1. 6 Chapter 6 Structured Query Language (SQL)

2. 6 2 Sample Database for the following examples Publishing company has three subsidiary publishers. Need to keep info about books, authors, editors, & publishers. Assume: –an author may write more than one book –a book may have more than one author –each book has one publisher –each book has one editor (may need to revise this assumption) –each editor may edit more than one book.

3. 6 3 BookBiz Database title_id title price type pubdate ytd_sales advance pub_id ed_id au_id au_lname au_fname phone address city state zip pub_id pub_name address city state zip authorspublishers titles ed_id ed_lname ed_fname phone address city state zip editors titleauthors title_id au_id au_ord royaltyshare

4. 6 4 SELECT Queries SELECT [ALL| DISTINCT] Select_list FROM Table_list [WHERE Search_conditions] [GROUP BY Group_by_list] [HAVINGSearch_conditions] [ORDER BY Order_by_list] Order of clauses is important keywords are case insensitive. Everything else is (depends on system) Attribute and table names may have to be qualified: owner.database.table.attribute

5. 6 5 Eliminating Duplicate Row: DISTINCT SELECT [ALL| DISTINCT] Desired Attributes …… ALL returns all qualified rows (default) DISTINCT returns only unique rows Example: Select titleSelect DISTINCT titlefrom titlesorder by title

6. 6 6 WHERE Clause: Search Conditions Relational operators Logical: AND, OR, NOT Special –BETWEEN - defines limits –IN - checks for value in a set –LIKE - checks for similar string –IS NULL - checks for nulls –EXISTS - used with subqueries SELECT * FROM Publishers WHERE zip = 77002 OR V_CODE = 77077;

7. 6 7 Between Select title_id, ytd_sales Fromtitles Where ytd_slates BETWEEN 4000 AND 12000; Select title_id, ytd_sales Fromtitles Where ytd_slates NOT (BETWEEN 4000 AND 12000);

8. 6 8 IN List all authors who reside in the states of CA, TX or NY Select au_lname From authors where state in ('CA', 'TX', 'NY'); List must be in parentheses list elements separated by commas

9. 6 9 IS [NOT] NULL Null is a place holder for unknown info. Select title_id, advance from titles where advance is not null

10. 6 10 LIKE Match for embedded pattern in string Syntax: WHERE attribute [NOT] LIKE 'pattern' pattern must include a wildcard: % matches a string of zero or more chars - matches a single char E.g. find city of some author whose last name starts with 'Mc' or 'Mac' E.g. list all editors in the 713 area code

11. 6 11 ORDER BY Clause SELECTSelect_List FROMTable_list [WHERESearch_Conditions] [ORDER BYOrder_by_list] Order by allows you to sort results by any expression or mixture of expressions from the select_list

12. 6 12 ORDER BY Clause Ordering is ascending, unless you specify the DESC keyword. Ties are broken by the second attribute on the ORDERBY list, etc. Generally, items in orderby_list must also appear in select_list –attribute name –arithmetic expr of attributes –display label (alias) –a position number in select_list

13. 6 13 ORDER BY Clause Select title_id, pub_id, price*ytd_sales as income From titles Where type in (‘business’, ‘psychology’) Order by pub_id, income desc

14. 6 14 ORDER BY Clause Select title_id, pub_id, price*ytd_sales as income From titles Where type in (‘business’, ‘psychology’) Order by pub_id, 3 desc

15. 6 15 Aggregate Functions Aggregate functions are used to get summary values: sum, avg, min, max, count aggregates are applied to sets of rows –to all the rows in a table –to those rows specified in WHERE clause –to groups of rows set up by the GROUP BY clause Outcome is always a single value for each set of rows

16. 6 16 Aggregate Syntax aggregate_function([DISTINCT] expression) sum( [Distinct] expression) avg ( [Distinct] expression) count ([Distinct] expression) count(*)//count number of selected rows Max (expression) Min (expression) All aggregate functions, except count(*), ignore rows where expression is null

