1. Existence detection of foreign key mapping
In the two tables, find records based on the existence of the foreign key mapping.
[Example 1] Calculate the average score of a class of boys. The transcripts and student tables are as follows:
[Question-solving ideas]
When selecting data from the score table, it is judged whether there is a record that the name of the class is a class and the gender of the student is male, and if it exists, it is selected.
[SPL script]
| A | B | |
| 1 | =connect("db") | /Connect to the database |
| 2 | =A1.query("select * from Score") | /Query student table |
| 3 | =A1.query("select * from Student") | /Query student transcript |
| 4 | =A3.select(Class=="Class 1" && Gender=="Male") | /Select a class of boys |
| 5 | =A2.join@i(Class:StudentID, A4:Class:ID) | /Use function A.join@i() to connect and filter |
| 6 | =A5.groups(StudentID; avg(Score):Score) | / Group and summarize the average score of each student |
The results of A6 are as follows:
| StudentID | Score |
| 1 | 76 |
| 3 | 74 |
| … | … |
When the amount of data in the foreign key table is large, you can use the orderly merge of the cursor to solve it.
[Example 2] Query the number of orders that did not use discounts in 2014. The order table and order detail table are as follows:
[Question-solving ideas]
When selecting data from the order table, judge whether there is an order with a discount of 0, and select it if it exists.
[SPL script]
| A | B | |
| 1 | =connect("db") | /Connect to the database |
| 2 | =A1.cursor("select * from Order where year(Date)=2014 order by ID") | /Create the order table cursor, select the 2014 record |
| 3 | =A1.cursor("select * from Detail order by ID") | /Create an order list cursor |
| 4 | =A3.select(Discount==0) | /Select records where discounts are not used |
| 5 | =joinx(A2:Order,ID;A4:Detail,ID) | /Use the function joinx to orderly merge the cursors of the order table and the order detail table |
| 6 | =A5.groups(month(Order.Date):Month; icount(Order.ID):OrderCount) | /Group and summarize the number of orders per month |
The results of A6 are as follows:
| Month | OrderCount |
| 1 | 16 |
| 2 | 25 |
| … | … |
2. Existence detection of non-equivalent connection
In a table, look up data by detecting the existence of non-equivalent connections.
[Example 3] Query the sales of orders with the same order spanning more than one year. Part of the order form data is as follows:
| ID | NUMBER | AMOUNT | DELIVERDATE | ARRIVALDATE |
| 10814 | 1 | 408.0 | 2014/01/05 | 2014/04/18 |
| 10814 | 2 | 204.0 | 2014/02/21 | 2014/04/05 |
| 10814 | 3 | 102.0 | 2014/03/14 | 2014/04/06 |
| 10814 | 4 | 102.0 | 2014/04/09 | 2014/04/27 |
| 10814 | 5 | 102.0 | 2014/05/04 | 2014/07/04 |
| 10848 | 1 | 873.0 | 2014/01/06 | 2014/04/21 |
| … | … | … | … | … |
[Question-solving ideas]
When selecting data from the order table, it is judged whether there are records with an order span of more than one year, and if so, it is selected.
[SPL script]
| A | B | |
| 1 | =connect("db") | /Connect to the database |
| 2 | =A1.query("select * from Detail") | /Query order details |
| 3 | =A2.group(ID) | /Group by order date |
| 4 | =A3.select(interval(~.min(DELIVERDATE), ~.max(ARRIVALDATE)) > 365) | /Select the records where the time interval of the same order exceeds 365 days |
| 5 | =A4.new(ID, ~.sum(AMOUNT):Amount) | /Create a data table to count the sales of each order |
The results of A 5 are as follows:
| ID | Amount |
| 10998 | 6800.0 |
| 11013 | 4560.0 |
| 11032 | 20615.0 |
| … | … |
3. Non-existence detection of foreign key mapping
In the two tables, find records based on the non-existence of foreign key mapping.
【例 4】查询所有科目均高于 80 分的学生。成绩表和学生表如下：
【解题思路】
从学生表选出数据时，判断学生是否存在任意科目低于 80 分的成绩，如果不存在则选出。
【SPL 脚本】
| A | B | |
| 1 | =connect("db") | /连接数据库 |
| 2 | =A1.query("select * from Student") | /查询学生表 |
| 3 | =A1.query("select * from Score") | /查询成绩表 |
| 4 | =A3.select(Score<=80) | /选出成绩不高于 80 分的记录 |
| 5 | =A4.id(StudentID) | /按学生 ID 去重 |
| 6 | =A2.join@d(ID, A5) | /使用函数 A.join@d() 选出不匹配的记录 |
A6的执行结果如下：
| ID | Class | Name |
| 2 | Class 1 | Ashley |
| 16 | Class 2 | Alexis |
4. 双重否定的存在性检测
通过双重否定，查询能够匹配的记录。
【例 5】 查询选修了所有课程的学生。选课表、课程表和学生表如下：
【解题思路】
从学生表选出数据时，判断学生是否存在某一科目课程没有选出的记录，如果不存在则选出。处理双重否定的存在性检测时，我们也可以正向思考，只要选出选修科目数量与所有科目数量相同的记录即可。
【SPL 脚本】
| A | B | |
| 1 | =connect("db") | /连接数据库 |
| 2 | =A1.query("select * from Student") | /查询学生表 |
| 3 | =A1.query("select * from Course") | /查询课程表 |
| 4 | =A1.query("select * from SelectCourse") | /查询选课表 |
| 5 | =A4.groups(StudentID; icount(CourseID):CourseCount) | /选课表按照学生 ID 分组汇总每个学生的选课数量 |
| 6 | =A5.select(CourseCount==A3.len()) | /选出选择了所有课程的学生 ID |
| 7 | =A2.join@i(ID, A6:StudentID) | /使用函数 A.join@i() 连接过滤 |
A7的执行结果如下：
| ID | Name | Class |
| 4 | Emily Smith | Class 1 |
5. 任意条件的存在性检测
在两个表中，根据任意条件的存在性检测查找记录。
【例 6】 查询两科分数差超过 30 分的学生。成绩表和学生表如下：
【SQL 语句】
从学生表选出数据时，判断是否存在有任意两个科目成绩相差 30 分的记录，存在则选出。
【SPL 脚本】
| A | B | |
| 1 | =connect("db") | /连接数据库 |
| 2 | =A1.query("select * from Student") | /查询学生表 |
| 3 | =A1.query("select * from Score") | /查询成绩表 |
| 4 | =A3.group(StudentID) | /成绩表按学生 ID 分组 |
| 5 | =A4.select(~.max(Score)-~.min(Score)>30) | /选出最高分和最低分相差超过 30 分的学生 |
| 6 | =A5.id(StudentID) | /按学生 ID 去重 |
| 7 | =A2.join@i(ID,A6) | /使用函数 A.join@i() 连接过滤 |
A7的执行结果如下：
| ID | Name | Class |
| 4 | Emily Smith | Class 1 |
| 8 | Megan | Class 1 |
| … | … | … |
6. 全部条件的存在性检测
根据一个表中数据，筛选出满足所有条件的记录。
【例 7】查询哪些员工的工资比所有销售部员工都要高。员工表部分数据如下：
| ID | NAME | DEPT | SALARY |
| 1 | Rebecca | R&D | 7000 |
| 2 | Ashley | Finance | 11000 |
| 3 | Rachel | Sales | 9000 |
| 4 | Emily | HR | 7000 |
| 5 | Ashley | R&D | 16000 |
| … | … | … | … |
【SQL 语句】
从员工表选出数据时，判断员工工资大于所有销售部员工工资的记录是否存在，存在则选出。
【SPL 脚本】
| A | B | |
| 1 | =connect("db") | /连接数据库 |
| 2 | =A1.query("select * from Employee") | /查询员工表 |
| 3 | =A2.select(DEPT:"Sales").max(SALARY) | /选出所在城市包含在一线城市中的记录 |
| 4 | =A2.select(SALARY>A3) | /分组汇总各部门的平均工资 |
The results of A4 are as follows:
| ID | NAME | DEPT | SALARY |
| 5 | Ashley | R&D | 16000 |
| 20 | Alexis | Administration | 16000 |
| 22 | Jacob | R&D | 18000 |
| 47 | Elizabeth | Marketing | 17000 |
There are more examples of related calculations in "SPL CookBook".