1. 1 Introduction to Database Systems, CS420 SQL Views and Indexes

2. Agenda View Definition Materialized View Indexes 2

3. 3 Views A view is a relation defined in terms of stored tables (called base tables ) and other views. Two kinds: 1. Virtual = not stored in the database; just a query for constructing the relation. 2. Materialized = actually constructed and stored.

4. 4 Declaring Views Declare by: CREATE [MATERIALIZED] VIEW AS ; Default is virtual.

5. 5 Example: View Definition CanDrink(drinker, beer) is a view “containing” the drinker-beer pairs such that the drinker frequents at least one bar that serves the beer: CREATE VIEW CanDrink AS SELECT drinker, beer FROM Frequents, Sells WHERE Frequents.bar = Sells.bar;

6. View Usage - Restricting Access Provide an additional level of table security by restricting access to a predetermined set of rows or columns of a table 6

7. Example the staff view does not show the salary or commission_pct columns of the base table employees 7

8. View Usage - Hide Data Complexity A single view can be defined with a join, which is a collection of related columns or rows in multiple tables  However, the view hides the fact that this information actually originates from several tables A query might also perform extensive calculations with table information Thus, users can query a view without knowing how to perform a join or calculations 8

9. Example – Complex Query A view can be created for it 9

10. View Usage - Different Presentation Present the data in a different perspective from that of the base table For example, the columns of a view can be renamed without affecting the tables on which the view is based 10

11. View Usage - Independence Isolate applications from changes in definitions of base tables Example  A view references three columns of a four column table  A fifth column is added to the table  The definition of the view is not affected  All applications using the view are not affected 11

12. 12 Example: Accessing a View Query a view as if it were a base table.  Also: a limited ability to modify views if it makes sense as a modification of one underlying base table. Example query: SELECT beer FROM CanDrink WHERE drinker = ’Sally’;

13. 13 Triggers on Views Generally, it is impossible to modify a virtual view, because it doesn’t exist. But an INSTEAD OF trigger lets us interpret view modifications in a way that makes sense. Example: View Synergy has (drinker, beer, bar) triples such that the bar serves the beer, the drinker frequents the bar and likes the beer.

14. 14 Example: The View CREATE VIEW Synergy AS SELECT Likes.drinker, Likes.beer, Sells.bar FROM Likes, Sells, Frequents WHERE Likes.drinker = Frequents.drinker AND Likes.beer = Sells.beer AND Sells.bar = Frequents.bar; Natural join of Likes, Sells, and Frequents Pick one copy of each attribute

15. 15 Interpreting a View Insertion We cannot insert into Synergy --- it is a virtual view. But we can use an INSTEAD OF trigger to turn a (drinker, beer, bar) triple into three insertions of projected pairs, one for each of Likes, Sells, and Frequents.  Sells.price will have to be NULL.

16. 16 The Trigger CREATE TRIGGER ViewTrig INSTEAD OF INSERT ON Synergy REFERENCING NEW ROW AS n FOR EACH ROW BEGIN INSERT INTO LIKES VALUES(n.drinker, n.beer); INSERT INTO SELLS(bar, beer) VALUES(n.bar, n.beer); INSERT INTO FREQUENTS VALUES(n.drinker, n.bar); END;

17. 17 Materialized View

18. Materialized Views (MVs) Materialized views are query results that have been stored or "materialized" in advance as schema objects The FROM clause of the query can name tables, views, and materialized views Collectively these objects are called master tables (a replication term) or detail tables (a data warehousing term) 18

19. A MV with 3 Tables Creates and populates a materialized aggregate view based on three master tables 19

20. Base Table Dropped Lets now drop table sales, which is a master table for sales_mv Then queries sales_mv. 20

21. Data Selected The query selects data because the rows are stored (materialized) separately from the data in the master tables 21

22. Replication Environment In a replication environment, a MV shares data with a table in a different database, called a master database 22

23. MV Usage Materialized views are used to summarize, compute, replicate, and distribute data In data warehouses, you can use materialized views to compute and store data generated from aggregate functions such as sums and averages 23

24. 24 Example: A Data Warehouse Wal-Mart stores every sale at every store in a database. Overnight, the sales for the day are used to update a data warehouse = materialized views of the sales. The warehouse is used by analysts to predict trends and move goods to where they are selling best.

25. 25 What to Materialize? Store in warehouse results useful for common queries Example: day 2 day 1 129... total sales materialize

26. 26 Materialized Views Refresh Problem: each time a base table changes, the materialized view may change.  Cannot afford to recompute the view with each change. Solution: Periodic reconstruction of the materialized view, which is otherwise “out of date.”

27. 27 Indexes

28. 28 Indexes Index = data structure used to speed access to tuples of a relation, given values of one or more attributes. Could be a hash table, but in a DBMS it is always a balanced search tree with giant nodes (a full disk page) called a B-tree.

29. 29 Declaring Indexes No standard! Typical syntax: CREATE INDEX BeerInd ON Beers(manf); CREATE INDEX SellInd ON Sells(bar, beer);

30. 30 Using Indexes Given a value v, the index takes us to only those tuples that have v in the attribute(s) of the index. Example: use BeerInd and SellInd to find the prices of beers manufactured by Pete’s and sold by Joe. (next slide)

31. 31 Using Indexes - (2) SELECT price FROM Beers, Sells WHERE manf = ’Pete’’s’ AND Beers.name = Sells.beer AND bar = ’Joe’’s Bar’; 1. Use BeerInd to get all the beers made by Pete’s. 2. Then use SellInd to get prices of those beers, with bar = ’Joe’’s Bar’

32. 32 Database Tuning A major problem in making a database run fast is deciding which indexes to create. Pro: An index speeds up queries that can use it. Con: An index slows down all modifications on its relation because the index must be modified too.

33. 33 Example: Tuning Suppose the only things we did with our beers database was: 1. Insert new facts into a relation (10%). 2. Find the price of a given beer at a given bar (90%). Then SellInd on Sells(bar, beer) would be wonderful, but BeerInd on Beers(manf) would be harmful.

34. 34 Tuning Advisors A major research thrust.  Because hand tuning is so hard. An advisor gets a query load, e.g.: 1. Choose random queries from the history of queries run on the database, or 2. Designer provides a sample workload.

35. 35 Tuning Advisors - (2) The advisor generates candidate indexes and evaluates each on the workload.  Feed each sample query to the query optimizer, which assumes only this one index is available.  Measure the improvement/degradation in the average running time of the queries.

36. Summary View and MV definition Usage cases Indexes 36

37. 37 END