MySQL-练习-数据汇总-CASE WHEN

一. 数据介绍

二. 数据汇总

三. 使用CASE WHEN 和 GROUP BY将数据分组

1. 使用CASE WHEN自定义分组

• 需求：我们要在报表中显示每种产品的库存量，但我们不想简单地将“ units_in_stock”列放在报表中。报表中只需要一个总体级别，例如低，高：

  SELECT
    product_id,
    product_name,
    units_in_stock,
    CASE
      WHEN units_in_stock > 100 THEN 'high'
      WHEN units_in_stock > 50 THEN 'moderate'
      WHEN units_in_stock > 0 THEN 'low'
      WHEN units_in_stock = 0 THEN 'none'
    END AS availability
  FROM products;
  

• 上面的SQL查询结果中，我们创建了一个新列availability， 通过 CASE WHEN 语句来对这一列赋值

• CASE WHEN 语法

• 上面的查询中，通过 units_in_stock 列的值来判断库存的可用性

  • 库存大于100 的可用性为高(high)
  • 50到100的可用性为中等(moderate)
  • 小于50的为低(low)
  • 零库存 为 (none)

练习15

运行上面的SQL，比较units_in_stock 和 availability两列的结果

product_id	product_name	units_in_stock	availability
1	Chai	39	low
2	Chang	17	low
3	Aniseed Syrup	13	low
4	Chef Anton’s Cajun Seasoning	53	moderate
5	Chef Anton’s Gumbo Mix	0	none
6	Grandma’s Boysenberry Spread	120	high
7	Uncle Bob’s Organic Dried Pears	15	low
8	Northwoods Cranberry Sauce	6	low
9	Mishi Kobe Niku	29	low
10	Ikura	31	low
11	Queso Cabrales	22	low
12	Queso Manchego La Pastora	86	moderate
13	Konbu	24	low
14	Tofu	35	low
15	Genen Shouyu	39	low
16	Pavlova	29	low
17	Alice Mutton	0	none
18	Carnarvon Tigers	42	low
19	Teatime Chocolate Biscuits	25	low
20	Sir Rodney’s Marmalade	40	low

练习16

• 需求： 创建一个报表，统计员工的经验水平
• 显示字段：first_name, last_name, hire_date, 和 experience
• 经验字段（experience ）：
  • 'junior' 2014年1月1日以后雇用的员工
  • 'middle' 在2013年1月1日之后至2014年1月1日之前雇用的员工
  • 'senior' 2013年1月1日或之前雇用的员工

SELECT
  first_name,
  last_name,
  hire_date,
  CASE
    WHEN hire_date > '2014-01-01' THEN 'junior'
    WHEN hire_date > '2013-01-01' and hire_date < '2014-01-01' THEN 'middle'
    WHEN hire_date <= '2013-01-01' THEN 'senior'
  END AS experience
FROM employees;

first_name	last_name	hire_date	experience
Nancy	Davolio	2012-05-01	senior
Andrew	Fuller	2012-08-14	senior
John	Smith	2012-04-01	senior
Margaret	Peacock	2013-05-03	middle
Steven	Buchanan	2013-10-17	middle
Michael	Suyama	2013-10-17	middle
Robert	King	2014-01-02	junior
Laura	Callahan	2014-03-05	junior
Anne	Dodsworth	2014-11-15	junior
John	Smith	2017-03-21	junior

2. CASE WHEN中ELSE的使用

• 我们的商店要针对北美地区的用户做促销活动：任何运送到北美地区（美国，加拿大) 的包裹免运费。

• 创建报表，查询订单编号为10720~10730 活动后的运费价格

  SELECT 
    order_id,
    customer_id,
    ship_country,
    CASE
      WHEN ship_country = 'USA' OR ship_country = 'Canada' THEN 0.0
    END AS shipping_cost
  FROM orders
  WHERE order_id BETWEEN 10720 AND 10730;
  

• 上面的SQL中，只定义了美国和加拿大的运费，并没有处理其他目的地的运费信息

练习17

• 运行上面的SQL 观察 ship_country 和 shipping_cost 列，除了美国和加拿大之外，其他行的 shipping_cost 的值为NULL

order_id	customer_id	ship_country	shipping_cost
10720	QUEDE	Brazil	null
10721	QUICK	Germany	null
10722	SAVEA	USA	0.0
10723	WHITC	USA	0.0
10724	MEREP	Canada	0.0
10725	FAMIA	Brazil	null
10726	EASTC	UK	null
10727	REGGC	Italy	null
10728	QUEEN	Brazil	null
10729	LINOD	Venezuela	null
10730	BONAP	France	null