17. 6 17 Aggregate fiunctions Compute total ytd sales for all books Select sum(ytd_sales) From titles Note: Select price, sum(price) From titles NOT ALLOWED

18. 6 18 Aggregate fiunctions Compute total ytd sales for all books Select sum(ytd_sales) as Total From titles  Total 87654

19. 6 19 Aggregate fiunctions Total number of books: Select count(title_id) From titles May use any other attribute: Select count(price) From titles Same results as long as there are no NULL Select count(price), count(*) From titles Count distinct values? Select count(DISTINCT price) from titles

20. 6 20 Aggregate Functions--Count Count(expression) –expression is generally a column name –returns the number of non-null occurrences of the expression Count(distinct expression) –Each occurrence is counted only once Count(*) –counts numbers of rows (includes NULLs)

21. 6 21 GROUP BY Clause SELECT [ALL| DISTINCT] Select_list FROM Table_list [WHERE Search_conditions] [GROUP BY Group_by_list] [HAVINGSearch_conditions] [ORDER BY Order_by_list]

22. 6 22 Grouping Data & Aggregates The Group by clause partitions a table into sets of rows Aggregate functions (if any) produce summary values for each set ==> vector aggregates Having clause puts conditions on the group by results much like the Where clause qualifies the individual rows

23. 6 23 Grouping Data & Aggregates How many books each publisher has? Select pub_id, count(title_id) as count from titles group by pub_id pub_idcount 13806 273317 132221

24. 6 24 Groups within groups Select pub_id, type, count(title_id) as count from titles group by pub_id, type pub_idtype count 1380math2 1380cs4 2733math5 2733Business12 1322cs5 1322biology3 1322physics6 Divide the rows in the table by publishers Separate the rows in each publisher group by type Apply aggregate function(s) to each set

25. 6 25 Avoid confusing queries Select pub_id, type, count(title_id) as count from titles group by pub_id pub_idtype count 1380math6 1380cs6 2733math17 2733Business17 1322cs14 1322biology14 1322physics14

26. 6 26 Groups All NULLs are include in same group Order_by clause always goes after Group_by E.g. list avg price for each book type in ascend order. Include only books with more than $500 advance Select type, avg(price) as avg_price from titles where advance > 500 group by type order by avg_price

27. 6 27 Having Clause Puts conditions on the group_by results I.e. on groups formed by the group_by Having conditions must be either –from select_list –aggregate function Order of execution: 1. Where clause selects rows 2. Group_by partitions resulting rows from (1) 3. Aggregates on groups are calculated 4. Having clause checks results of group rows to see which qualify for output.

28. 6 28 Having Clause Get number of books and average price of each book type whose average price is above $50 Select type, count(*), avg(price) from titles group by type having avg(price) > 50

29. 6 29 Where vs Having Select type, count(*), avg(price) from titles where price > 50 group by type Get number of books and average price of each book type. Include only books whose price is above $50

30. 6 30 Where vs Having Can't use aggregates in WHERE clause WHERE clause applies to individual rows HAVING clause applies to groups of rows

31. 6 31 Where vs Having Select type, count(*) from titles group by type having type like 'B%' Equivalent to: Select type, count(*) from titles where type like 'B%' group by type

32. 6 32 BookBiz Database title_id title price type pubdate ytd_sales advance pub_id ed_id au_id au_lname au_fname phone address city state zip pub_id pub_name address city state zip authorspublishers titles ed_id ed_lname ed_fname phone address city state zip editors titleauthors title_id au_id au_ord royaltyshare Sales Sonum store_id sdate Sonum title_id qty_ordered qty_shipped date_shipped Salesline

33. 6 33 Joining Tables The join operation lets you retrieve data from more than one table in a SELECT statement. Joins are needed because during the normalization process, data is split in multiple tables to minimize redundancy. There can be more than one join op in a SELECT statement Each join operation is done on two tables, using one column from each table as a connecting column Join column should have compatible data types

