1. Introduction to SQL Ahmet Oezcimen

2. Agenda 1. What is SQL? 2. SQL data types 3. Statement categories in SQL 4. Data modelling example 5. CREATE & DROP command structures 6. SELECT, INSERT, UPDATE & DELETE command structures 7. Operators 8. Functions 9. Basic SQL statements 10. Advanced SQL statements 11. Tips and techniques for better SQL 12. Tools using SQL 13. SQL*Plus 14. Literature 15. Questions

3. 1. What is SQL? SQL stands for Structured Query Language SQL is an ANSI (American National Standards Institute) standard language SQL works with Oracle, Sybase, Informix, MS SQL Server, DB2, MySQL, etc.. SQL is easy to learn

4. 2. SQL data types VARCHAR2 – contains text string up to 4,000b NUMBER - contains numeric data DATE – contains date data BLOB – Large binary object up to 4G CLOB – Large character-based object uo to 4G BFILE – Large external file Etc …

5. 3. Statement categories in SQL DDL ( Data Definition Language ) –CREATE, ALTER, DROP, etc… DML ( Data Manipulation Language ) –SELECT, UPDATE, DELETE, INSERT Transaction Control Commands –COMMIT, ROLLBACK, SAVEPOINT, etc… Session Control Commands –ALTER SESSION DCL (Data Control Language) –GRANT, REVOKE, etc… Etc…

6. 4. Data modelling example Department (deptno) Job (jobno) Interview (intno) Candidate (cno) Explanation: A deparment might have more than one job therefore also might invite more than one candidate and for one job might more than one interview and one candidate might be invited several times.

7. 4. Data modelling example (cont.) Deparment : deptno number(5), deptname varchar2(25), depthead varchar2(35) Job : jobno number(5), jobtitle varchar2(25),salary number(5), deptno number(5) Candidate: cno number(5), cname varchar2(25), deptno number(5), ctel varchar2(20), position varchar(25) Interview: intno number(5), intdate date, jobno number(5), cno number(5)

8. 5. CREATE & DROP command structures CREATE TABLE (,.., ) TABLESPACE ; DROP TABLE ;

9. 6. SELECT, INSERT, UPDATE & DELETE command structures SELECT [distinct],.., FROM [alias],.., [alias] WHERE GROUP BY,.., HAVING CONNECT BY PRIOR START WITH ORDER BY,.., [ASC or DESC]; DELETE FROM WHERE ; INSERT INTO [( )] VALUES (value list); UPDATE SET = [WHERE ];

10. 7. Operators Arithmetical operators –/, *, +, -, =, !=, <>, >, =, <= Boolean operators –NOT, NOR, AND, OR Logical operators –IN, EXISTS, LIKE

11. 8. Functions Text functions –Lpad(x,y [,z]), rpad(x,y [,z]), lower(x), upper(x), initcap(x), length(x), substr(x,y[,z]),instr(x,y), trim(), replace(x,y [,z]) Math functions –Abs(x), ceil(x), floor(x), mod(x,y), round(x,y), sign(x), sqrt(x), trunc(x,y), vsize(x), Nvl(), decode(), greatest(x,y,…), least(x,y,…) Date functions –Sysdate, add_months(x,y), last_day(x), months_between(x,y), new_time(x,y,z), next_day(x) Conversion functions –To_char(x), to_number(x), to_date(x), etc… Group functions –avg(x), count(x), max(x), min(x), sum(x), etc…

12. 9. Basic SQL statement The most easiest SQL is just to select a table –Select * from department; –select deptname, depthead from department; Conditional Selection –Select * from department where depthead=‘Alvis Brazma’; Relational operators –Select * from job where salary > 2000; More complex conditions –Select * from job where deptno=1 or deptno=2; –Select * from job where deptno=3 and salary > 2000; Using IN & BETWEEN –Select * from job where deptno in (1,2); –Select * from job where deptno between 1 and 3; Using LIKE –Select * from department where depthead like ‘Alvis%’;