• 在上面的案例中，除了北美地区的以外的订单，运费统计为NULL, 如果将其他地区的运费设置为10美元，那么可以用如下方式处理：

  SELECT 
    order_id,
    customer_id,
    ship_country,
    CASE
      WHEN ship_country = 'USA' OR ship_country = 'Canada' THEN 0.0
      ELSE 10.0
    END AS shipping_cost
  FROM orders
  WHERE order_id BETWEEN 10720 AND 10730;
  

• 我们在CASE WHEN结构中添加了ELSE

• 如果不满足其他条件，则执行ELSE。 因此，所有其他国家/地区的 shipping_cost都将变为“ 10.0”，而不是NULL。

练习18

• 需求：创建客户基本信息报表
• 包含字段：
  • 客户id customer_id
  • 公司名字 company_name
  • 所在国家 country
  • 使用语言language
• 使用语言language 的取值按如下规则

  • Germany, Switzerland, and Austria 语言为德语 'German'

  • UK, Canada, the USA, and Ireland 语言为英语 'English'

  • 其他所有国家 'Other'

    SELECT 
      customer_id,
      company_name,
      country,
      CASE
        WHEN country IN ('Germany', 'Switzerland', 'Austria') THEN 'German'
        WHEN country IN ('UK', 'Canada', 'USA', 'Ireland') THEN 'English'
        ELSE 'Other'
      END AS language
    FROM customers;
    

    customer_id	company_name	country	language
    ALFKI	Alfreds Futterkiste	Germany	German
    ANATR	Ana Trujillo Emparedados y helados	Mexico	Other
    ANTON	Antonio Moreno Taquería	Mexico	Other
    AROUT	Around the Horn	UK	English
    BERGS	Berglunds snabbköp	Sweden	Other
    BLAUS	Blauer See Delikatessen	Germany	German
    BLONP	Blondesddsl père et fils	France	Other
    BOLID	Bólido Comidas preparadas	Spain	Other
    BONAP	Bon app’	France	Other
    BOTTM	Bottom-Dollar Markets	Canada	English
    BSBEV	B’s Beverages	UK	English
    CACTU	Cactus Comidas para llevar	Argentina	Other
    CENTC	Centro comercial Moctezuma	Mexico	Other
    CHOPS	Chop-suey Chinese	Switzerland	German
    COMMI	Comércio Mineiro	Brazil	Other
    CONSH	Consolidated Holdings	UK	English
    DRACD	Drachenblut Delikatessen	Germany	German
    DUMON	Du monde entier	France	Other
    EASTC	Eastern Connection	UK	English
    ERNSH	Ernst Handel	Austria	German
    FAMIA	Familia Arquibaldo	Brazil	Other
    FISSA	FISSA Fabrica Inter. Salchichas S.A.	Spain	Other
    FOLIG	Folies gourmandes	France	Other
    FOLKO	Folk och fä HB	Sweden	Other
    FRANK	Frankenversand	Germany	German
    FRANR	France restauration	France	Other
    FRANS	Franchi S.p.A.	Italy	Other
    FURIB	Furia Bacalhau e Frutos do Mar	Portugal	Other
    GALED	Galería del gastrónomo	Spain	Other
    GODOS	Godos Cocina Típica	Spain	Other
    GOURL	Gourmet Lanchonetes	Brazil	Other
    GREAL	Great Lakes Food Market	USA	English
    GROSR	GROSELLA-Restaurante	Venezuela	Other
    HANAR	Hanari Carnes	Brazil	Other
    HILAA	HILARION-Abastos	Venezuela	Other
    HUNGC	Hungry Coyote Import Store	USA	English
    HUNGO	Hungry Owl All-Night Grocers	Ireland	English
    ISLAT	Island Trading	UK	English
    KOENE	Königlich Essen	Germany	German
    LACOR	La corne d’abondance	France	Other
    LAMAI	La maison d’Asie	France	Other
    LAUGB	Laughing Bacchus Wine Cellars	Canada	English
    LAZYK	Lazy K Kountry Store	USA	English
    LEHMS	Lehmanns Marktstand	Germany	German
    LETSS	Let’s Stop N Shop	USA	English
    LILAS	LILA-Supermercado	Venezuela	Other
    LINOD	LINO-Delicateses	Venezuela	Other
    LONEP	Lonesome Pine Restaurant	USA	English
    MAGAA	Magazzini Alimentari Riuniti	Italy	Other
    MAISD	Maison Dewey	Belgium	Other
    MEREP	Mère Paillarde	Canada	English
    MORGK	Morgenstern Gesundkost	Germany	German
    NORTS	North/South	UK	English
    OCEAN	Océano Atlántico Ltda.	Argentina	Other
    OLDWO	Old World Delicatessen	USA	English
    OTTIK	Ottilies Käseladen	Germany	German
    PARIS	Paris spécialités	France	Other
    PERIC	Pericles Comidas clásicas	Mexico	Other
    PICCO	Piccolo und mehr	Austria	German
    PRINI	Princesa Isabel Vinhos	Portugal	Other
    QUEDE	Que Delícia	Brazil	Other
    QUEEN	Queen Cozinha	Brazil	Other
    QUICK	QUICK-Stop	Germany	German
    RANCH	Rancho grande	Argentina	Other
    RATTC	Rattlesnake Canyon Grocery	USA	English
    REGGC	Reggiani Caseifici	Italy	Other
    RICAR	Ricardo Adocicados	Brazil	Other
    RICSU	Richter Supermarkt	Switzerland	German
    ROMEY	Romero y tomillo	Spain	Other
    SANTG	Santé Gourmet	Norway	Other
    SAVEA	Save-a-lot Markets	USA	English
    SEVES	Seven Seas Imports	UK	English
    SIMOB	Simons bistro	Denmark	Other
    SPECD	Spécialités du monde	France	Other
    SPLIR	Split Rail Beer & Ale	USA	English
    SUPRD	Suprêmes délices	Belgium	Other
    THEBI	The Big Cheese	USA	English
    THECR	The Cracker Box	USA	English
    TOMSP	Toms Spezialitäten	Germany	German
    TORTU	Tortuga Restaurante	Mexico	Other
    TRADH	Tradição Hipermercados	Brazil	Other
    TRAIH	Trail’s Head Gourmet Provisioners	USA	English
    VAFFE	Vaffeljernet	Denmark	Other
    VICTE	Victuailles en stock	France	Other
    VINET	Vins et alcools Chevalier	France	Other
    WANDK	Die Wandernde Kuh	Germany	German
    WARTH	Wartian Herkku	Finland	Other
    WELLI	Wellington Importadora	Brazil	Other
    WHITC	White Clover Markets	USA	English
    WILMK	Wilman Kala	Finland	Other
    WOLZA	Wolski Zajazd	Poland	Other