34. 6 34 Joining Tables--Example List the names of the authors of the book titled “Database Systems” SELECT au_lname, au_fname FROM authors a, titles t, titleauthors tl WHERE t.title_id = tl.title_id AND tl.au_id = a.au_id AND t.title = ‘Database Systems’ ;

35. 6 35 Joining Tables – SYNTAX-1 SelectSelect_list From table-1, table_2 [, table_3,…] Where [table_1.]Col join_op [table_2.]Col Tables are joined pairwise join_op: a relational operator Specify a join on two tables using a column from each table as a connecting column. connecting columns must be join compatible. Best if they have same data type. Connecting columns DO NOT have to have the same name.

36. 6 36 Joining Tables Most often: connecting column is a primary key of one table and foreign key of the second table. Example: Find the name of the editor of book title "Database Systems" Select ed_fname, ed_lname From editors e, titles t Where t.ed_id = e.ed_id AND t.title =‘Database Systems’ ;

37. 6 37 Joining Tables – SYNTAX-2 SELECTSelect_list FROM table-1 [NATURAL|CROSS]JOIN table_2 [ON [table_1.]Col join_op [table_2].Col] | USING (column) ] join_op: a relational operator If keywords NATURAL or CROSS are used, the ON and USING clauses are not allowed NATURAL JOIN works only when the two tables have a single identical column. The join is done on this column CROSS JOIN produces the Cartesian product  need to use a WHERE clause with it.

38. 6 38 Joining Tables Example: Find the name of the editor of book title "Database Systems“ SELECT ed_fname, ed_lname FROM editors JOIN titles ON editors.ed_id = titles.ed_id WHERE title.title ='Database Systems’ SELECT ed_fname, ed_lname FROM editors NATURAL JOIN titles WHERE title.title = ‘Database Systems’ SELECT ed_fname, ed_lname FROM editors CROSS JOIN titles WHERE editors.ed_id = titles.ed_id AND title.title ='Database Systems’

39. 6 39 Joining Tables e.g. find out if any editor is also an author select ed_lname, ed_fname from editors, authors where editors.ed_id = authors.au_id Note: if connecting columns have NULLs, the NULLs won't join: NULLs are not equal to each other

40. 6 40 Joining Tables--Examples Find all authors who live in same city as any publisher Select a.au_lname, a.city, p.pub_name From authors a, publishers p where a.city = p.city

41. 6 41 Joining more than two tables example: find titles of all business books and the names of their authors Select au_lname, au_fname, title from authors a, titles b, tiltesauthors ba where a.au_id = ba.au_id and b.title_id = ba.title_id and b.type = 'business'

42. 6 42 Self_joins Example: list all authors with same last name Select a1.au_id, a1.au_fname, a1.au_lname from authors a1, authors a2 where a1.au_lname = a2.au_lname and a1.au_id <> a2.au_id

43. 6 43 Self_joins Find authors who live in same city as "Steven King" Selectau_lname, au_fname, city from authors a1, authors a2 where a1.city = a2.city and a2.au_lname = 'King' and a2.au_fname = 'Steven'

44. 6 44 Non-equijoins Equijoin: join on matching (equal) values Join can be done on other relational operations: > >= <= <>

45. 6 45 Joins not based on equality Example: list all authors with same last name Select a1.au_id, a1.au_fname, a1.au_lname from authors a1, authors a2 where a1.au_lname = a2.au_lname and a1.au_id <> a2.au_id

46. 6 46 Joins not based on equality Find all sales orders that were on date later than the sales date (company tries to ship same day) and the store id and date they were sold at. SELECT DISTINCT s.sonum, s.store_id, s.sdate FROM sales s, salesline sl WHERE s.sdate < sl.date_shipped AND s.sonum = sl.sonum;

