Lecture9: Data Manipulation in SQL, Advanced SQL queries

Transcription

1 IS220 / IS422 : Database Fundamentals College of Computer and Information Sciences - Information Systems Dept. Lecture9: Data Manipulation in SQL, Advanced SQL queries Ref. Chapter5 Prepared by L. Nouf Almujally & Aisha AlArfaj 1

2 The Process of Database Design Real World Domain Conceptual model (ERD) Relational Data Model Create schema (DDL) Load Data (DML) 2Lecture9

3 Tables in the Examples Customer(custNo, custname, custst, custcity, age) Product(prodNo, prodname, proddes, price) Orders(ordNo, orddate, custno, prodno, quantity) Where custname, custst, custcity, prodname, proddes are strings orddate is date Others are numbers 3Lecture9

4 Sample Data in Customer Table custno custname custst custcity age 1 C1 Olaya St Jeddah 20 2 C2 Mains St Riyadh 30 3 C3 Mains Rd Riyadh 25 4 C4 Mains Rd Dammam 5 C5 Mains Rd Riyadh 4Lecture9

5 Sample Data in Product Table prodno prodname proddes price 100 P0 Food P1 healthy food P P3 self_raising flour,80%wheat P4 network 80x 300 5Lecture9

6 Sample Data in Orders Table ordno orddate custno prodno quantity 1 01-jan jan jan jan jan mar Lecture9

7 Aggregate Functions COUNT - returns the number of selected values SUM - returns the sum of selected (numeric) values AVG - returns the average of selected (numeric) values MIN - returns the minimum of selected values MAX - returns the maximum of selected values 7Lecture9

8 Use of COUNT(column_name) The COUNT(column_name) function returns the number of values (NULL values will not be counted) of the specified column Syntax SELECT COUNT(column_name) FROM table_name; 8Lecture9

9 Use of COUNT(column_name) prod No prodnam e proddes price 100 P0 Food P1 healthy food P P3 self_raising flour,80%wh eat P4 network 80x 300 Example 1: List the number of products in the product table SELECT count(prodno) FROM product; Example 2: List the number of product descriptions in the product table SELECT count(proddes) FROM product; COUNT(PRODNO) COUNT(PRODDES) Note: count(proddes) does not count rows that have NULL value for proddes. 9Lecture9

10 Use of COUNT(*) The COUNT(*) function returns the number of records in a table (NULL values will be counted) Syntax SELECT COUNT(*) FROM table_name; 10

11 Use of COUNT (*) prod No prodnam e proddes price 100 P0 Food P1 healthy food P P3 self_raising flour,80%wh eat P4 network 80x 300 Example 1: How many products are there in the product table? SELECT count(*) FROM product; COUNT(*) Example 2: How many products are priced at 300? SELECT count(*) FROM product WHERE price =300; COUNT(*) Note: count(*) also count rows that have NULL values 11

12 Use of COUNT(DISTINCT column_name) The COUNT(DISTINCT column_name) function returns the number of distinct values of the specified column: Syntax SELECT COUNT(DISTINCT column_name) FROM table_name; 12

13 Use of COUNT(DISTINCT column_name) Example1: How many cities are the customers located in? SELECT count(distinct custcity) from customer; COUNT(DISTINCT CUSTCITY) Example 2: How many customers ordered products since 01/01/2003? SELECT count(distinct custno) FROM orders WHERE orddate >= '01-jan-2003'; COUNT(DISTINCT CUSTNO) custno custnam e custst custcity age 1 C1 Olaya St Jeddah 20 ordno orddate cust prodno quantit 2 C2 Mains StNo Riyadh y C301-jan-2003 Mains Rd1 100 Riyadh jan C4 Mains Rd Dammam 3 01-jan C5 Mains Rd Riyadh 4 01-jan jan mar

14 Use of SUM The SUM() function returns the total sum of a numeric column. Syntax SELECT SUM(column_name) FROM table_name; 14