练习19

• 需求：创建报表将所有产品划分为素食和非素食两类
• 报表中包含如下字段：

  • 产品名字 product_name

  • 类别名称 category_name

  • 膳食类型 diet_type:

    • 非素食 'Non-vegetarian' 商品类别字段的值为 'Meat/Poultry' 和 'Seafood'.
    • 素食

    SELECT
      product_name,
      category_name,
      CASE
        WHEN category_name IN ('Meat/Poultry', 'Seafood') THEN 'Non-vegetarian'
        ELSE 'Vegetarian'
      END AS diet_type
    FROM categories c
    JOIN products p
      ON c.category_id = p.category_id;
    

    product_name	category_name	diet_type
    Chai	Beverages	Vegetarian
    Ikura	Seafood	Non-vegetarian
    Queso Cabrales	Dairy Products	Vegetarian
    Queso Manchego La Pastora	Dairy Products	Vegetarian
    Konbu	Seafood	Non-vegetarian
    Tofu	Produce	Vegetarian
    Genen Shouyu	Condiments	Vegetarian
    Pavlova	Confections	Vegetarian
    Alice Mutton	Meat/Poultry	Non-vegetarian
    Carnarvon Tigers	Seafood	Non-vegetarian
    Teatime Chocolate Biscuits	Confections	Vegetarian
    Chang	Beverages	Vegetarian
    Sir Rodney’s Marmalade	Confections	Vegetarian
    Sir Rodney’s Scones	Confections	Vegetarian
    Gustaf’s Knäckebröd	Grains/Cereals	Vegetarian
    Tunnbröd	Grains/Cereals	Vegetarian
    Guaraná Fantástica	Beverages	Vegetarian
    NuNuCa Nuß-Nougat-Creme	Confections	Vegetarian
    Gumbär Gummibärchen	Confections	Vegetarian
    Schoggi Schokolade	Confections	Vegetarian
    Rössle Sauerkraut	Produce	Vegetarian
    Thüringer Rostbratwurst	Meat/Poultry	Non-vegetarian
    Aniseed Syrup	Condiments	Vegetarian
    Nord-Ost Matjeshering	Seafood	Non-vegetarian
    Gorgonzola Telino	Dairy Products	Vegetarian
    Mascarpone Fabioli	Dairy Products	Vegetarian
    Geitost	Dairy Products	Vegetarian
    Sasquatch Ale	Beverages	Vegetarian
    Steeleye Stout	Beverages	Vegetarian
    Inlagd Sill	Seafood	Non-vegetarian
    Gravad lax	Seafood	Non-vegetarian
    Côte de Blaye	Beverages	Vegetarian
    Chartreuse verte	Beverages	Vegetarian
    Chef Anton’s Cajun Seasoning	Condiments	Vegetarian
    Boston Crab Meat	Seafood	Non-vegetarian
    Jack’s New England Clam Chowder	Seafood	Non-vegetarian
    Singaporean Hokkien Fried Mee	Grains/Cereals	Vegetarian
    Ipoh Coffee	Beverages	Vegetarian
    Gula Malacca	Condiments	Vegetarian
    Rogede sild	Seafood	Non-vegetarian
    Spegesild	Seafood	Non-vegetarian
    Zaanse koeken	Confections	Vegetarian
    Chocolade	Confections	Vegetarian
    Maxilaku	Confections	Vegetarian
    Chef Anton’s Gumbo Mix	Condiments	Vegetarian