47. 6 47 Subqueries A subquery is a SELECT statement that nests inside the WHERE or HAVING clause of another SELECT, INSERT, UPDATE or DELETE statement SELECT [DISTINCT] Select_list FROM Table_list WHERE {expression [not] IN | comparison_op [ANY|ALL] | EXISTS} (SELECT [DISTINCT] Select_list FROM Table_list WHERE Conditions ) [GROUP BY Group_by_list] [HAVINGSearch_conditions] [ORDER BY Order_by_list]

48. 6 48 Simple Subqueries Find names of publishers who publish CS books Select distinct pub_name from publishers where pub_id IN (Select pub_id from titles where type = 'CS') Inner and outer queries are evaluated in two steps. First the inner subquery is evaluated. Then the result (a set of pub_ids) are passed to outer subquery.

49. 6 49 Subqueries & Joins Select distinct pub_name from publishers p, titles b where p.pub_id = b.pub_id and type = 'CS' Subqueries and joins can often be used interchangeably In some cases, one is preferred to other

50. 6 50 Subqueries & Joins Find all books with prices equal to the minimum book price. Subquery: select title, price from titles where price = ( select min (price) from titles) Can NOT be done with a join.

51. 6 51 Subqueries & Joins Find name of the authors whose address is in the same city as the home office of a publisher (list pub_name, authors name & city) Join: select pub_name, au_fname, au_lname, authors.city From publishers, authors where publishers.city = authors.city

52. 6 52 Subqueries & Joins Subquery select pub_name From publishers where city in ( Select city from authors) Can only list information from outer query, NOT from both

53. 6 53 Subqueries & Joins: Which is better? Use subqueries when you need to compare aggregates to other values. Use joins when you need to display results from multiple tables. Otherwise, you may use either.

54. 6 54 Subqueries & Joins Find the names of all second authors who live in California and receive less than 30% of the royalties on the books they coauthor select au_lname, au_fname from authors where state = 'CA' and au_id IN ( select au_id from bookauthors where au_ord = 2 and royaltyshare < 0.30)

55. 6 55 Subqueries & Joins select au_lname, au_fname from authors a, bookauthors ba where state = 'CA' and a.au_id = ba.au_id and ba.au_ord = 2 and ba.royaltyshare < 0.30)

56. 6 56 Self_join Find authors who live in same city as "Steven King" Select au_lname, au_fname, city from authors where city IN (select city from authors where au_fname='Steven' and au_lname='King')

57. 6 57 Correlated Subqueries Find names of publishers who publish CS books Select distinct pub_name from publishers where pub_id IN (Select pub_id from titles where type = 'CS')

58. 6 58 Correlated Subquery Find names of publishers who publish CS books Select distinct pub_name from publishers p where exists (Select * from titles t where t.pub_id = p.pub_id and t.type = 'CS') Inner query needs p.pub_id values from outer query, and passes results to outer query. The exists operator succeeds if the result of the inner query is non-empty.

59. 6 59 Correlated Subquery Processing 1. Outer query finds the first name in the publishers table and its id: p.pub_id 2. The inner query looks up the titles table to find rows whose tiltes.pub_id = p.pub_id and titles.type = 'CS' 3. The result is returned to the outer query. 4. The exists operator of the outer query check for existence: if result is not empty set, outer query include the p.pub_id of step 1 in it final result 5. Steps 1-4 are repeated for each pub_id in publishers table.

