouping(brand_id)  = 0
         then sum(if(rk2 = 1 and brand_id is not null  and order_from = 'android',coalesce(goods_amount,0),0))
        when grouping(create_time) = 0
         then sum(if(rk1 = 1 and create_time is not null  and order_from = 'android',coalesce(order_amount,0),0)) -- 日期
   end as    android_sale_amt,

    case when grouping(store_id) = 0    -- ios成交额
         then sum(if(rk1 = 1 and store_id is not null and order_from = 'ios', coalesce(order_amount,0),0))
        when grouping(trade_area_id) = 0
         then sum(if(rk1 = 1 and trade_area_id is not null and order_from = 'ios', coalesce(order_amount,0),0))
        when grouping(city_id) = 0
         then sum(if(rk1 = 1 and city_id is not null and order_from = 'ios', coalesce(order_amount,0),0))
        when grouping(min_class_id)  = 0
         then sum(if(rk2 = 1 and min_class_id is not null  and order_from = 'ios',coalesce(goods_amount,0),0))
        when grouping(mid_class_id)  = 0
         then sum(if(rk2 = 1 and mid_class_id is not null  and order_from = 'ios',coalesce(goods_amount,0),0))
        when grouping(max_class_id)  = 0
         then sum(if(rk2 = 1 and max_class_id is not null  and order_from = 'ios',coalesce(goods_amount,0),0))
        when grouping(brand_id)  = 0
         then sum(if(rk2 = 1 and brand_id is not null  and order_from = 'ios',coalesce(goods_amount,0),0))
        when grouping(create_time) = 0
         then sum(if(rk1 = 1 and create_time is not null  and order_from = 'ios',coalesce(order_amount,0),0)) -- 日期
   end as  ios_sale_amt,

    case when grouping(store_id) = 0    -- pcweb成交额
         then sum(if(rk1 = 1 and store_id is not null and order_from = 'pcweb', coalesce(order_amount,0),0))
        when grouping(trade_area_id) = 0
         then sum(if(rk1 = 1 and trade_area_id is not null and order_from = 'pcweb', coalesce(order_amount,0),0))
        when grouping(city_id) = 0
         then sum(if(rk1 = 1 and city_id is not null and order_from = 'pcweb', coalesce(order_amount,0),0))
        when grouping(min_class_id)  = 0
         then sum(if(rk2 = 1 and min_class_id is not null  and order_from = 'pcweb',coalesce(goods_amount,0),0))
        when grouping(mid_class_id)  = 0
         then sum(if(rk2 = 1 and mid_class_id is not null  and order_from = 'pcweb',coalesce(goods_amount,0),0))
        when grouping(max_class_id)  = 0
         then sum(if(rk2 = 1 and max_class_id is not null  and order_from = 'pcweb',coalesce(goods_amount,0),0))
        when grouping(brand_id)  = 0
         then sum(if(rk2 = 1 and brand_id is not null  and order_from = 'pcweb',coalesce(goods_amount,0),0))
        when grouping(create_time) = 0
         then sum(if(rk1 = 1 and create_time is not null  and order_from = 'pcweb',coalesce(order_amount,0),0)) -- 日期
   end as   pcweb_sale_amt,

   case when grouping(store_id) = 0   -- 成交单量
         then count(if(rk1 = 1 and store_id is not null , order_id,null))
        when grouping(trade_area_id) = 0
         then count(if(rk1 = 1 and trade_area_id is not null , order_id,null))
        when grouping(city_id) = 0
         then count(if(rk1 = 1 and city_id is not null , order_id,null))
        when grouping(min_class_id)  = 0
         then count(distinct  if(rk2 = 1 and min_class_id is not null , order_id,null))
        when grouping(mid_class_id)  = 0
         then count(distinct if(rk2 = 1 and mid_class_id is not null  , order_id,null))
        when grouping(max_class_id)  = 0
         then count(distinct if(rk2 = 1 and max_class_id is not null  , order_id,null))
        when grouping(brand_id)  = 0
         then count(distinct if(rk2 = 1 and brand_id is not null  , order_id,null))
        when grouping(create_time) = 0
         then count(if(rk1 = 1 and create_time is not null  , order_id,null)) -- 日期
   end as   order_cnt,

   case when grouping(store_id) = 0   -- 参评单量
         then count(if(rk1 = 1 and store_id is not null and evaluation_id is not null , order_id,null))
        when grouping(trade_area_id) = 0
         then count(if(rk1 = 1 and trade_area_id is not null and evaluation_id is not null , order_id,null))
        when grouping(city_id) = 0
         then count(if(rk1 = 1 and city_id is not null and evaluation_id is not null, order_id,null))
        when grouping(min_class_id)  = 0
         then count(distinct  if(rk2 = 1 and min_class_id is not null and evaluation_id is not null, order_id,null))
        when grouping(mid_class_id)  = 0
         then count(distinct if(rk2 = 1 and mid_class_id is not null and evaluation_id is not null , order_id,null))
        when grouping(max_class_id)  = 0
         then count(distinct if(rk2 = 1 and max_class_id is not null and evaluation_id is not null , order_id,null))
        when grouping(brand_id)  = 0
         then count(distinct if(rk2 = 1 and brand_id is not null and evaluation_id is not null , order_id,null))
        when grouping(create_time) = 0
         then count(if(rk1 = 1 and create_time is not null and evaluation_id is not null , order_id,null)) -- 日期
   end as   eva_order_cnt,