13. 10. Advanced SQL statements Joins & outer joins –Select * from department, job where department.deptno=job.deptno; –select * from department a, job b where a.deptno=b.deptno(+); Group by –Select max(salary) from job; –Select jobtitle,max(salary) from job group by jobtitle; Subqueries –select * from job where deptno in (select deptno from department); Exists & all –select * from job where exists (select * from department); –select * from job where salary >= all (select salary from job); Union –select deptno,deptname from department union select jobno,jobtitle from job; Intersect & minus –select deptno from job minus select deptno from job where jobbtitle=‘DBA’; –select jobtitle from job where deptno=1 intersect select jobtitle from job where deptno=2;

14. 11. Tips and techniques for better SQL Index will not be used when a function is performed on an indexed field. SELECT * FROM department WHERE SUBSTR(DEPTNAME, 1, 3) = ‘Arr’

15. 11. Tips and techniques for better SQL (cont.) If you cannot avoid using a function: –Use the INDEX hint. SELECT /*+ INDEX(DEPARTMENT DEPT_IDX_1) */ * FROM DEPARTMENT WHERE SUBSTR(DEPTNAME, 1, 3) = ‘Arr’

16. Replace SELECT * FROM job WHERE SALARY +1000 = :NEWSALARY with SELECT * FROM job WHERE SALARY = :NEWSALARY -1000 11. Tips and techniques for better SQL (cont.)

17. Indexes are not used, and a full table scan is done when the WHERE clause contains: != (NOT EQUALS) LIKE '%SA%'

18. 11. Tips and techniques for better SQL (cont.) Depending on the range of the numbers in a BETWEEN, the optimizer will choose to do a full table scan or use the index. SELECT * FROM job WHERE salary BETWEEN 2500 AND 3500

19. 11. Tips and techniques for better SQL (cont.) When retrieving a large portion of the table’s data, full table scans are likely to offer the best performance. When retrieving small number of rows, avoid full table scans.

20. 11. Tips and techniques for better SQL (cont.) Sometimes DO disable the index. SELECT * FROM job WHERE SALARY + 0 = '10000' SELECT * FROM department WHERE deptname || '' = ‘A'

21. 11. Tips and techniques for better SQL (cont.) Select the smallest table or smallest result set first. SELECT a.deptname FROM department a, job b WHERE a.deptno=b.deptno (assume a.deptno and b.deptno are indexed)

22. 11. Tips and techniques for better SQL (cont.) Small table should drive the large table. If job is a large table and department is a small one. Disable index on department. This changes the table driving path. Replace SELECT * FROM job large, department small WHERE large.deptno = small.deptno With SELECT * FROM job large, department small WHERE large.deptno = small.deptno || ''

23. 11. Tips and techniques for better SQL (cont.) A table join is normally better than sub-query Replace: SELECT * FROM job a WHERE a.deptno IN (SELECT b.deptno FROM department b) With: SELECT A.* FROM job A, department B WHERE A.job = B.department

24. These statements have the same result. Assume table job, department relationship is one to many. SELECT * FROM job WHERE deptno IN (SELECT deptno FROM department) SELECT * FROM job WHERE EXISTS (SELECT deptno FROM department WHERE job.deptno = department.deptno) 11. Tips and techniques for better SQL (cont.)

25. Use IN operator IN checks all rows. Only use IN if the table in the subquery is extremely small. SELECT * FROM job WHERE deptno IN (SELECT deptno FROM department)

26. 11. Tips and techniques for better SQL (cont.) Use EXISTS operator EXISTS makes use of the index on the deptno column in the department table. For large tables, it may be faster. SELECT * FROM job WHERE EXISTS (SELECT deptno FROM department WHERE job.deptno = department.deptno)

27. 11. Tips and techniques for better SQL (cont.) If A.STATE and B.STATE have a unique index, Replace: SELECT a.deptno, b.deptno FROM department a, job b WHERE a.deptno = b.deptno (+) With: SELECT a.deptname, b.jobtitle FROM department a, job b WHERE a.deptno = b.deptno UNION ALL SELECT c.deptname, NULL FROM department c WHERE NOT EXISTS (SELECT 'X' FROM job d WHERE c.deptno = d.deptno)

28. 11. Tips and techniques for better SQL (cont.) Replace: SELECT * FROM department a, job b, candidate c WHERE a.deptno=b.deptno and b.deptno=c.deptno and c.deptno=1 With: SELECT * FROM A,B,C FROM department a, job b, candidate c WHERE a.deptno=b.deptno and b.deptno=c.deptno and a.deptno=1 and b.deptno=1 and c.deptno=1

29. 12. Tools using SQL Oracle SQL*Plus Oracle PL/SQL Oracle Forms Oracle Reports Oracle ProC Java-JDBC Perl-CGI etc …

30. 13. SQL*Plus Starting SQL*Plus –Sqlplus [ / ] [@ ] [@ ] Running a script –SQL>Start –SQL>@ Exiting SQL*Plus –exit Some important SQL*Plus commands –Host or !, set, spool, rem, accept, prompt, @ or start, commit, rollback, help, desc, ttitle, btitle, break, etc …

31. 14. Literature Oracle8i The complete reference Autors:Kevin Loney, George Koch Learning SQL Autors: Richard W.Earp,Sikha S.Bagui Oracle SQL and PL/SQL Handbook Autors: John Adolph Palinski

33. Glossary –Table: department DeptnoDeptnameDepthead 2MSDKim Henrick 3Swiss-ProtRolf Apweiler 4TrEMBLRolf Apweiler 1ArrayExpressAlvis Brazma 5PersonnelKeith Wiliamson

34. Glossary - Table: job JobnoJobtitleSalaryDeptno 6Database coordinator50002 7Database curator40002 8Software Engineer30002 9WEB Developer35002 10DBA20002 11Database coordinator50003 12Database curator40003 13Software Engineer30003 14WEB Developer35003 15DBA20003 16Database coordinator50004 17Database curator40004 18Software Engineer30004 19WEB Developer35004 20DBA20004 1Database coordinator50001 2Database curator40001 3Software Engineer30001 4WEB Developer35001 5DBA20001

35. Glossary - Table: candidate CnoCnameCtelPositionDeptno 1Richard0044-1243- 123456 Database coordinator 1 2Don0044-1243- 123456 Database coordinator 1 3Donald0044-1243- 123456 Database coordinator 1 4Marie0044-1243- 123456 Database coordinator 1 5Elisa0044-1243- 123456 Database coordinator 1

36. Glossary - Table: interview IntnoIntdateJobnoCno 12002-02-02 00:00:00.011

37. Exercises 1.Very simple queries 2.Queries by using WHERE condition 3.Queries by using ORDER BY 4.Queries by using functions 5.Queries by using joins 6.Queries by using subqueries 7.Queries by using GROUP BY 8.Using queries for any other database (ARRAYS, EXPERIMENTS, PROTOCOLS)

38. Some AE examples - Show me arrays that use PCR products: Select i.identifier as array, o.value as technology From tt_identifiable i, tt_physicalarraydesign a, tt_featuregroup f, tt_ontologyentry o where i.id = a.id and a.id = f.t_arraydesign_id and f.technologytype_id = o.id and lower( o.value ) like '%pcr%'

39. Some AE examples - Show me all the bibliographic references that are books: select b.title as Title, b.authors as Author from tt_bibliographicreference b, tt_parameters_t_bibliogra l, tt_ontologyentry o where b.id = l.t_bibliographicreference_id and l.parameters_id = o.id and lower( o.value ) like '%book%'

40. Some AE examples - Produce a table of all the experiments and the arrays: select distinct ie.identifier as experiment, ia.identifier as arraydesign from tt_identifiable ie, tt_experiment e, tt_bioassays_t_experiment eb, tt_physicalbioassay pba, tt_bioassaycreation bac, tt_array a, tt_identifiable ia where ie.id = e.id and e.id = eb.t_experiment_id and eb.bioassays_id = pba.id and pba.bioassaycreation_id = bac.id and bac.array_id = a.id and ia.id = a.arraydesign_id order by ie.identifier asc

41. Some AE examples -Produce a table of all the experiments and the species they study: select distinct i.identifier as experiment, o.value as species from tt_identifiable i, tt_biomaterials_experiments eb, tt_characteris_t_biomateri bo, tt_ontologyentry o where i.id = eb.experiments_id and eb.biomaterials_id = bo.t_biomaterial_id and bo.characteristics_id = o.id and o.category like '%species%' order by i.identifier