60. 6 60 Subquery Rules 1. The SELECT list of an inner subquery introduced with a comparison operator or IN can include only one expression or column. The column you name in the WHERE clause of the outer query must be join-compatible with the column you name in the subquery SELECT list. Select pub_name from publishers where pub_id IN (Select pub_id from titles where type = 'CS')

61. 6 61 Sub-query Rules Cont. 2. Sub-queries can not include the ORDER BY clause 3. The SELECT list if a subquery introduced with the EXISTS operator always consists of the (*) Select pub_name from publishers p where exists (Select * from titles t where t.pub_id = p.pub_id and t.type = 'CS')

62. 6 62 Subquery Rules Cont. Three types of subqueries: 1. Subqueries that return 0 or any number of items: Use IN operator, or comparison modified by ALL or ANY 2. Subqueries that return a single value: use unmodified comparison 3. Subqueries that are an existence test: [NOT]EXISTS operator The EXISTS operator is generally used with correlated queries.

63. 6 63 Subqueries: IN & NOT IN Find names of publishers who have NOT published CS books Select pub_name from publishers where pub_id NOT IN (select pub_id from titles where type = 'CS')

64. 6 64 Comparisons with ALL and ANY > ALL ==> larger than the max > ANY ==> larger than the min less than the min less than the max = ALL ==> equal to each (all at same time) = ANY ==> equal to at least one (same as IN op)

65. 6 65 Comparisons with ALL and ANY Which books commanded an advance greater than any book published by Pub1 Inc. select title from titles where advance > all (select advance from publishers p, titles b where p.pub_name = 'Pub1 Inc.' and b.pub_id = p.pub_id)

66. 6 66 Comparisons with ALL and ANY Which books commanded an advance greater than the minimum advance amount paid published by Pub1 Inc. select title from books where advance > ANY (select advance from publishers p, titles b where p.pub_name = 'Pub1 Inc.' and b.pub_id = p.pub_id)

67. 6 67 Comparisons with ALL and ANY Find authors who live in same city as some publisher 1)Select au_lname, au_fname, city from authors where city IN (select city from publishers) order by city; 2)Select au_lname, au_fname, city from authors where city =ANY (select city from publishers) order by city;

68. 6 68 Unmodified Comparisons Unmodified comparisons return a single value Select au_lname, au_fname from authors where city = (select city from publishers where pub_name = 'Prentice Hall') Finds names of authors who live in same city where Prentice Hall is located. Assumes each publisher is located in one city. Note: Subquery must return a single value. Otherwise, error.

69. 6 69 Unmodified Comparisons Usually used with aggregate function because they are guaranteed to return a single value. Example: Find names of all books with prices higher than the average price select title from titles where price > (select avg(price) from titles)

70. 6 70 Unmodified Comparisons Comparison subqueries can not include GROUP BY and HAVING clause. E.g. select title from titles where price > (select min(price) from titles group by type ) generates an error

71. 6 71 Correlated Subqueries with comparisons Find titles whose price is greater than the average price for books of its type Select t1.type t1.title from titles t1 where t1.price > (Select avg(t2.price) from titles t2 where t2.type = t1.type ) For each row of t1, the system evaluates the subquery and includes the row in the final result if the price value in that row is greater than the calculated average.

72. 6 72 Multi-Level Subqueries Find the names of authors who have participated in writing at least one CS book. Select au_lname, au_fname from authors a, titles t, titleauthors ta where a.au_id = ta.au_id AND t.title_id = ta.title_id AND t.type ='CS'

73. 6 73 Multi-Level Subqueries Find the names of authors who have participated in writing at least one CS book. Select au_lname, au_fname From authors Where au_id IN (Select au_id From titleauthors Where title_id IN (Select title_id From titles Where type= 'CS' ) )

74. 6 74 Subqueries in the FROM Clause Get number of sales orders for each store Select store_id, count(sonum) From sales group by store_id Get store_id and the number of sales orders of stores with more than 10 sales orders. Select store_id, count(sonum) From sales group by store_id having count(sonum) > 10;

75. 6 75 Subqueries in the FROM Clause CNTD Get store_id and number of sales orders for the store with highest sales order Select store_id, count(sonum) From sales group by store_id having count(sonum) = max(count(sonum)) Can't nest aggregates !