 case when grouping(store_id) = 0   -- 差评单量
         then count(if(rk1 = 1 and store_id is not null and evaluation_id is not null  and geval_scores < 6 , order_id,null))
        when grouping(trade_area_id) = 0
         then count(if(rk1 = 1 and trade_area_id is not null and evaluation_id is not null and geval_scores < 6 , order_id,null))
        when grouping(city_id) = 0
         then count(if(rk1 = 1 and city_id is not null and evaluation_id is not null and geval_scores < 6, order_id,null))
        when grouping(min_class_id)  = 0
         then count(distinct  if(rk2 = 1 and min_class_id is not null and evaluation_id is not null and geval_scores < 6, order_id,null))
        when grouping(mid_class_id)  = 0
         then count(distinct if(rk2 = 1 and mid_class_id is not null and evaluation_id is not null and geval_scores < 6 , order_id,null))
        when grouping(max_class_id)  = 0
         then count(distinct if(rk2 = 1 and max_class_id is not null and evaluation_id is not null  and geval_scores < 6, order_id,null))
        when grouping(brand_id)  = 0
         then count(distinct if(rk2 = 1 and brand_id is not null and evaluation_id is not null and geval_scores < 6 , order_id,null))
        when grouping(create_time) = 0
         then count(if(rk1 = 1 and create_time is not null and evaluation_id is not null and geval_scores < 6 , order_id,null)) -- 日期
   end as    bad_eva_order_cnt,

    case when grouping(store_id) = 0   -- 配送单量
         then count(if(rk1 = 1 and store_id is not null and delievery_id is not null , order_id,null))
        when grouping(trade_area_id) = 0
         then count(if(rk1 = 1 and trade_area_id is not null  and delievery_id is not null , order_id,null))
        when grouping(city_id) = 0
         then count(if(rk1 = 1 and city_id is not null  and delievery_id is not null, order_id,null))
        when grouping(min_class_id)  = 0
         then count(distinct  if(rk2 = 1 and min_class_id is not null  and delievery_id is not null, order_id,null))
        when grouping(mid_class_id)  = 0
         then count(distinct if(rk2 = 1 and mid_class_id is not null and delievery_id is not null , order_id,null))
        when grouping(max_class_id)  = 0
         then count(distinct if(rk2 = 1 and max_class_id is not null and delievery_id is not null, order_id,null))
        when grouping(brand_id)  = 0
         then count(distinct if(rk2 = 1 and brand_id is not null and delievery_id is not null, order_id,null))
        when grouping(create_time) = 0
         then count(if(rk1 = 1 and create_time is not null and delievery_id is not null , order_id,null)) -- 日期
   end as    deliver_order_cnt,

 case when grouping(store_id) = 0   -- 退款单量
         then count(if(rk1 = 1 and store_id is not null and refund_id is not null , order_id,null))
        when grouping(trade_area_id) = 0
         then count(if(rk1 = 1 and trade_area_id is not null  and refund_id is not null , order_id,null))
        when grouping(city_id) = 0
         then count(if(rk1 = 1 and city_id is not null  and refund_id is not null, order_id,null))
        when grouping(min_class_id)  = 0
         then count(distinct  if(rk2 = 1 and min_class_id is not null  and refund_id is not null, order_id,null))
        when grouping(mid_class_id)  = 0
         then count(distinct if(rk2 = 1 and mid_class_id is not null and refund_id is not null , order_id,null))
        when grouping(max_class_id)  = 0
         then count(distinct if(rk2 = 1 and max_class_id is not null and refund_id is not null, order_id,null))
        when grouping(brand_id)  = 0
         then count(distinct if(rk2 = 1 and brand_id is not null and refund_id is not null, order_id,null))
        when grouping(create_time) = 0
         then count(if(rk1 = 1 and create_time is not null and refund_id is not null , order_id,null)) -- 日期
   end as    refund_order_cnt,   -- 退款单量

 case when grouping(store_id) = 0   -- 小程序成交单量
         then count(if(rk1 = 1 and store_id is not null and order_from = 'miniapp' , order_id,null))
        when grouping(trade_area_id) = 0
         then count(if(rk1 = 1 and trade_area_id is not null  and order_from = 'miniapp' , order_id,null))
        when grouping(city_id) = 0
         then count(if(rk1 = 1 and city_id is not null  and order_from = 'miniapp', order_id,null))
        when grouping(min_class_id)  = 0
         then count(distinct  if(rk2 = 1 and min_class_id is not null   and order_from = 'miniapp', order_id,null))
        when grouping(mid_class_id)  = 0
         then count(distinct if(rk2 = 1 and mid_class_id is not null  and order_from = 'miniapp' , order_id,null))
        when grouping(max_class_id)  = 0
         then count(distinct if(rk2 = 1 and max_class_id is not null  and order_from = 'miniapp', order_id,null))
        when grouping(brand_id)  = 0
         then count(distinct if(rk2 = 1 and brand_id is not null   and order_from = 'miniapp', order_id,null))
        when grouping(create_time) = 0
         then count(if(rk1 = 1 and create_time is not null  and order_from = 'miniapp' , order_id,null)) -- 日期
   end as  miniapp_order_cnt,
  case when grouping(store_id) = 0  -- 安卓APP订单量
         then count(if(rk1 = 1 and store_id is not null and order_from = 'android' , order_id,null))
        when grouping(trade_area_id) = 0
         then count(if(rk1 = 1 and trade_area_id is not null  and order_from = 'android' , order_id,null))
        when grouping(city_id) = 0
         then count(if(rk1 = 1 and city_id is not null  and order_from = 'android', order_id,null))
        when grouping(min_class_id)  = 0
         then count(distinct  if(rk2 = 1 and min_class_id is not null   and order_from = 'android', order_id,null))
        when grouping(mid_class_id)  = 0
         then count(distinct if(rk2 = 1 and mid_class_id is not null  and order_from = 'android' , order_id,null))
        when grouping(max_class_id)  = 0
         then count(distinct if(rk2 = 1 and max_class_id is not null  and order_from = 'android', order_id,null))
        when grouping(brand_id)  = 0
         then count(distinct if(rk2 = 1 and brand_id is not null   and order_from = 'android', order_id,null))
        when grouping(create_time) = 0
         then count(if(rk1 = 1 and create_time is not null  and order_from = 'android' , order_id,null)) -- 日期
   end as   android_order_cnt,
 case when grouping(store_id) = 0  -- ios订单量
         then count(if(rk1 = 1 and store_id is not null and order_from = 'ios' , order_id,null))
        when grouping(trade_area_id) = 0
         then count(if(rk1 = 1 and trade_area_id is not null  and order_from = 'ios' , order_id,null))
        when grouping(city_id) = 0
         then count(if(rk1 = 1 and city_id is not null  and order_from = 'ios', order_id,null))
        when grouping(min_class_id)  = 0
         then count(distinct  if(rk2 = 1 and min_class_id is not null   and order_from = 'ios', order_id,null))
        when grouping(mid_class_id)  = 0
         then count(distinct if(rk2 = 1 and mid_class_id is not null  and order_from = 'ios' , order_id,null))
        when grouping(max_class_id)  = 0
         then count(distinct if(rk2 = 1 and max_class_id is not null  and order_from = 'ios', order_id,null))
        when grouping(brand_id)  = 0
         then count(distinct if(rk2 = 1 and brand_id is not null   and order_from = 'ios', order_id,null))
        when grouping(create_time) = 0
         then count(if(rk1 = 1 and create_time is not null  and order_from = 'ios' , order_id,null)) -- 日期
   end as    ios_order_cnt,
    case when grouping(store_id) = 0  -- ios订单量
         then count(if(rk1 = 1 and store_id is not null and order_from = 'pcweb' , order_id,null))
        when grouping(trade_area_id) = 0
         then count(if(rk1 = 1 and trade_area_id is not null  and order_from = 'pcweb' , order_id,null))
        when grouping(city_id) = 0
         then count(if(rk1 = 1 and city_id is not null  and order_from = 'pcweb', order_id,null))
        when grouping(min_class_id)  = 0
         then count(distinct  if(rk2 = 1 and min_class_id is not null   and order_from = 'pcweb', order_id,null))
        when grouping(mid_class_id)  = 0
         then count(distinct if(rk2 = 1 and mid_class_id is not null  and order_from = 'pcweb' , order_id,null))
        when grouping(max_class_id)  = 0
         then count(distinct if(rk2 = 1 and max_class_id is not null  and order_from = 'pcweb', order_id,null))
        when grouping(brand_id)  = 0
         then count(distinct if(rk2 = 1 and brand_id is not null   and order_from = 'pcweb', order_id,null))
        when grouping(create_time) = 0
         then count(if(rk1 = 1 and create_time is not null  and order_from = 'pcweb' , order_id,null)) -- 日期
   end as    pcweb_order_cnt,     -- PC商城成交单量
    create_time as dt
from temp
group by
grouping sets(
  create_time,
  (create_time,city_id,city_name),
  (create_time,city_id,city_name,trade_area_id,trade_area_name),
  (create_time,city_id,city_name,trade_area_id,trade_area_name,store_id,store_name),
  (create_time,brand_id,brand_name),
  (create_time,max_class_id,max_class_name),
  (create_time,max_class_id,max_class_name,mid_class_id,mid_class_name),
  (create_time,max_class_id,max_class_name,mid_class_id,mid_class_name,min_class_id,min_class_name)
  )
)
-------------------------------参考代码----------------------------------------
insert into  hive.yp_dws.dws_sale_daycount
with temp as (select
    --维度抽取
    o.dt as create_date,  --日期
    s.city_id,
    s.city_name,--城市
    s.trade_area_id,
    s.trade_area_name,--商圈
    s.id as store_id,
    s.store_name,--店铺
    g.brand_id,
    g.brand_name, --品牌
    g.max_class_id,
    g.max_class_name,--商品大类
    g.mid_class_id,
    g.mid_class_name,--商品中类
    g.min_class_id,
    g.min_class_name, --商品小类

    --订单量指标
    o.order_id, --订单ID
    o.goods_id, --商品ID


    --金额指标
    o.order_amount,--订单金额
    o.total_price,--商品金额
    o.plat_fee, --平台分润
    o.dispatcher_money,--配送员运费

    --判断条件
    o.order_from,--订单来源：安卓，苹果啥的...
    o.evaluation_id,--评论单ID（如果不为null,表示该订单有评价）
    o.geval_scores, --订单评分（用于计算差评）
    o.delievery_id, --配送单ID(如果不为null，表示是配送单，其他还有可能是自提、商家配送)
    o.refund_id, --退款单ID(如果不为null,表示有退款)

    --分组去重
    row_number() over(partition by order_id) as order_rn,
    row_number() over(partition by order_id,g.brand_id) as brand_rn,
    row_number() over(partition by order_id,g.max_class_name) as maxclass_rn,
    row_number() over(partition by order_id,g.max_class_name,g.mid_class_name) as midclass_rn,
    row_number() over(partition by order_id,g.max_class_name,g.mid_class_name,g.min_class_name) as minclass_rn,

    --下面分组加入goods_id
    row_number() over(partition by order_id,g.brand_id,o.goods_id) as brand_goods_rn,
    row_number() over(partition by order_id,g.max_class_name,o.goods_id) as maxclass_goods_rn,
    row_number() over(partition by order_id,g.max_class_name,g.mid_class_name,o.goods_id) as midclass_goods_rn,
    row_number() over(partition by order_id,g.max_class_name,g.mid_class_name,g.min_class_name,o.goods_id) as minclass_goods_rn

from dwb_order_detail o
    left join dwb_goods_detail g on o.goods_id = g.id
    left join dwb_shop_detail s on o.store_id = s.id)

select
    --查询出来的字段个数、顺序、类型要和待插入表的一致  dws_sale_daycount
   case when grouping(city_id) = 0   --如果分组中包含city_id 则grouping为0 那么就返回city_id
		then city_id
		else null end as city_id ,
	case when grouping(city_id) = 0
		then city_name
		else null end as city_name ,
	case when grouping(trade_area_id) = 0--商圈
		then trade_area_id
		else null end as trade_area_id ,
	case when grouping(trade_area_id) = 0
		then trade_area_name
		else null end as trade_area_name ,
	case when grouping(store_id) = 0 --店铺
		then store_id
		else null end as store_id ,
	case when grouping(store_id) = 0
		then store_name
		else null end as store_name ,
	case when grouping(brand_id) = 0 --品牌
		then brand_id
		else null end as brand_id ,
	case when grouping(brand_id) = 0
		then brand_name
		else null end as brand_name ,
	case when grouping(max_class_id) = 0 --大类
		then max_class_id
		else null end as max_class_id ,
	case when grouping(max_class_id) = 0
		then max_class_name
		else null end as max_class_name ,
	case when grouping(mid_class_id) = 0 --中类
		then mid_class_id
		else null end as mid_class_id ,
	case when grouping(mid_class_id) = 0
		then mid_class_name
		else null end as mid_class_name ,
	case when grouping(min_class_id) = 0--小类
		then min_class_id
		else null end as min_class_id ,
	case when grouping(min_class_id) = 0
		then min_class_name
		else null end as min_class_name ,

	case when grouping(store_id,store_name) = 0  --分组类型
		then 'store'
		when grouping(trade_area_id ,trade_area_name) = 0
		then 'trade_area'
		when grouping (city_id,city_name) = 0
		then 'city'
		when grouping (brand_id,brand_name) = 0
		then 'brand'
		when grouping (min_class_id,min_class_name) = 0
		then 'min_class'
		when grouping (mid_class_id,mid_class_name) = 0
		then 'mid_class'
		when grouping (max_class_id,max_class_name) = 0
		then 'max_class'
		when grouping (create_date) = 0
		then 'all'
		else 'other' end as group_type,

	--指标计算 注意每个指标都对应着8个分组维度的计算
	--1、销售收入指标 sale_amt
	case when grouping(store_id,store_name) =0  --如果分组中包含店铺,则分组为：日期+城市+商圈+店铺
		then sum(if( order_rn = 1 and store_id is not null ,order_amount,0)) --只有分组中标号为1的(去重)，店铺不为空的才参与计算
		--then sum(if( order_rn = 1 and store_id is not null ,coalesce(order_amount,0),0))  --使用coalesce函数更加成熟

		when grouping (trade_area_id ,trade_area_name) = 0 --日期+城市+商圈
		then sum(if( order_rn = 1 and trade_area_id is not null ,order_amount,0))

		when grouping (city_id,city_name) = 0 --日期+城市
		then sum(if( order_rn = 1 and city_id is not null,order_amount,0))

		when grouping (brand_id,brand_name) = 0 --日期+品牌
		then sum(if(brand_goods_rn = 1 and brand_id is not null,total_price,0))

		when grouping (min_class_id,min_class_name) = 0 --日期+大类+中类+小类
		then sum(if(minclass_goods_rn = 1 and min_class_id is not null ,total_price,0))

		when grouping (mid_class_id,mid_class_name) = 0 --日期+大类+中类
		then sum(if(midclass_goods_rn = 1 and mid_class_id is not null,total_price,0))

		when grouping (max_class_id,max_class_name) = 0 ----日期+大类
		then sum(if(maxclass_goods_rn = 1 and max_class_id is not null ,total_price,0))

		when grouping (create_date) = 0 --日期
		then sum(if(order_rn=1 and create_date is not null,order_amount,0))
	else null end  as sale_amt,

