1. Ashish Raghute, IT Director, Fleetwood Enterprises Introduction to RDBMS and SQL

2. 7:30 am – 9 am 1. General RDBMS Concepts - Relational Vs. File Systems, normalization, ERD, extensibility 2. SQL DDL (Data definition language) Create, Alter, Drop Tables and Indexes, typical data types, space implications, referential integrity 9.15 am – 10.30 am 3. SQL DML (Data manipulation language) - selection, projection, aggregates, inner/outer/self/recursive/nested/co-related, updates, inserts, index use, statistics use, best practices and tips 4. Vendor enhancements to SQL - example SQL*PLUS and iSQL, functions (string, math, date etc.) ‏ 5. Examples of some tough SQLs for selects, inserts, updates and deletes 10.35 am – 11.30 am 6. Setting up ODBC 7. Exercises for the week

3. 1. General RDBMS Concepts - Relational Vs. File Systems, normalization, ERD, extensibility RDBMS – Relational Database Management System Chronology: Simple file based system Sophisticated file based systems like VAX/RMS with COBOL DBMS – Database Next generation of DBMS – e.g. Paradox, DBaseIII.. DBMS typically had an engine and 4GL tool set Relational DBMS is the most popular data access technology today OODBMS not so popular Typical RDBMS Features: Normalization Strong 4GL language support Optimization – Indexing, Caching, execution planning etc. Introduction to RDBMS and SQL

4. 1. General RDBMS Concepts - Relational Vs. File Systems, normalization, ERD, extensibility Flat Files vs. Relational Databases Flat file is "A relatively simple database system in which each database is contained in a single table (or two). In contrast, relational database systems use multiple tables to store information, and each table can have a different record format.” - ZDNet’s Definition. Examples Scenario – Order Entry System File Database design: Cust Name, Cust Address, Order Date, Order Header, Item 1, Qty 1, Price1, Item 2, Qty 2, Price2, Item 3,……… RDBMS Customer Table : Name, Address …… Order Table: Link to Customer Table, Order Header …. Order Item Table: Link to Order Table, Qty, Link to Product Table …. Product Table: Product Name, Cost, Price, On Hand Qty ….. Suggested Reading on Normalization Introduction to RDBMS and SQL

5. 1. General RDBMS Concepts - Relational Vs. File Systems, normalization, ERD, extensibility CustomerOrderOrder Item Product Entity Relationship Diagram or ERD for 3 RD Normal Form Entity Customer.Customer_Num = Order.Customer_Num Primary KeyForeign Key 1 to Many (1:M) ‏ Customer can have minimum zero and max many/unlimited orders Order can have minimum one and maximum one Customer Attributes are all non-Key fields of an entity (typically one table) ‏ Hierarchical table design example, employee-manager Introduction to RDBMS and SQL

6. 1. General RDBMS Concepts - Relational Vs. File Systems, normalization, ERD, extensibility What is Normalization ? Arranging data into logical groupings such that each group describes a small part of the whole; minimizing the amount of duplicate data stored in a database; organizing the data such that, when you modify it, you make the change in only one place; building a database in which you can access and manipulate the data quickly and efficiently without compromising the integrity of the data in storage. Introduction to RDBMS and SQL

7. 1. General RDBMS Concepts - Relational Vs. File Systems, normalization, ERD, extensibility Example of poorly normalized table Introduction to RDBMS and SQL

8. 1. General RDBMS Concepts - Relational Vs. File Systems, normalization, ERD, extensibility Example of well normalized tables in 3NF Introduction to RDBMS and SQL

9. 1. General RDBMS Concepts - Relational Vs. File Systems, normalization, ERD, extensibility Extensibility - Commonly observed poorly designed tables: 1. Employee, Manager1, Manager2, Manager3 What will happen if a fourth manager comes into picture? What if 99% of employees have only one manager? 2A. Order Number, Part Number, Part Description 2B. Part Number, Part Description What if Part Description needs to be changed? 3A. Candidate Name, Address …. 3B. Masters Degree College, Graduation Year, Under-grad college, under- grad year, high school, high school year Several candidates will have only high-school though a few will have Masters Introduction to RDBMS and SQL

10. 1. General RDBMS Concepts - Relational Vs. File Systems, normalization, ERD, extensibility Getting started quickly on SQL: SQL*Plus is the most commonly used program to work with Oracle Database Another commonly used program is SQLPLUS Worksheet We will use SQL*Plus for this session Introduction to RDBMS and SQL

11. 1. General RDBMS Concepts - Relational Vs. File Systems, normalization, ERD, extensibility Starting SQL*Plus Introduction to RDBMS and SQL

12. 2. SQL DDL Before we begin, common, useful commands for Oracle (NON-ANSI): Select * from tab; Describe Select sysdate from DUAL; Introduction to RDBMS and SQL

13. Data Definition Language is used to create Tables, Indexes, Views, Sequences, DB Links, Tablespaces etc.. Creating a table (click here for suggested reading): Create table TableName ( ColumnName1 int, ColumnName2 char(10), ColumnName3 varchar2(20), ColumnName4 Long); Create table TableName as Select ColumnName1, ColumnName2….. from ExistingTable; 2. SQL DDL Exercise – Create a set of tables in 3 rd Normal Form (3 or 4 tables). Use as many data-types as you can. Note that only one Long field is allowed per table (how will you solve this problem, if you need more than 1?). Suggested Reading click (here)‏ Introduction to RDBMS and SQL

14. Some tips After any DDL, transactions are always committed Advance table creation options with tablespaces, extent sizes etc. Indexes – guidelines on creation, statistics, sizing, composite index use Sequence Object – its use, avoidable problems Database Links Referential Integrity 2. SQL DDL Recreate the tables you created to add a few referential integrity checks. Suggested Reading click (here)‏ Introduction to RDBMS and SQL

15. 9.15 am – 10.30 am 3. SQL DML (Data manipulation language) - selection, projection, aggregates, inner/outer/self/recursive/nested/co-related, updates, inserts, index use, statistics use, best practices and tips 4. Vendor enhancements to SQL - example SQL*PLUS and iSQL, functions (string, math, date etc.) ‏ 5. Examples of some tough SQLs for selects, inserts, updates and deletes Introduction to RDBMS and SQL

16. Employee Table = Emp_Id, Emp_Fname, Emp_Lname, Age, Salary 3. SQL DML (Data manipulation language) ‏ Select Emp_Id, Age, Salary From Employee Where Salary 30; SELECTION PROJECTION SELECTION & PROJECTION To select all fields, we can use “*”. For example, Select * from Employee To select all rows, just drop the WHERE clause Introduction to RDBMS and SQL

17. Select Emp_Id, Age, Salary From Employee Where Salary 30 Order by Salary, Age Descending; Employee Table = Emp_Id, Emp_Fname, Emp_Lname, Age, Salary 3. SQL DML (Data manipulation language) ‏ ORDER BY Introduction to RDBMS and SQL

18. Select A.Emp_Id, A.Age, B.Company_Name From Employee A, Company B Where A.Company_id = B.Company_Id and A.Age > 30 Order by A.Age Descending; Employee Table = Emp_Id, Emp_Fname, Emp_Lname, Age, Company_ID Company Table = Company_Id, Company_Name 3. SQL DML (Data manipulation language) ‏ SIMPLE (PLAIN or INNER) JOIN Note: Result set is a Cartesian product of number of rows from each table Be careful to ensure all tables are joined correctly Introduction to RDBMS and SQL

19. SOME COMMON EXAMPLES ARE COUNT, SUM, AVG etc. Employee Table = Emp_Id, Emp_Fname, Emp_Lname, Age, Company_ID Company Table = Company_Id, Company_Name AGGREGATE FUNCTIONS Common mistake – Group by is used even if there is no aggregate function in select Select AVG(A.Age), B.Company_Name From Employee A, Company B Where A.Company_id = B.Company_Id and Group by B.Company_Name Order by 1; 3. SQL DML (Data manipulation language) ‏ Introduction to RDBMS and SQL

20. SOME COMMON EXAMPLES ARE COUNT, SUM, AVG etc. Employee Table = Emp_Id, Emp_Fname, Emp_Lname, Age, Company_ID Company Table = Company_Id, Company_Name DISTINCT Note – Distinct should be used very rarely. Need to use Distinct often is indicative of a bad application design Select distinct Company_Name From Company; Select count (distinct Company_Name) From Company; 3. SQL DML (Data manipulation language) ‏ Introduction to RDBMS and SQL

21. SOME COMMON EXAMPLES ARE COUNT, SUM, AVG etc. Employee Table = Emp_Id, Emp_Fname, Emp_Lname, Age, Company_ID Company Table = Company_Id, Company_Name “HAVING” CLAUSE Having clause is like a Where clause for Aggregate attributes Select AVG(A.Age), B.Company_Name From Employee A, Company B Where A.Company_id = B.Company_Id and Group by B.Company_Name Having AVG(A.Age) > 20 3. SQL DML (Data manipulation language) ‏ Introduction to RDBMS and SQL

22. Significance of NULL value To compare a column to NULL, use “IS NULL” or “IS NOT NULL” instead of “=NULL” or “!=NULL” because comparison with NULL will always evaluate to FALSE Example – Select * from Employee where Age is NULL; NVL Function is another way to compare NULLS Example – Select * from Employee where NVL(Age,0) = 0; 3. SQL DML (Data manipulation language) ‏ Introduction to RDBMS and SQL

23. Operators and Expressions in SQL Suggested Reading 3. SQL DML (Data manipulation language) ‏ Introduction to RDBMS and SQL

24. Self referencing joins Suggested Reading select employee_name, mgr_name, level from employee connect by prior employee_name= Mgr_name Note to myself: Demo this in conv@siebel3_fltux5 3. SQL DML (Data manipulation language) ‏ Introduction to RDBMS and SQL

25. Standard ANSI SQL and Oracle Compliance Suggested Reading 3. SQL DML (Data manipulation language) ‏ Introduction to RDBMS and SQL

26. Sub Queries Select a.last_name, a.fst_name from s_contact a where a.last_name in (select b.last_name from s_prospect) ‏ Co-related Sub Queries Select a.last_name, a.fst_name from s_contact a where a.pr_addr_id in (select b.row_id from s_addr_per b where b.per_id = a.row_id) ‏ 3. SQL DML (Data manipulation language) ‏ Introduction to RDBMS and SQL

27. Exists clause Select * from contacts A where exists (select 1 from Orders B where B.contact_id=a.contact_id) ‏ Not Exists Select * from contacts A where not exists (select 1 from Orders B where B.contact_id=a.contact_id) ‏ 3. SQL DML (Data manipulation language) ‏ Introduction to RDBMS and SQL

28. Insert Update Insert examples insert into Contact (Fst_name, Last_name) ‏ values (‘John’, ‘Smith’); insert into Contact values (‘John’, ‘Smith’….); insert into Contact (Fst_name, Last_name) select First, Last from AnotherContactTable; Update examples Update Contact set Fst_Name=Last_Name where Fst_Name is null; Update Contact set Fst_Name = ‘Cliff’ where last_name=‘Luchsinger’; Update Contact A set A. Company_id = (select b.company_id from Company B where A.phone_number=b.phone_number); 3. SQL DML (Data manipulation language) ‏ Introduction to RDBMS and SQL

29. Delete Truncate Delete examples Delete from Contact where last_upd < sysdate – 5*365 ; Delete Contact where last_upd < sysdate – 5*365 ; Delete Contact A where not exists (select 1 from Orders B where B.contact_id=A.contact_id); Truncate example Truncate table Contact 3. SQL DML (Data manipulation language) ‏ Introduction to RDBMS and SQL

30. “Decode” function in Oracle Select Event, Year, decode(Month, 1, ‘Jan’, 2, ‘Feb’,….11,’Nov’,’Dec’) from History; Decodes can be nested. 4. Vendor enhancements to SQL – Some Example SQL Server has an equivalent function called iff. Introduction to RDBMS and SQL

31. Problem – You forgot to create unique indexes on a table and by mistake, duplicate records got loaded. Even the primary keys are dups. You need to clean up the table such that only one record is left behind. Delete DupTable A where A.Rowid < (select max(B.Rowid) from DupTable B where b.primary_key=a.primary_key); 5. Example of a tough SQL Introduction to RDBMS and SQL

32. Setup one data source. Connect to this datasource using MS-ACCESS 6. Set-up ODBC Introduction to RDBMS and SQL

33. See your training folder for the “ exercises-RDBMS, SQL, PLSQL.ppt” 7. Exercises Introduction to RDBMS and SQL

34. About the Author A shish Raghute currently works as the IT Director at Fleetwood Enterprises, Inc., USA’s leader in recreational vehicle sales and a leading producer and retailer of manufactured housing. Prior to joining Fleetwood, Ashish was a Principal at IBM Business Consulting Services and Principal Consultant at PricewaterhouseCoopers Consulting. For more than 15 years, Ashish has guided companies of various sizes from dot net startups to Fortune 1000 to successfully realize their IT vision in the areas of CRM, ERP, Data Warehousing and E-Business. Ashish can be contacted via email at raghute@yahoo.com.