76. 6 76 Subqueries in the FROM Clause Create a subquery in the outer FROM to define a subset of data (called a view) with a single column consisting of sales order count for each store alias the view use the view in a select statement Select store_id, max(s.num) from ( select store_id, count(sonum) as num from sales group by store_id) s

77. 6 77 Subqueries in the HAVING Clause List types of books in which maximum advance is at least twice the average advance of books of that type select t1.type from titles t1 group by t1.type having max(t1.advance) in (select 2*avg(t2.advance) from titles t2 where t1.type = t2.type) Subquery is evaluated once for each group of outer query

78. 6 78 Creating and Using Views A view creates a virtual table from a SELECT statement. Think of it as a movable window through which users can see data. Definition of a view is stored in the system catalog. Views don’t exist as independent entities in the Database as “real” tables do. create views using CREATE VIEW delete views using DROP VIEW

79. 6 79 Creating and Using Views CREATE VIEW view_name [ zero or more columns] AS SELECT_Statement example: create a view that displays names of authors who live in Houston, Texas

80. 6 80 Creating and Using Views create view houstonians (FirstName, LastName, Book) as select au_fname, au_lname, title from authors a, titles t, titleauthors ta where a.au_id = ta.au_id and t.title_id = ta.au_id and a.city = 'Houston' and a.state = 'Texas'

81. 6 81 Displaying Data thru the view Select * from houstonians Creating a view does not create any tables. It simply stores the view's name and definition in the database catalog when the view is used, its select statement is retrieved from the catalog and executed.

82. 6 82 Displaying Data thru the view a view in a select statement works just like a table Select Book as Title, Lastname as Surname from houstonians order by Title Select LastName, count(Book) from houstonians group by LastName having count(Book) > 5

83. 6 83 Advantages of views 1. Once a view is created ==> less typing and less errors due to typos example: a salesman need info on which author wrote which book and their order create view books_SalesmanVersion as select titles.title_id, au_ord, au_lname, au_fname from authors a, titles t, titleauthors ta where a.au_id = ta.au_id and t.title_id = ta.book_id and b.type = 'business'

84. 6 84 Advantages of views Once the view is created, no need to retype the whole select query. E.g. select * from books_SalesmanVersion etc.

85. 6 85 Advantages of views. Views can be used to provide users with access to only a subset of whole data. E.g. an executive may only be interested on knowing how the different categories of books are doing at each subsidiary. Create view currentinfo (Pub#, Type, Income, Avg_Price, Avg_sales) as Select pub_id, type, sum(price*ytd_saels), avg(price), avg(ytd_sales) From titles Group by pub_id, type

86. 6 86 Advantages of views Limiting user access with views may be needed: 2. Customization: to help users focus on only the data they need 3. Independence: separating the users view of the data from actual structure of the database. If the structure of the database is changed, users don't even notice it. They still have the same view 1. Security: different users with access to different subsets of the data

87. 6 87 Naming view columns 1. Create view books1 (ID, Ord, Surname) as select title_id, au_ord, au_lname from titles //need a name for each item in select_list 2. Create view books2 as select title_id as ID, au_ord, au_lname as Surname from titles

88. 6 88 Naming view columns View columns MUST be named if view's column is a complex expression the view winds up with more than one column with same name. This occurs if there is join operation in the Select statement, the joined tables have columns of same names.

89. 6 89 Naming view columns Create a view that shows how the different categories of books are doing at each subsidiary. Create view currentinfo (Pub#, Type, Income, Avg_Price, Avg_sales) as Select pub_id, type, sum(price*ytd_saels), avg(price), avg(ytd_sales) from books group by pub_id, type

90. 6 90 Naming view columns Create view cities (Author, AuthorCity, Pub, PubCity) as Select au_lname, authors.city, pub_name, publishers.city from authors, publishers where authors.city = pubslishers.city

91. 6 91 Deriving Views from Views RECALL: Create view currentinfo (Pub#, Type, Income, Avg_Price, Avg_sales) as Select pub_id, type, sum(price*ytd_saels), avg(price), avg(ytd_sales) from books group by pub_id, type

92. 6 92 Deriving Views from Views Need to view same info., but only for books of type CS create view CS_currentinfo as select * from currentinfo where type = 'CS'

93. 6 93 Modifying Views Syntax is the same as for modifying tables E.g. Update Houstonians Set FirstName = ‘Sylvia’ Where FirstName = ‘Stan’; Changing data through views is a thorny issue. Problem: command to change data thu view are sometimes ambiguous.

94. 6 94 Modifying Views– Rules according to ANSI View are read-only if the CREATE VIEW statement contains one of the following: –DISTINCT in the select statement –Expressions in the select list (computed column, aggregates, etc) –References to more than one table– in the FROM clause, a subquery, or a Union –A Group By or HAVING clause –References to a view that is itself not updatable.

95. 6 95 UNION, INTERSECT & DIFFERENCE UNION: –Get a list of all authors and editors (Select au_lname as lname, au_fname as fname from authors) UNION (Select ed_lname as lname, ed_fname as fname from editors)

96. 6 96 UNION, INTERSECT & DIFFERENCE INTERSECTION –Get a list of all authors who are also editors (Select au_lname as lname, au_fname as fname from authors) INTERSECT (Select ed_lname as lname, ed_fname as fname from editors)

97. 6 97 UNION, INTERSECT & DIFFERENCE Difference –Get a list of all authors who are not editors (Select au_lname as lname, au_fname as fname from authors) EXCEPT (Select ed_lname as lname, ed_fname as fname from authors)

98. 6 98 DATA MODIFICATION INSERT: add new rows to a table UPDATE: change existing rows DELETE: delete existing rows

99. 6 99 INSERT Two ways: –With VALUES keyword –With SELECT statement INSERT with VALUES: INSERT INTO table_name [(column1, column2, …)] VALUES [(constant1, constant2, …)]

100. 6 100 INSERT with VALUES: Insert into publishers Values (‘1622’, ‘UHD Press’, ‘1 Main Str.’, ‘Houston, ‘TX’); Insert into publishers (pub_id, pub_name) Values (‘1777’, ‘Prentice Hall’); All other fields are Null Can’t insert same entity more than once

101. 6 101 Insert with Select Used if you need to insert values generated by a query Insert into table_name [(insert_column_list)] Select column_list From table_list Where search_conditions

102. 6 102 Insert with Select Suppose a table called newauthors exists with same format as authors Insert into newauthors Select au_id, au_lname, au_fname, phone, address, city, state, zip From authors OR Insert into newauthors Select * From authors

103. 6 103 Insert with Select Insert into books Select title_id, title, type, pub_id, price*1.5, advance, pubdate, ytd_sales, ed_id From titles;

104. 6 104 Update Update table_name Set column_name = expression [Where search_condition]; Update publishers Set city = ‘Atlanta’, state = ‘CA’  Changes city and state of all pubs

105. 6 105 Update Update publishers Set city = ‘Atlanta’, state = ‘CA’ Where pub_id = ‘1777’; Update tiltles Set price = price/2;

106. 6 106 Delete Delete from table_name Where search_conditions Delete from publishers Where pub_id = ‘1622’ or pub_id=‘1777’; Update publishers Set city = ‘Atlanta’, state = ‘CA’

107. 6 107 DATA DEFINITION CREATE TABLE table_name ( column_name datatype [NULL| NOT NULL] [, column_name datatype [NULL| NOT NULL]]…) CREATE table authors ( au_id char(11)not null, au_lname varchar(40) not null, au_fname varchar(20) not null, phonechar(12) null, addressvarchar(40) null, cityvarchar(20) null, statechar(2) null, zipchar(5) null)

108. 6 108 Data Types Character data types –Fixed length characters: char(n) –Variable length characters: varchar(n) