1. Joins, views, and subqueries CMSC 461 Michael Wilson

2. Multi table selects  So, we mentioned that we can refer to multiple tables during the course of our selects  How do we do this?  What does that do for us?

3. Joins  We went over the natural join before  There are actually a billion types of joins you can explicitly state in ANSI SQL  Okay, fine. There are 5 types.  There are a lot of good images on the net about this, but I’m uncomfortable with their licensing terms, so I’m going to re- draw them for you

4. Joining on  Most joins require you to join “on” a particular statement  The statements are the same kind that are used in WHERE clauses  Table1.id = Table2.AddressBookId  The PostgreSQL refers to this as the join condition

5. Join types  INNER JOIN  FULL OUTER JOIN  LEFT OUTER JOIN  RIGHT OUTER JOIN  CROSS JOIN

6. Inner join  This is one of the more frequent types of joins  Finds all rows which meet the join condition  Example  SELECT * FROM AddressBook a INNER JOIN CallList c on a.id = c.addressBookId;  a and c are aliases

7. Inner join

8. Left outer join  Contains all records between T1 and T2 that meet the join condition, and then any records in T1 that don’t meet the join condition  Rows for which the join condition is not met, the columns of T2 are padded with nulls

9. Left outer join

10. Right outer join  Contains all records between T1 and T2 that meet the join condition, and then any records in T2 that don’t meet the join condition  Rows for which the join condition is not met, the columns of T1 are padded with nulls

11. Right outer join

12. Full outer join  Contains all records between T1 and T2 that meet the join condition, and the combination of a left outer join and right outer join are appended onto the results

13. Full outer join

14. Cross join  Cross joins have no join condition  Cross joins literally return the Cartesian product (discussed in the relational algebra slides)

15. Implicit join notation vs. explicit  Inner joins can be accomplished with “implicit” join notation  In other words, we don’t literally use the terms “inner join” in our select statement  We can use where clauses/multi table selects to accomplish the same thing

16. Explicit join  SELECT * FROM AddressBook a INNER JOIN CallList c on a.id = c.addressBookId;

17. Implicit join  SELECT * FROM AddressBook a, CallList c WHERE a.id = c.addressBookId;

18. Which to use?  Which should you use?  It’s up to you, really  My experience  I never really use explicit syntax  Implicit makes much more sense to me, personally

19. Outer joins, cross joins in the real world?  You can very much create a fully functional database without using left outer joins, right outer joins, etc.  These types of joins allow you to collate data in ways that would be require much more data munging  More queries, more tables  Truth be told, I didn’t realize their power until writing these slides

20. Examples  Get a full list of employees and determine who has not enrolled in benefits  SELECT * FROM employees LEFT OUTER JOIN benefitsEnrollment ON employees.id = benefitsEnrollment.employeeId;  If an employee hasn’t enrolled in benefits, the benefitsEnrollment columns would come back as NULL

21. Views  A view is kind of like a virtual table  Views are defined as queries (SELECT statements)  They can be queried like tables  They are read only  Syntax:  CREATE VIEW AS

22. View example  CREATE VIEW phoneNumbers AS SELECT phoneNumber FROM AddressBook;  This would create a view that only contained phone numbers from our AddressBook

23. More complex views  CREATE VIEW callsAndInfo AS SELECT * FROM AddressBook a INNER JOIN CallList c on a.id = c.addressBookId;  Views are more useful for more complex queries  Can join these views on other tables as well

24. View danger!  Depending too heavily on views can cause performance issues if you’re not careful  You can apply constraints to view queries which have a heavy performance impact  If you have views that depend on views that depend on views

25. Materialized views  PostgreSQL has materialized views, which are views that are stored on disk  Periodically updated and stored  Regular views are not stored, so they always hit dependencies in real time  Syntax:  CREATE MATERIALIZED VIEW AS

26. Subqueries  You can use selects in your selects!  This is SUPER confusing  You can use them in both the FROM and the WHERE  Used in the from, kind of like in-lining a view  Can use them in the where to grab values from other tables

27. Subquery  SELECT * FROM Stalkers s, (SELECT * FROM AddressBook a INNER JOIN CallList c on a.id = c.addressBookId) c WHERE s.contactName = c.contactName;

28. Using subqueries in a from  SELECT * FROM UserProfile WHERE userId = (SELECT userId FROM MostPopularUser ORDER BY popularity LIMIT 1);