The query language for relational databases Jef De Smedt

Transcription

1 SQL The query language for relational databases Jef De Smedt

2 Getting to know Βeta vzw, Antwerp 1993 computer training for unemployed 2000 computer training for employees Cevora vzw/cefora asbl ( Fr 15/9 + Mon 18/09 9:00 12:30 13:00 16:30

3 Getting to know you Name Job description Experience: databases, SQL Expectations

4 Overview(1) Introduction relational databases Example database De Schop (gardencenter) Introduction SQL CREATE TABLE, DROP TABLE, ALTER TABLE Selecting data from one table

5 Overview(2) Selecting data from more than one table Subqueries Change the contents of a table Views

6 Introduction relational databases Introduction Some weird words (to impress people) Properties of a table Creating a table Relations between tables Normalisation

7 Introduction relational databases Structured datacollection Structured easy to read and change using a computer program Not structured: John is a man and he is 32 years old. He lives in Brussels. The postal code of Brussels is Jeanie also lives in Brussels. She is 35 years old and she is a woman.

8 Introduction relational databases Structured form => table Name Age Sex Postal code City John 32 Male 1000 Brussels Jeanie 35 Female 1000 Brussels

9 Weird words Entity: something we want to store in a database e.g. person, product, vehicle, order,... Attribute: property of an entity, e.g. Name, age, city, postalcode,... Relation: a connection between two entities, entity John is married to entity Jeanie, entity invoice 23/ is coupled to entity customer John

10 Properties of tables Each table contains data for 1 entity: table Customer contains customer data A row in a table is called a record (= occurence) A column in a table is a a field (= attribute) Important: A table must contain unique records (why?)

11 Unique records Each table has a primary key Values of a primary key field must be unique in a table Primary key cannot be empty Two possibilities An existing attribute: national number, personel number, invoice number,... Add a new attribute with an automatic value: autonumbering

12 Properties of tables Fieldnames must be unique Each field has a strict type Number: Int: whole number, Decimal: exact number with decimal (money) Float: approximate number with decimal Character: char(x): fixed length, varchar(x): variable length Text: unstructured data

13 Properties of tables The structure of a table (number and types of fields) must not change during the normal execution of a program Field must not contain composite data Field must not contain calculated data Records have no order

14 Relations between tables A relation between two tables is defined using the primary key and a foreign key Primary key: Postal code(city) Foreign key: Postal code(person) Name Age Postal code John Jeanie Postal code City 1000 Brussels

15 Relations between tables Persontbl Citytbl Name Age Postal code Postal code City Each record in Citytbl must have a unique postal code (primary key) Persons can have the same postal code (foreign key) Using the foreign key value we can find the city

16 Normalisation Normalisation gets rid of redundancy Consequence of normalisation => table is split into other tables See databases training (Cevora)

17 Example database De Schop Garden center has a database with plants, suppliers, orders and offers An order has one or more order lines An order belongs to a supplier Offers are provided by by suppliers

18 Example database De Schop Table PlantInfo contains information about planting distances Relation between Plants and Plantinfo is not between an foreign key and a primary key Relation: height of plant must be between height1 and height2

19 Introduction SQL SQL is used to create tables and alter the structure (Data Definition Language) SQL is used to query and alter data (Data Manipulation Language) 4 th generation language: we define the result we want to get, not how the database should get that result.

20 Data Definition Language: CREATE TABLE Create a new table in a database Define structure: name of the table, fields (name, type, NULL), primary key NULL: the field can remain empty NOT NULL: the field must contain a value

21 CREATE TABLE CREATE TABLE table_name (column_name datatype [ [NULL NOT NULL] [PRIMARY KEY UNIQUE] [[FOREIGN KEY] REFERENCES ref_table (ref_column )] ] [,... n] ) Capitals: SQL keyword italics : replace with real values [] : optional : one of the possibilites (or),... n : repeat previous part 0 or more times

22 Examples CREATE TABLE CREATE TABLE post (code char(4) PRIMARY KEY, city char(30) NOT NULL) CREATE TABLE person (no int PRIMARY KEY, name char(20) NOT NULL, code char(4) REFERENCES post(code))

23 Adding data to a table We can add data using the insert statement: INSERT INTO post (code, city) VALUES ( 1000, Brussels ) INSERT INTO person (no, name,code) VALUES (1, John, 1000 )

24 ALTER TABLE ALTER TABLE tabel_name { ADD column_name type ALTER COLUMN column_name type DROP COLUMN column_name } Examples ALTER TABLE person ALTER COLUMN name char(30) ALTER TABLE person DROP COLUMN name ALTER TABLE person ADD name char(20)

25 DROP TABLE DROP TABLE table_name Example DROP TABLE person Pay attention: a table that is referenced by another table cannot be dropped

26 Query one table SELECT [DISTINCT] {* column_name [,...n]} FROM table_name[[as] table_alias] [WHERE <condition>] [ORDER BY column_name [ASC DESC], n] Examples SELECT * FROM suppliers SELECT city FROM suppliers SELECT DISTINCT city FROM suppliers

27 Calculated fields We can create new fields using calculations Examples SELECT plantname + ( + species + ) article, price * 1.21 as vat_included FROM plants

28 Query one table: order The records in a table have no order (set) Normally records are shown ordered by primary key With ORDER BY we can define a sorting order for the results Default ordering is ascending (ASC). With DESC we can order descending Example SELECT * FROM suppliers ORDER BY discount DESC, city ASC

29 Query one table: filtering With WHERE we can limit the number of records by adding conditions for the values of some fields Examples SELECT * FROM plants WHERE price > 1.5 SELECT * FROM plants WHERE bloom_start + 2 <= bloom_end SELECT * FROM plants WHERE species = water

30 Query one table: wildcards With LIKE we can use wildcards: %: arbitrary number of arbitrary characters _: one arbitrary character Examples SELECT * FROM plants WHERE plantname LIKE %bloem SELECT * FROM plants WHERE plantname LIKE _a d%j%

31 Query one table: combining conditions We can combine conditions using AND/OR Examples SELECT * FROM plants WHERE price >= 1.5 AND price <= 4 SELECT * FROM plants WHERE species = bush OR species = perennial

32 Query one table: alternatives We can also use BETWEEN: SELECT * FROM plants WHERE price BETWEEN 1.5 AND 4 And IN SELECT * FROM plants WHERE species IN ( bush, water )

33 Query one table: checking for empty values To check for a NULL value we use the IS - operator: SELECT * FROM plants WHERE colour IS NULL To check for non-empty values we can use IS NOT : SELECT * FROM plants WHERE colour IS NOT NULL Attention: Do not use = NULL

34 Aggregation functions Aggregation functions return one value: the biggest, smallest, average, sum, count Examples SELECT COUNT(*) FROM suppliers WHERE city = Lisse SELECT COUNT(colour) FROM plants SELECT MIN(discount) FROM suppliers SELECT MAX(discount) FROM suppliers SELECT SUM(tot_amount) FROM orders WHERE sup_code = 004 SELECT AVG(discount) FROM suppliers

35 GROUP BY Hovenier Struik Dezaaier Spitman Mooiweer Lisse Lisse Lisse Aalsmeer Aalsmeer } } 3 suppliers 2 suppliers SELECT Lisse, COUNT(*) FROM suppliers WHERE city= Lisse SELECT Aalsmeer, COUNT(*) FROM suppliers WHERE city= Aalsmeer Lisse Aalsmeer 3 2

36 GROUP BY GROUP BY => Per -queries or for each -queries Show the number of records per city in the table suppliers or Show for each city in the table suppliers the number of records table suppliers per city number of records Lisse, Aalsmeer : FROM suppliers : GROUP BY city : SELECT COUNT(*) : SELECT city SELECT city, COUNT(*) FROM suppliers GROUP BY city

37 GROUP BY Filtering afterwards : HAVING (HAVING comes after GROUP BY) Show the number of records for each city that start with L in the table suppliers SELECT city, COUNT(*) FROM suppliers GROUP BY city HAVING city LIKE L% => 1) executes the command SELECT city, COUNT(*) FROM suppliers GROUP BY city 2) takes the result and only shows the cities that start with L

38 GROUP BY Filtering before: WHERE (WHERE comes before GROUP BY) Show for each city the number of suppliers that give a discount of 0% SELECT city, COUNT(*) FROM suppliers WHERE discount = 0 GROUP BY city => 1) Executes the command SELECT * FROM suppliers WHERE discount=0 2) Groups the result per city and count the number of records

39 GROUP BY In which table can we find the information? => FROM What is the for each -veld? => GROUP BY Do we want to filter results before we start grouping? Yes => WHERE Do we want to see all the grouped results? No => HAVING What must be shown? SELECT Remark for SELECT: SELECT can only contain fields in aggregation functions, unless the field is also in the group by clause Do we want to show the records in a specific order? Yes=> ORDER BY

40 Overview SELECT FROM WHERE GROUP BY TIP: - Start with this list - Add the required information - Change unused keywords into comments ( -- ) HAVING ORDER BY

41 More tables UNION JOIN

42 UNION SELECT FROM WHERE GROUP BY HAVING UNION [ALL] SELECT FROM WHERE GROUP BY HAVING 1) ORDER BY not in SELECT 2) Fields in both selects must be the same (type and number) 3) Fieldnames are the names of the first SELECT 4) Result of a UNION is unique (implicit DISTINCT) unless we use UNION ALL ORDER BY

43 SELECT sup_name, *** FROM suppliers WHERE discount > 0 UNION SELECT sup_name, FROM suppliers WHERE discount = 0 Example of UNION

44 JOIN Person Post No Name John Jeanie Code SELECT no, name, person.code, city FROM person, post WHERE person.code = post.code Jan Rita Code Brussels Brussels City Brussels Antwerp Because the field Code exists in both tables we have to prefix it it with the tablename.

45 JOIN Persoon Post Nr Name Code Code City 001 John Brussels 002 Jeanie Antwerp SELECT name, person.code, city FROM person, post WHERE person.code = post.code 001 John 9090 Brussels Only the records that can be coupled will be shown. Jeanie is not shown because for her the condition person.code = post.code is never true. Remark: With an 1-N relation this cannot happen (normally)

46 JOIN Persoon, alias P1(children) Persoon, alias P2 (parents) No Name Father Mother No Name Father Mother 001 John NULL NULL 001 John NULL NULL 002 Jeanie NULL NULL 002 Jeanie NULL NULL 003 Paul Paul Ringo Ringo Show all children of John ( John (001) as a father or John (001) as a mother) SELECT no, name FROM Person WHERE father= 001 OR mother= 001 SELECT p1.no, p1.name FROM person p1, person p2 WHERE (p1.father = p2.no OR p1.mother = p2.no) AND p2.name= John

47 JOIN WHERE and JOIN SELECT o.orderno, o.sup_code, s.sup_name, o.orderdate FROM orders o, suppliers s WHERE o.sup_code = s.sup_code SELECT o.orderno, o.sup_code, s.sup_name, o.orderdate FROM orders o JOIN suppliers s ON o.sup_code = s.sup_code

48 LEFT/RIGHT [OUTER] JOIN LEFT/RIGHT join: take all records from the left/right table + add the matching records from the other table Records that do not match will have NULLs: select sup_name, b.sup_code from suppliers s left join orders b on s.sup_code = b.sup_code where b.sup_code is null => all suppliers with no orders

49 JOIN In which tables (plural) can we find the information? => FROM How are they joined? => WHERE tab1.field=tab2.field [AND ] What do we want to see? => SELECT Do we need all records? No? => AND (no new WHERE!!!) Do we want to see the records in a specific order? Yes => ORDER BY

50 Subqueries Show all plants that are more expensive than the average price of all plants Step1: what is the average price of all plants? SELECT avg(price) FROM plants Step2: use that in the query SELECT * FROM plants WHERE price > (SELECT avg(price) FROM plants)

51 Subqueries The subquery should return only one result SELECT height FROM plants WHERE height < (SELECT height FROM plants WHERE plantname = zonnebloem ) Error Why? There is more than one plant with the name zonnebloem

52 Operators IN, ANY, ALL We can use a subquery that returns more than one result using IN Remember: WHERE plantname IN ( Berk, Beuk, Linde ) SELECT * FROM suppliers WHERE sup_code NOT IN (SELECT sup_code FROM orders)

53 Operators IN,ANY, ALL ANY and ALL operators are not used that often SELECT * FROM offers WHERE off_price <= ALL (SELECT off_price FROM offers) This is the same as SELECT * FROM offers WHERE off_price = (SELECT MIN(off_price) FROM offers)

54 Synchronized subqueries Synchronized subquery: subquery refers to a value in the main query Show all data for the plants where height equals the maximum height of all plants of the same species SELECT * FROM plants p WHERE height = (SELECT max(height) FROM plants where species = p.species)

55 Synchronized subqueries A synchronized subquery can often be used when a GROUP BY fails SELECT species, MAX(height), plantname FROM plants We cannot write this GROUP BY species Using a subquery: SELECT species, height, plantname FROM plants p WHERE height = (SELECT max(height) FROM plants where species = p.species)

56 Exists Exists: true if there are records SELECT plantname, species, price FROM plants p WHERE NOT EXISTS (SELECT * FROM plants WHERE species = 'perennial AND price >= p.price) But this can also be written as SELECT plantname, species, price FROM plants WHERE price > (SELECT max(price) FROM plants WHERE species='perennial')

57 Manipulation of data: new records Adding data INSERT INTO table_name [ (columname1 [, n])] VALUES (value1[, n]) [,(value1[, n])][, n] Example INSERT INTO plants (art_code, plantname, species, height, price) VALUES (125, fir, tree, 3000, 12)

58 Manipulation of data: new records Copy into an existing table: CREATE TABLE trees (art_code char(3), plantname varchar(16)) INSERT INTO trees (art_code, plantname) SELECT art_code, plantname FROM plants WHERE species = tree

59 Manipulation of data: updating UPDATE table_name SET columname=value[, n] [WHERE <condition>] UPDATE plants SET price = price * 1.05 WHERE species = perennial

60 Manipulation of data: deleting DELETE FROM table_name WHERE <condition> DELETE FROM plants WHERE species = perennial

61 Working with views View: store an SQL-statement in a database CREATE VIEW view_name AS <select-command> [WITH CHECK OPTION] CREATE VIEW vw_perennials AS SELECT * FROM plants WHERE species = perennial

62 Changing data with views Views can be used like tables => we can also use them in Insert, Update and Delete statements This only works for views with no DISTINCT no GROUP BY only one table no calculated columns no optional fields