    Valkoinen suklaa	Confections	Vegetarian
    Manjimup Dried Apples	Produce	Vegetarian
    Filo Mix	Grains/Cereals	Vegetarian
    Perth Pasties	Meat/Poultry	Non-vegetarian
    Tourtière	Meat/Poultry	Non-vegetarian
    Pâté chinois	Meat/Poultry	Non-vegetarian
    Gnocchi di nonna Alice	Grains/Cereals	Vegetarian
    Ravioli Angelo	Grains/Cereals	Vegetarian
    Escargots de Bourgogne	Seafood	Non-vegetarian
    Raclette Courdavault	Dairy Products	Vegetarian
    Grandma’s Boysenberry Spread	Condiments	Vegetarian
    Camembert Pierrot	Dairy Products	Vegetarian
    Sirop d’érable	Condiments	Vegetarian
    Tarte au sucre	Confections	Vegetarian
    Vegie-spread	Condiments	Vegetarian
    Wimmers gute Semmelknödel	Grains/Cereals	Vegetarian
    Louisiana Fiery Hot Pepper Sauce	Condiments	Vegetarian
    Louisiana Hot Spiced Okra	Condiments	Vegetarian
    Laughing Lumberjack Lager	Beverages	Vegetarian
    Scottish Longbreads	Confections	Vegetarian
    Gudbrandsdalsost	Dairy Products	Vegetarian
    Uncle Bob’s Organic Dried Pears	Produce	Vegetarian
    Outback Lager	Beverages	Vegetarian
    Flotemysost	Dairy Products	Vegetarian
    Mozzarella di Giovanni	Dairy Products	Vegetarian
    Röd Kaviar	Seafood	Non-vegetarian
    Longlife Tofu	Produce	Vegetarian
    Rhönbräu Klosterbier	Beverages	Vegetarian
    Lakkalikööri	Beverages	Vegetarian
    Original Frankfurter grüne Soße	Condiments	Vegetarian
    Northwoods Cranberry Sauce	Condiments	Vegetarian
    Mishi Kobe Niku	Meat/Poultry	Non-vegetarian

3. 在GROUP BY中使用CASE WHEN

• 在引入北美地区免运费的促销策略时，我们也想知道运送到北美地区和其它国家地区的订单数量

  SELECT 
    CASE
      WHEN ship_country = 'USA' OR ship_country = 'Canada' THEN 0.0
      ELSE 10.0
    END AS shipping_cost,
    COUNT(*) AS order_count
  FROM orders
  GROUP BY
    CASE
      WHEN ship_country = 'USA' OR ship_country = 'Canada' THEN 0.0
      ELSE 10.0
    END;
  

• 在SELECT子句和GROUP BY子句中，有相同的CASE WHEN出现在GROUP BY子句中

• 这里并没有使用别名shipping_cost。 虽然在SELECT子句中指定了别名（shipping_cost），但标准SQL不允许在GROUP BY子句中引用别名，所以这里CASE WHEN 写了两次

• MySQL允许 在GROUP BY中使用列别名，在本案例中两种写法都可以

  shipping_cost	order_count
  10.0	678
  0.0	152

• 注意： CASE WHEN 语句在 GROUP BY 和 SELECT 子句中，写法必须相同

练习20

• 需求：创建报表统计供应商来自哪个大洲
• 报表中包含两个字段：供应商来自哪个大洲（supplier_continent ）和 供应产品数量（product_count）
• 供应商来自哪个大洲（supplier_continent ）包含如下取值：

  • 'North America' （供应商来自 'USA' 和 'Canada'.）

  • 'Asia' （供应商来自 'Japan' 和 'Singapore')

  • 'Other' (其它国家)

    SELECT 
      CASE
        WHEN country IN ('USA', 'Canada') THEN 'North America'
        WHEN country IN ('Japan', 'Singapore') THEN 'Asia'
        ELSE 'Other'
      END AS supplier_continent,
      COUNT(*) AS product_count
    FROM products p
    JOIN suppliers s
      ON p.supplier_id = s.supplier_id
    GROUP BY
      CASE
        WHEN country IN ('USA', 'Canada') THEN 'North America'
        WHEN country IN ('Japan', 'Singapore') THEN 'Asia'
        ELSE 'Other'
      END;
    

    supplier_continent	product_count
    Other	49
    Asia	9
    North America	19

练习21

• 需求：创建一个简单的报表来统计员工的年龄情况
• 报表中包含如下字段

  • 年龄（ age ）：生日大于1980年1月1日 'young' ，其余'old'

  • 员工数量 （ employee_count）

    SELECT
      CASE
        WHEN birth_date > '1980-01-01' THEN 'young'
        ELSE 'old'
      END AS age,
      COUNT(*) AS employee_count
    FROM employees
    GROUP BY
      CASE
        WHEN birth_date > '1980-01-01' THEN 'young'
        ELSE 'old'
      END;
    

    age	employee_count
    young	5
    old	5

4. CASE WHEN 和 COUNT

• 可以将 CASE WHEN 和 COUNT 结合使用，自定义分组并统计每组数据数量

  SELECT 
    COUNT(CASE 
      WHEN ship_country = 'USA' OR ship_country = 'Canada' THEN order_id 
    END) AS free_shipping,
    COUNT(CASE
      WHEN ship_country != 'USA' AND ship_country != 'Canada' THEN order_id
    END) AS paid_shipping
  FROM orders;
  

  free_shipping	paid_shipping
  152	678

• 在上面的查询中，在COUNT（）函数中包含了一个CASE WHEN子句。

  • 对于每一行，CASE WHEN子句会检查ship_country中的值。 如果是“ USA”或“ Canada”，则将order_id传递给COUNT（）并进行计数。
  • 如果ship_country中的值不同，则CASE WHEN将返回NULL, COUNT（）不会统计NULL值。 free_shipping列将仅计算运往美国或加拿大的订单”
  • paid_shipping列的构建方式与上述方式类似

练习22

• 需求：统计客户的contact_title 字段值为 ’Owner’ 的客户数量

• 查询结果有两个字段：represented_by_owner 和 not_represented_by_owner

  SELECT 
    COUNT(CASE
      WHEN contact_title = 'Owner' THEN customer_id
    END) AS represented_by_owner,
    COUNT(CASE
      WHEN contact_title != 'Owner' THEN customer_id
    END) AS not_represented_by_owner
  FROM customers;
  

  represented_by_owner	not_represented_by_owner
  17	74

练习23

• 需求：Washington (WA) 是 Northwind的主要运营地区，统计有多少订单是由华盛顿地区的员工处理的，多少订单是有其它地区的员工处理的

• 结果字段： orders_wa_employees 和 orders_not_wa_employees

  SELECT 
    COUNT(CASE
      WHEN region = 'WA' THEN order_id
    END) AS orders_wa_employees,
    COUNT(CASE
      WHEN region != 'WA' THEN order_id
    END) AS orders_not_wa_employees
  FROM employees e
  JOIN orders o
    ON e.employee_id = o.employee_id;
  

  orders_wa_employees	orders_not_wa_employees
  605	225

5. GROUP BY 和 CASE WHEN组合使用

• 先看下面的SQL

  SELECT 
    ship_country,
    COUNT(CASE
      WHEN freight < 40.0 THEN order_id
    END) AS low_freight,
    COUNT(CASE
      WHEN freight >= 40.0 AND freight < 80.0 THEN order_id
    END) AS avg_freight,
    COUNT(CASE
      WHEN freight >= 80.0 THEN order_id
    END) AS high_freight
  FROM orders
  GROUP BY ship_country;
  

  ship_country	low_freight	avg_freight	high_freight
  France	46	14	17
  Germany	50	34	38
  Brazil	45	22	16
  Belgium	10	5	4
  Switzerland	7	3	8
  Venezuela	23	10	13
  Austria	6	7	27
  Mexico	16	9	3
  USA	53	22	47
  Swede	15	5	17
  Finland	16	3	3
  Italy	20	6	2
  Spain	16	3	4
  UK	35	11	10
  Ireland	4	5	10
  Portugal	7	3	3
  Canada	13	11	6
  Denmark	8	6	4
  Poland	6	0	1
  Norway	3	2	1
  Argentina	12	2	2

• 将COUNT(CASE WHEN...) 和 GROUP BY 组合使用，可以创建更复杂的报表，在报表中，我们将运输到不同国家的订单根据运费高低进一步分成三组，并统计每组数量

练习24

• 需求：创建报表，统计不同类别产品的库存量，将库存量分成两类 >30 和 <=30 两档,分别统计这两档的商品数量
• 报表包含三个字段

  • 类别名称 category_name,

  • 库存充足 high_availability

  • 库存紧张 low_availability

    SELECT 
      c.category_name,
      COUNT(CASE
        WHEN units_in_stock > 30 THEN product_id
      END) AS high_availability,
      COUNT(CASE
        WHEN units_in_stock <= 30 THEN product_id
      END) AS low_availability
    FROM products p
    JOIN categories c
      ON p.category_id = c.category_id
    GROUP BY c.category_id,
      c.category_name;
    

    category_name	high_availability	low_availability
    Grains/Cereals	4	3
    Dairy Products	3	7
    Meat/Poultry	1	5
    Condiments	6	6
    Produce	1	4
    Beverages	6	6
    Seafood	8	4
    Confections	5	8

6. SUM中使用CASE WHEN

• 上面通过我们通过 COUNT() 函数 和CASE WHEN子句联合使用来创建的报表，也可以通过 SUM() 来替代 COUNT()

  SELECT 
    SUM(CASE
      WHEN ship_country = 'USA' OR ship_country = 'Canada' THEN 1
    END) AS free_shipping,
    SUM(CASE
      WHEN ship_country != 'USA' AND ship_country != 'Canada' THEN 1
    END) AS paid_shipping
  FROM orders;
  

• 在上面的查询中，我们将SUM（）与CASE WHEN一起使用，结果与使用 COUNT()相同

练习25

SELECT 
  COUNT(CASE
    WHEN region = 'WA' THEN order_id
  END) AS orders_wa_employees,
  COUNT(CASE
    WHEN region != 'WA' THEN order_id
  END) AS orders_not_wa_employees
FROM employees e
JOIN orders o
  ON e.employee_id = o.employee_id;

• 将上面的SQL修改成用 SUM（） 函数实现

  SELECT 
    SUM(CASE
      WHEN region = 'WA' THEN 1
    END) AS orders_wa_employees,
    SUM(CASE
      WHEN region != 'WA' THEN 1
    END) AS orders_not_wa_employees
  FROM employees e
  JOIN orders o
    ON e.employee_id = o.employee_id;
  

  orders_wa_employees	orders_not_wa_employees
  605	225

• 需求：创建报表统计运输到法国的的订单中，打折和未打折订单的总数量

• 结果包含两个字段：full_price （原价）和 discounted_price（打折）

  SELECT
    SUM(CASE
      WHEN discount = 0 THEN 1
    END) AS full_price,
    SUM(CASE
      WHEN discount != 0 THEN 1
    END) AS discounted_price
  FROM orders o
  JOIN order_items oi
    ON o.order_id = oi.order_id
  WHERE ship_country = 'France';
  

  full_price	discounted_price
  107	77

7. SUM中使用CASE WHEN进行复杂计算

• 我们现在要统计每个订单的总付款额以及非素食产品的总付款额。

  注: 非素食产品的产品ID （ category_id） 是 6 和 8

  SELECT
    o.order_id,
    SUM(oi.quantity * oi.unit_price * (1 - oi.discount)) AS total_price,
    SUM(CASE
      WHEN p.category_id in (6, 8) THEN oi.quantity * oi.unit_price * (1 - oi.discount)
      ELSE 0
    END) AS non_vegetarian_price
  FROM orders o
  JOIN order_items oi
    ON o.order_id = oi.order_id
  JOIN products p
    ON p.product_id = oi.product_id
  GROUP BY o.order_id;
  

• 之前的场景中，我们可以通过SUM(CASE WHEN...) 来替换COUNT(CASE WHEN...) ，但在上面的例子中，我们只能使用SUM(CASE WHEN...) ，因为涉及到不同值的累加，不能通过COUNT计数替代

练习27

• 需求：输出报表，统计不同供应商供应商品的总库存量，以及高价值商品的库存量（单价超过40定义为高价值）
• 结果显示四列：

  • 供应商ID supplier_id

  • 供应商公司名 company_name

  • 由该供应商提供的总库存 all_units

  • 由该供应商提供的高价值商品库存 expensive_units

    SELECT 
      s.supplier_id,
      s.company_name,
      SUM(units_in_stock) AS all_units,
      SUM(CASE
        WHEN unit_price > 40.0 THEN units_in_stock
        ELSE 0
      END) AS expensive_units
    FROM products p
    JOIN suppliers s
      ON p.supplier_id = s.supplier_id
    GROUP BY s.supplier_id,
      s.company_name;
    

    supplier_id	company_name	all_units	expensive_units
    1	Exotic Liquids	69	0
    4	Tokyo Traders	64	29
    5	Cooperativa de Quesos ‘Las Cabras’	108	0
    6	Mayumi’s	98	0
    7	Pavlova, Ltd.	110	66
    8	Specialty Biscuits, Ltd.	74	40
    9	PB Knäckebröd AB	165	0
    10	Refrescos Americanas LTDA	20	0
    11	Heli Süßwaren GmbH & Co. KG	140	49
    12	Plutzer Lebensmittelgroßmärkte AG	205	26
    13	Nord-Ost-Fisch Handelsgesellschaft mbH	10	0
    14	Formaggi Fortini s.r.l.	23	0
    16	Bigfoot Breweries	347	0
    17	Svensk Sjöföda AB	224	0
    18	Aux joyeux ecclésiastiques	86	17
    2	New Orleans Cajun Delights	133	0
    19	New England Seafood Cannery	208	0
    20	Leka Trading	70	17
    21	Lyngbysild	100	0
    22	Zaanse Snoepfabriek	51	0
    23	Karkki Oy	132	0
    24	G’day, Mate	58	20
    25	Ma Maison	136	0
    26	Pasta Buttini s.r.l.	57	0
    27	Escargots Nouveaux	62	0
    28	Gai pâturage	98	79
    3	Grandma Kelly’s Homestead	141	0
    29	Forêts d’érables	130	17

8. 小结

1. CASE WHEN语句检查一个或多个条件，并在找到第一个匹配条件时返回一个值。 如果没有ELSE子句并且没有匹配条件，则CASE WHEN返回NULL。

   CASE
     WHEN condition_1 THEN result_1
     WHEN condition_2 THEN result_2
     ...
     ELSE result
   END
   

2. 要添加新列，从而对业务数据进行自定义分组，可以在SELECT子句中使用CASE WHEN：

   SELECT 
     CASE
       WHEN ... THEN ...
     END AS sample_column
   FROM table;
   

3. 可以在“ GROUP BY”子句中使用“ CASE WHEN”来创建自己的分组。 同样的CASE WHEN子句也必须出现在SELECT子句中：

   SELECT 
     CASE
       WHEN ... THEN ...
     END AS sample_column,
     COUNT(*) AS sample_count
   FROM table
     ...
   GROUP BY
     CASE WHEN ... THEN ...
     END;
   

4. 可以在COUNT()或SUM()函数内使用CASE WHEN来创建业务对象的自定义计数：

   SELECT 
     COUNT(CASE
       WHEN ... THEN column_name
     END) AS count_column
   FROM table;
   

   SELECT 
     SUM(CASE
       WHEN ... THEN 1
     END) AS count_column
   FROM table;
   

练习28

• 需求：创建报表来为每种商品添加价格标签，贵、中等、便宜
• 结果包含如下字段：product_id, product_name, unit_price, 和 price_level
• 价格等级price_level的取值说明：

  • 'expensive' 单价高于100的产品

  • 'average' 单价高于40但不超过100的产品

  • 'cheap' 其他产品

    SELECT 
      product_id,
      product_name,
      unit_price,
      CASE
        WHEN unit_price > 100 THEN 'expensive'
        WHEN unit_price > 40 THEN 'average'
        ELSE 'cheap'
      END AS price_level
    FROM products;
    

    product_id	product_name	unit_price	price_level
    1	Chai	18	cheap
    10	Ikura	31	cheap
    11	Queso Cabrales	21	cheap
    12	Queso Manchego La Pastora	38	cheap
    13	Konbu	6	cheap
    14	Tofu	23.25	cheap
    15	Genen Shouyu	15.5	cheap
    16	Pavlova	17.45	cheap
    17	Alice Mutton	39	cheap
    18	Carnarvon Tigers	62.5	average
    19	Teatime Chocolate Biscuits	9.2	cheap
    2	Chang	19	cheap
    20	Sir Rodney’s Marmalade	81	average
    21	Sir Rodney’s Scones	10	cheap
    22	Gustaf’s Knäckebröd	21	cheap
    23	Tunnbröd	9	cheap
    24	Guaraná Fantástica	4.5	cheap
    25	NuNuCa Nuß-Nougat-Creme	14	cheap
    26	Gumbär Gummibärchen	31.23	cheap
    27	Schoggi Schokolade	43.9	average
    28	Rössle Sauerkraut	45.6	average
    29	Thüringer Rostbratwurst	123.79	expensive
    3	Aniseed Syrup	10	cheap
    30	Nord-Ost Matjeshering	25.89	cheap
    31	Gorgonzola Telino	12.5	cheap
    32	Mascarpone Fabioli	32	cheap
    33	Geitost	2.5	cheap
    34	Sasquatch Ale	14	cheap
    35	Steeleye Stout	18	cheap
    36	Inlagd Sill	19	cheap
    37	Gravad lax	26	cheap
    38	Côte de Blaye	263.5	expensive
    39	Chartreuse verte	18	cheap
    4	Chef Anton’s Cajun Seasoning	22	cheap
    40	Boston Crab Meat	18.4	cheap
    41	Jack’s New England Clam Chowder	9.65	cheap
    42	Singaporean Hokkien Fried Mee	14	cheap
    43	Ipoh Coffee	46	average
    44	Gula Malacca	19.45	cheap
    45	Rogede sild	9.5	cheap
    46	Spegesild	12	cheap
    47	Zaanse koeken	9.5	cheap
    48	Chocolade	12.75	cheap
    49	Maxilaku	20	cheap
    5	Chef Anton’s Gumbo Mix	21.35	cheap
    50	Valkoinen suklaa	16.25	cheap
    51	Manjimup Dried Apples	53	average
    52	Filo Mix	7	cheap
    53	Perth Pasties	32.8	cheap
    54	Tourtière	7.45	cheap
    55	Pâté chinois	24	cheap
    56	Gnocchi di nonna Alice	38	cheap
    57	Ravioli Angelo	19.5	cheap
    58	Escargots de Bourgogne	13.25	cheap
    59	Raclette Courdavault	55	average
    6	Grandma’s Boysenberry Spread	25	cheap
    60	Camembert Pierrot	34	cheap
    61	Sirop d’érable	28.5	cheap
    62	Tarte au sucre	49.3	average
    63	Vegie-spread	43.9	average
    64	Wimmers gute Semmelknödel	33.25	cheap
    65	Louisiana Fiery Hot Pepper Sauce	21.05	cheap
    66	Louisiana Hot Spiced Okra	17	cheap
    67	Laughing Lumberjack Lager	14	cheap
    68	Scottish Longbreads	12.5	cheap
    69	Gudbrandsdalsost	36	cheap
    7	Uncle Bob’s Organic Dried Pears	30	cheap
    70	Outback Lager	15	cheap
    71	Flotemysost	21.5	cheap
    72	Mozzarella di Giovanni	34.8	cheap
    73	Röd Kaviar	15	cheap
    74	Longlife Tofu	10	cheap
    75	Rhönbräu Klosterbier	7.75	cheap
    76	Lakkalikööri	18	cheap
    77	Original Frankfurter grüne Soße	13	cheap
    8	Northwoods Cranberry Sauce	40	cheap
    9	Mishi Kobe Niku	97	average

练习29

• 需求：制作报表统计所有订单的总价（不计任何折扣）对它们进行分类。
• 包含以下字段：
  • order_id
  • total_price（折扣前）
  • price_group
• 字段 price_group 取值说明：

  • 'high'，总价超过2000美元

  • 'average'，总价在$ 600到$ 2,000之间，包括两端

  • 'low' 总价低于$ 600

    SELECT
      order_id,
      SUM(unit_price * quantity) AS total_price,
      CASE
        WHEN SUM(unit_price * quantity) > 2000 THEN 'high'
        WHEN SUM(unit_price * quantity) > 600 THEN 'average'
        ELSE 'low'
      END AS price_group
    FROM order_items
    GROUP BY order_id;
    

    order_id	total_price	price_group
    11038	751.00	average
    10782	12.50	low
    10725	287.80	low
    10423	1020.00	average
    10518	4150.05	high
    10356	1106.40	average
    10963	68.00	low
    10596	1476.10	average
    10282	155.40	low
    10658	4668.00	high
    10283	1414.80	average
    10579	317.75	low
    10693	2334.00	high
    10896	750.50	average
    10660	1701.00	average
    10253	1444.80	average
    10425	480.00	low
    10774	875.00	average
    10615	120.00	low
    10514	8623.45	high

练习30

• 需求：统计所有订单的运费，将运费高低分为三档
• 报表中包含三个字段

  • low_freight freight值小于“ 40.0”的订单数

  • avg_freight freight值大于或等于“ 40.0”但小于“ 80.0”的订单数

  • high_freight freight值大于或等于“ 80.0”的订单数

    SELECT
      COUNT(CASE
        WHEN freight >= 80.0 THEN order_id
      END) AS high_freight,
      COUNT(CASE
        WHEN freight < 40.0 THEN order_id
      END) AS low_freight,
      COUNT(CASE
        WHEN freight >= 40.0 AND freight < 80.0 THEN order_id
      END) AS avg_freight
    FROM orders;
    

    high_freight	low_freight	avg_freight
    236	411	183

四. 窗口函数