15 Use of SUM Example ordno orddate cust No prodno 1 01-jan jan jan quantit y 4 01-jan jan mar Example 1: How many products pieces were ordered by customer 1? SELECT SUM(quantity) FROM orders WHERE custno =1; SUM(QUANTITY) Example 2: How many orders were made by customer 1 and how many products pieces did he order? SELECT count(ordno), SUM(quantity) FROM orders WHERE custno =1; COUNT(ORDNO) SUM(QUANTITY)

16 Use of Avg The AVG() function returns the average value of a numeric column. Syntax SELECT AVG(column_name) FROM table_name; 16

17 Use of Min, Max The MIN() function returns the smallest value of the selected column. The MAX() function returns the largest value of the selected column. Syntax SELECT MIN(column_name), MAX (column_name) FROM table_name; 17

18 Example Use of AVG, MIN and MAX Example: list the minimum, maximum and average price of all products. prodno proddes prodnam e price SELECT MIN(price), MAX(price), AVG(price) FROM product; MIN(PRICE) MAX(PRICE) AVG(PRICE) P0 Food P1 healthy food P P3 self_raising flour,80%wh eat P4 network 80x 300 Note: if some product's price are NULLs, then SUM and AVG do not take those products into consideration. 18

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20 Advanced queries (GROUP BY) General Syntax of SELECT command SELECT [DISTINCT] {* [columnexpression,. } FROM TableName [WHERE condition] [GROUP BY columnlist] [HAVING condition] [ORDER BY columnlist] Order of the clauses cannot be changed. Only SELECT and FROM are mandatory 20

21 The GROUP BY Statement The GROUP BY statement is used in conjunction with the aggregate functions to group the result-set by one or more columns. Syntax SELECT column_name, aggregate_function(column_name) FROM table_name WHERE condition GROUP BY column_name; 21

22 Use of GROUP BY Use GROUP BY clause to get sub-totals. SELECT and GROUP BY closely integrated: each item in SELECT list must be single-valued per group, and SELECT clause may only contain: Column names in the group by clause Aggregate functions Constants Expression involving combinations of the above If WHERE is used with GROUP BY, WHERE is applied first, then groups are formed from rows satisfying condition. 22

23 Example 1 ( use of group by ) O_Id OrderDate OrderPrice Customer Orders /11/ Nora /10/ Sara /09/ Nora /09/ Nora /08/ Yara /10/ Sara Nora Sara Yara find the total (total order) of each customer. use the GROUP BY statement to group the customers. SELECT Customer, SUM(OrderPrice) FROM Orders GROUP BY Customer; 23

24 Example 1 The result ( output ): Customer SUM(OrderPrice) Nora 2000 Sara 1700 Yara 2000 what happens if we omit the GROUP BY statement SELECT Customer,SUM(OrderPrice) FROM Orders; The result Customer SUM(OrderPrice) Nora 5700 Sara 5700 Nora 5700 Nora 5700 Yara 5700 Sara

25 Example 2 ordno orddate custno prodno quantity 1 01-jan jan jan jan jan mar List the quantity of each product ordered during Jan SELECT prodno, sum(quantity) FROM orders WHERE orddate>='01-jan-2003' AND orddate<'01-feb-2003' GROUP BY prodno; PRODNO SUM(QUANTITY)

26 Example 3 return the minimum and maximum salaries for each department in the employees table Employee No. First Name Last Name Dept Number Salary E1 Mandy Smith D E2 Daniel Hodges D E3 Shaskia Ramanthan D E4 Graham Burke D E5 Annie Nguyen D D2 D1 SELECT deptnumber, MIN(salary), MAX (salary) FROM employees GROUP BY deptnumber ORDER BY deptnumber; DEPTNUMBER MIN(SALARY) MAX(SALARY) D D

27 Example 4 Grouping Output from Queries Example 1 : no grouping SELECT count(*) FROM EMPLOYEE; Employee No. First Name Last Name Dept Number Salary E1 Mandy Smith D E2 Daniel Hodges D E3 Shaskia Ramanthan D E4 Graham Burke D E5 Annie Nguyen D COUNT(*) Without group by COUNT(*) returns the number of rows in the table 27

28 Grouping Output from Queries Example 2 : group by SELECT deptnumber, count(*) FROM EMPLOYEE GROUP BY deptnumber ORDER BY deptnumber; Employee No. First Name Last Name Dept Number Salary E1 Mandy Smith D E4 Graham Burke D E5 Annie Nguyen D E2 Daniel Hodges D E3 Shaskia Ramanthan D DEPTNUMBER COUNT(*) D1 3 D2 2 28

29 Use of HAVING HAVING clause is designed for use with GROUP BY to restrict groups that appear in final result table. Similar to WHERE, but WHERE filters individual rows whereas HAVING filters groups. Column names in HAVING clause must also appear in the GROUP BY list or be contained within an aggregate function. SYNTAX SELECT column_name, aggregate_function(column_name) FROM table_name WHERE column_name operator value GROUP BY column_name HAVING aggregate_function(column_name) operator value ; 29

30 EXAMPLE 1 O_Id OrderDate OrderPrice Customer /11/ Nora /10/ Sara /09/ Nora /09/ Nora /08/ Yara /10/ Sara find if any of the customers have a total order of less than 2000 SELECT Customer,SUM(OrderPrice) FROM Orders GROUP BY Customer HAVING SUM(OrderPrice)<2000; CUSTOMER SUM(ORDERPRICE) SARA Without Having CUSTOMER SUM(ORDERPRICE) NORA 2000 SARA 1700 YARA

31 Example 2 O_Id OrderDate OrderPrice Customer /11/ Nora /10/ Sara /09/ Nora /09/ Nora /08/ Yara /10/ Sara find if the customers Nora" or Yara" have a total order of more than 1500 SELECT Customer,SUM(OrderPrice) FROM Orders WHERE Customer= Nora' OR Customer= Yara' GROUP BY Customer HAVING SUM(OrderPrice)>1500 ; CUSTOMER SUM(ORDERPRICE) NORA 2000 YARA

32 Example = 1 ordno orddate custno prodno quantity 1 01-jan jan jan jan jan mar = 4 101=2 List the product number and the quantity ordered for each product which has a total quantity of more than 2 during Jan SELECT prodno, sum(quantity) FROM orders WHERE orddate>='01-jan-2003' AND orddate<'01-feb-2003' GROUP BY prodno HAVING sum(quantity)>2; PRODNO SUM(QUANTITY)

33 Example 4 List the department number and the total number of employee in that department for each department that has more than two employees Employee No. First Name Last Name Dept Number Salary E1 Mandy Smith D E4 Graham Burke D E5 Annie Nguyen D E2 Daniel Hodges D E3 Shaskia Ramanthan D SELECT deptnumber, count(*) FROM EMPLOYEE GROUP BY deptnumber HAVING count(*)>2 ORDER BY deptnumber; DEPTNUMBER COUNT(*) D1 3 DEPTNUMBER COUNT(*) D1 3 D2 2 33

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35 Inserting Data Using Queries You can insert the result of a query into a table For example, if you have a table Product_Expensive which has the same structure as Product, then you can use SQL> insert into Product_Expensive select * from product where price>=200; 3 rows created. PRODNO PRODNAME PRODDES PRICE P P3 self_raising flour,80%wheat P4 network 80x

36 SQL data loader* For a table containing a large data set, INSERT command is not efficient to populate the table Oracle provides a data loader utility SQLLOADER which can be used to load data The data can be loaded from any text file and inserted into the database. table must be created first 36

37 SQL data loader* input Datafiles: Contains Data Records Control file : text file tells SQL*Loader where to insert the data. output Log file : records of successful SQL*Loader execution Discard file : contains records that were not inserted into any table in the database Bad file : contains records that were rejected because the input format is invalid. Database : where the data is loaded 37

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40 References Database Systems: A Practical Approach to Design, Implementation and Management. Thomas Connolly, Carolyn Begg. 5 th Edition, Addison-Wesley,