    --2、平台收入 plat_amt
		case when grouping(store_id,store_name) =0
			then sum(if( order_rn = 1 and store_id is not null ,plat_fee,0))
			when grouping (trade_area_id ,trade_area_name) = 0
			then sum(if( order_rn = 1 and trade_area_id is not null ,plat_fee,0))
			when grouping (city_id,city_name) = 0
			then sum(if( order_rn = 1 and city_id is not null,plat_fee,0))
			when grouping (brand_id,brand_name) = 0
			then null
			when grouping (min_class_id,min_class_name) = 0
			then null
			when grouping (mid_class_id,mid_class_name) = 0
			then null
			when grouping (max_class_id,max_class_name) = 0
			then null
			when grouping (create_date) = 0
			then sum(if(order_rn=1 and create_date is not null,plat_fee,0))
			else null end  as plat_amt ,

	-- 3、配送成交额 deliver_sale_amt
		case when grouping(store_id,store_name) =0
			then sum(if( order_rn = 1 and store_id is not null and delievery_id is not null ,dispatcher_money,0))
			when grouping (trade_area_id ,trade_area_name) = 0
			then sum(if( order_rn = 1 and trade_area_id is not null and delievery_id is not null,dispatcher_money,0))
			when grouping (city_id,city_name) = 0
			then sum(if( order_rn = 1 and city_id is not null and delievery_id is not null,dispatcher_money,0))
			when grouping (brand_id,brand_name) = 0
			then null
			when grouping (min_class_id,min_class_name) = 0
			then null
			when grouping (mid_class_id,mid_class_name) = 0
			then null
			when grouping (max_class_id,max_class_name) = 0
			then null
			when grouping (create_date) = 0
			then sum(if(order_rn=1 and create_date is not null and delievery_id is not null ,dispatcher_money,0))
			else null end  as deliver_sale_amt ,

	-- 4、小程序成交额 mini_app_sale_amt
		case when grouping(store_id,store_name) =0
			then sum(if( order_rn = 1 and store_id is not null and order_from='miniapp' ,order_amount,0))
			when grouping (trade_area_id ,trade_area_name) = 0
			then sum(if( order_rn = 1 and trade_area_id is not null and order_from='miniapp',order_amount,0))
			when grouping (city_id,city_name) = 0
			then sum(if( order_rn = 1 and city_id is not null and order_from='miniapp',order_amount,0))
			when grouping (brand_id,brand_name) = 0
			then sum(if(brand_goods_rn = 1 and brand_id is not null and order_from='miniapp',total_price,0))
			when grouping (min_class_id,min_class_name) = 0
			then sum(if(minclass_goods_rn = 1 and min_class_id is not null and order_from='miniapp',total_price,0))
			when grouping (mid_class_id,mid_class_name) = 0
			then sum(if(midclass_goods_rn = 1 and mid_class_id is not null and order_from='miniapp',total_price,0))
			when grouping (max_class_id,max_class_name) = 0
			then sum(if(maxclass_goods_rn = 1 and max_class_id is not null and order_from='miniapp',total_price,0))
			when grouping (create_date) = 0
			then sum(if(order_rn=1 and create_date is not null and order_from='miniapp',order_amount ,0))
			else null end  as mini_app_sale_amt ,

	-- 5、安卓成交额 android_sale_amt
		case when grouping(store_id,store_name) =0
			then sum(if( order_rn = 1 and store_id is not null and order_from='android' ,order_amount,0))
			when grouping (trade_area_id ,trade_area_name) = 0
			then sum(if( order_rn = 1 and trade_area_id is not null and order_from='android',order_amount,0))
			when grouping (city_id,city_name) = 0
			then sum(if( order_rn = 1 and city_id is not null and order_from='android',order_amount,0))
			when grouping (brand_id,brand_name) = 0
			then sum(if(brand_goods_rn = 1 and brand_id is not null and order_from='android',total_price,0))
			when grouping (min_class_id,min_class_name) = 0
			then sum(if(minclass_goods_rn = 1 and min_class_id is not null and order_from='android',total_price,0))
			when grouping (mid_class_id,mid_class_name) = 0
			then sum(if(midclass_goods_rn = 1 and mid_class_id is not null and order_from='android',total_price,0))
			when grouping (max_class_id,max_class_name) = 0
			then sum(if(maxclass_goods_rn = 1 and max_class_id is not null and order_from='android',total_price,0))
			when grouping (create_date) = 0
			then sum(if(order_rn=1 and create_date is not null and order_from='android',order_amount ,0))
			else null end  as android_sale_amt ,

	-- 6、苹果成交额 ios_sale_amt
		case when grouping(store_id,store_name) =0
			then sum(if( order_rn = 1 and store_id is not null and order_from='ios' ,order_amount,0))
			when grouping (trade_area_id ,trade_area_name) = 0
			then sum(if( order_rn = 1 and trade_area_id is not null and order_from='ios',order_amount,0))
			when grouping (city_id,city_name) = 0
			then sum(if( order_rn = 1 and city_id is not null and order_from='ios',order_amount,0))
			when grouping (brand_id,brand_name) = 0
			then sum(if(brand_goods_rn = 1 and brand_id is not null and order_from='ios',total_price,0))
			when grouping (min_class_id,min_class_name) = 0
			then sum(if(minclass_goods_rn = 1 and min_class_id is not null and order_from='ios',total_price,0))
			when grouping (mid_class_id,mid_class_name) = 0
			then sum(if(midclass_goods_rn = 1 and mid_class_id is not null and order_from='ios',total_price,0))
			when grouping (max_class_id,max_class_name) = 0
			then sum(if(maxclass_goods_rn = 1 and max_class_id is not null and order_from='ios',total_price,0))
			when grouping (create_date) = 0
			then sum(if(order_rn=1 and create_date is not null and order_from='ios',order_amount ,0))
			else null end  as ios_sale_amt ,

	-- 7、pc成交额 pcweb_sale_amt
		case when grouping(store_id,store_name) =0
			then sum(if( order_rn = 1 and store_id is not null and order_from='pcweb' ,order_amount,0))
			when grouping (trade_area_id ,trade_area_name) = 0
			then sum(if( order_rn = 1 and trade_area_id is not null and order_from='pcweb',order_amount,0))
			when grouping (city_id,city_name) = 0
			then sum(if( order_rn = 1 and city_id is not null and order_from='pcweb',order_amount,0))
			when grouping (brand_id,brand_name) = 0
			then sum(if(brand_goods_rn = 1 and brand_id is not null and order_from='pcweb',total_price,0))
			when grouping (min_class_id,min_class_name) = 0
			then sum(if(minclass_goods_rn = 1 and min_class_id is not null and order_from='pcweb',total_price,0))
			when grouping (mid_class_id,mid_class_name) = 0
			then sum(if(midclass_goods_rn = 1 and mid_class_id is not null and order_from='pcweb',total_price,0))
			when grouping (max_class_id,max_class_name) = 0
			then sum(if(maxclass_goods_rn = 1 and max_class_id is not null and order_from='pcweb',total_price,0))
			when grouping (create_date) = 0
			then sum(if(order_rn=1 and create_date is not null and order_from='pcweb',order_amount ,0))
			else null end  as pcweb_sale_amt ,

    -- 8、订单量 order_cnt
		case when grouping(store_id,store_name) =0
			then count(if(order_rn=1 and store_id is not null , order_id,null))
			when grouping (trade_area_id ,trade_area_name) = 0
			then count(if(order_rn=1 and trade_area_id is not null , order_id,null))
			when grouping (city_id,city_name) = 0
			then count(if(order_rn=1 and city_id is not null , order_id,null))
			when grouping (brand_id,brand_name) = 0
			then count(if(brand_rn=1 and brand_id is not null , order_id,null))
			when grouping (min_class_id,min_class_name) = 0
			then count(if(minclass_rn=1 and min_class_id is not null , order_id,null))
			when grouping (mid_class_id,mid_class_name) = 0
			then count(if(midclass_rn=1 and mid_class_id is not null , order_id,null))
			when grouping (max_class_id,max_class_name) = 0
			then count(if(maxclass_rn=1 and max_class_id is not null , order_id,null))
			when grouping (create_date) = 0
			then count(if(order_rn=1 , order_id,null))
			else null end  as order_cnt ,

	--9、 参评单量 eva_order_cnt
		case when grouping(store_id,store_name) =0
			then count(if(order_rn=1 and store_id is not null and evaluation_id is not null , order_id,null))
			when grouping (trade_area_id ,trade_area_name) = 0
			then count(if(order_rn=1 and trade_area_id is not null and evaluation_id is not null , order_id,null))
			when grouping (city_id,city_name) = 0
			then count(if(order_rn=1 and city_id is not null and evaluation_id is not null , order_id,null))
			when grouping (brand_id,brand_name) = 0
			then count(if(brand_rn=1 and brand_id is not null and evaluation_id is not null , order_id,null))
			when grouping (min_class_id,min_class_name) = 0
			then count(if(minclass_rn=1 and min_class_id is not null and evaluation_id is not null , order_id,null))
			when grouping (mid_class_id,mid_class_name) = 0
			then count(if(midclass_rn=1 and mid_class_id is not null  and evaluation_id is not null, order_id,null))
			when grouping (max_class_id,max_class_name) = 0
			then count(if(maxclass_rn=1 and max_class_id is not null  and evaluation_id is not null, order_id,null))
			when grouping (create_date) = 0
			then count(if(order_rn=1 and evaluation_id is not null, order_id,null))
			else null end  as eva_order_cnt ,
	--10、差评单量 bad_eva_order_cnt
		case when grouping(store_id,store_name) =0
			then count(if(order_rn=1 and store_id is not null and evaluation_id is not null and coalesce(geval_scores,0) <6 , order_id,null))
			when grouping (trade_area_id ,trade_area_name) = 0
			then count(if(order_rn=1 and trade_area_id is not null and evaluation_id is not null and coalesce(geval_scores,0) <6, order_id,null))
			when grouping (city_id,city_name) = 0
			then count(if(order_rn=1 and city_id is not null and evaluation_id is not null and coalesce(geval_scores,0) <6, order_id,null))
			when grouping (brand_id,brand_name) = 0
			then count(if(brand_rn=1 and brand_id is not null and evaluation_id is not null and coalesce(geval_scores,0) <6, order_id,null))
			when grouping (min_class_id,min_class_name) = 0
			then count(if(minclass_rn=1 and min_class_id is not null and evaluation_id is not null and coalesce(geval_scores,0) <6, order_id,null))
			when grouping (mid_class_id,mid_class_name) = 0
			then count(if(midclass_rn=1 and mid_class_id is not null  and evaluation_id is not null and coalesce(geval_scores,0) <6, order_id,null))
			when grouping (max_class_id,max_class_name) = 0
			then count(if(maxclass_rn=1 and max_class_id is not null  and evaluation_id is not null and coalesce(geval_scores,0) <6, order_id,null))
			when grouping (create_date) = 0
			then count(if(order_rn=1 and evaluation_id is not null and coalesce(geval_scores,0) <6, order_id,null))
			else null end  as bad_eva_order_cnt ,

	--11、配送单量 deliver_order_cnt
		case when grouping(store_id,store_name) =0
			then count(if(order_rn=1 and store_id is not null and delievery_id is not null, order_id,null))
			when grouping (trade_area_id ,trade_area_name) = 0
			then count(if(order_rn=1 and trade_area_id is not null and delievery_id is not null, order_id,null))
			when grouping (city_id,city_name) = 0
			then count(if(order_rn=1 and city_id is not null and delievery_id is not null, order_id,null))
			when grouping (brand_id,brand_name) = 0
			then count(if(brand_rn=1 and brand_id is not null and delievery_id is not null, order_id,null))
			when grouping (min_class_id,min_class_name) = 0
			then count(if(minclass_rn=1 and min_class_id is not null and delievery_id is not null, order_id,null))
			when grouping (mid_class_id,mid_class_name) = 0
			then count(if(midclass_rn=1 and mid_class_id is not null  and delievery_id is not null, order_id,null))
			when grouping (max_class_id,max_class_name) = 0
			then count(if(maxclass_rn=1 and max_class_id is not null and delievery_id is not null, order_id,null))
			when grouping (create_date) = 0
			then count(if(order_rn=1 and delievery_id is not null, order_id,null))
			else null end  as deliver_order_cnt ,

	--12、退款单量 refund_order_cnt
		case when grouping(store_id,store_name) =0
			then count(if(order_rn=1 and store_id is not null and refund_id is not null, order_id,null))
			when grouping (trade_area_id ,trade_area_name) = 0
			then count(if(order_rn=1 and trade_area_id is not null and refund_id is not null, order_id,null))
			when grouping (city_id,city_name) = 0
			then count(if(order_rn=1 and city_id is not null and refund_id is not null, order_id,null))
			when grouping (brand_id,brand_name) = 0
			then count(if(brand_rn=1 and brand_id is not null and refund_id is not null, order_id,null))
			when grouping (min_class_id,min_class_name) = 0
			then count(if(minclass_rn=1 and min_class_id is not null and refund_id is not null, order_id,null))
			when grouping (mid_class_id,mid_class_name) = 0
			then count(if(midclass_rn=1 and mid_class_id is not null  and refund_id is not null, order_id,null))
			when grouping (max_class_id,max_class_name) = 0
			then count(if(maxclass_rn=1 and max_class_id is not null and refund_id is not null, order_id,null))
			when grouping (create_date) = 0
			then count(if(order_rn=1 and refund_id is not null, order_id,null))
			else null end  as refund_order_cnt ,

	-- 13、小程序订单量 miniapp_order_cnt
		case when grouping(store_id,store_name) =0
			then count(if(order_rn=1 and store_id is not null and order_from = 'miniapp', order_id,null))
			when grouping (trade_area_id ,trade_area_name) = 0
			then count(if(order_rn=1 and trade_area_id is not null and order_from = 'miniapp', order_id,null))
			when grouping (city_id,city_name) = 0
			then count(if(order_rn=1 and city_id is not null and order_from = 'miniapp', order_id,null))
			when grouping (brand_id,brand_name) = 0
			then count(if(brand_rn=1 and brand_id is not null and order_from = 'miniapp', order_id,null))
			when grouping (min_class_id,min_class_name) = 0
			then count(if(minclass_rn=1 and min_class_id is not null and order_from = 'miniapp', order_id,null))
			when grouping (mid_class_id,mid_class_name) = 0
			then count(if(midclass_rn=1 and mid_class_id is not null  and order_from = 'miniapp', order_id,null))
			when grouping (max_class_id,max_class_name) = 0
			then count(if(maxclass_rn=1 and max_class_id is not null and order_from = 'miniapp', order_id,null))
			when grouping (create_date) = 0
			then count(if(order_rn=1 and order_from = 'miniapp', order_id,null))
			else null end  as miniapp_order_cnt ,

	-- 14、android订单量 android_order_cnt
		case when grouping(store_id,store_name) =0
			then count(if(order_rn=1 and store_id is not null and order_from = 'android', order_id,null))
			when grouping (trade_area_id ,trade_area_name) = 0
			then count(if(order_rn=1 and trade_area_id is not null and order_from = 'android', order_id,null))
			when grouping (city_id,city_name) = 0
			then count(if(order_rn=1 and city_id is not null and order_from = 'android', order_id,null))
			when grouping (brand_id,brand_name) = 0
			then count(if(brand_rn=1 and brand_id is not null and order_from = 'android', order_id,null))
			when grouping (min_class_id,min_class_name) = 0
			then count(if(minclass_rn=1 and min_class_id is not null and order_from = 'android', order_id,null))
			when grouping (mid_class_id,mid_class_name) = 0
			then count(if(midclass_rn=1 and mid_class_id is not null  and order_from = 'android', order_id,null))
			when grouping (max_class_id,max_class_name) = 0
			then count(if(maxclass_rn=1 and max_class_id is not null and order_from = 'android', order_id,null))
			when grouping (create_date) = 0
			then count(if(order_rn=1 and order_from = 'android', order_id,null))
			else null end  as android_order_cnt ,

	-- 15、ios订单量 ios_order_cnt
		case when grouping(store_id,store_name) =0
			then count(if(order_rn=1 and store_id is not null and order_from = 'ios', order_id,null))
			when grouping (trade_area_id ,trade_area_name) = 0
			then count(if(order_rn=1 and trade_area_id is not null and order_from = 'ios', order_id,null))
			when grouping (city_id,city_name) = 0
			then count(if(order_rn=1 and city_id is not null and order_from = 'ios', order_id,null))
			when grouping (brand_id,brand_name) = 0
			then count(if(brand_rn=1 and brand_id is not null and order_from = 'ios', order_id,null))
			when grouping (min_class_id,min_class_name) = 0
			then count(if(minclass_rn=1 and min_class_id is not null and order_from = 'ios', order_id,null))
			when grouping (mid_class_id,mid_class_name) = 0
			then count(if(midclass_rn=1 and mid_class_id is not null  and order_from = 'ios', order_id,null))
			when grouping (max_class_id,max_class_name) = 0
			then count(if(maxclass_rn=1 and max_class_id is not null and order_from = 'ios', order_id,null))
			when grouping (create_date) = 0
			then count(if(order_rn=1 and order_from = 'ios', order_id,null))
			else null end  as ios_order_cnt ,

	--16、pcweb订单量 pcweb_order_cnt
		case when grouping(store_id,store_name) =0
			then count(if(order_rn=1 and store_id is not null and order_from = 'pcweb', order_id,null))
			when grouping (trade_area_id ,trade_area_name) = 0
			then count(if(order_rn=1 and trade_area_id is not null and order_from = 'pcweb', order_id,null))
			when grouping (city_id,city_name) = 0
			then count(if(order_rn=1 and city_id is not null and order_from = 'pcweb', order_id,null))
			when grouping (brand_id,brand_name) = 0
			then count(if(brand_rn=1 and brand_id is not null and order_from = 'pcweb', order_id,null))
			when grouping (min_class_id,min_class_name) = 0
			then count(if(minclass_rn=1 and min_class_id is not null and order_from = 'pcweb', order_id,null))
			when grouping (mid_class_id,mid_class_name) = 0
			then count(if(midclass_rn=1 and mid_class_id is not null  and order_from = 'pcweb', order_id,null))
			when grouping (max_class_id,max_class_name) = 0
			then count(if(maxclass_rn=1 and max_class_id is not null and order_from = 'pcweb', order_id,null))
			when grouping (create_date) = 0
			then count(if(order_rn=1 and order_from = 'pcweb', order_id,null))
			else null end  as pcweb_order_cnt ,

        create_date as dt  --日期

from temp
group by
    grouping sets(
        create_date, --日期
        (create_date,city_id,city_name),--日期+城市
        (create_date,city_id,city_name,trade_area_id,trade_area_name),--日期+城市+商圈
        (create_date,city_id,city_name,trade_area_id,trade_area_name,store_id,store_name), --日期+城市+商圈+店铺
        (create_date,brand_id,brand_name),--日期+品牌
        (create_date,max_class_id,max_class_name),--日期+大类
        (create_date,max_class_id,max_class_name,mid_class_id,mid_class_name),--日期+大类+中类
        (create_date,max_class_id,max_class_name,mid_class_id,mid_class_name,min_class_id,min_class_name)--日期+大类+中类+小类
    );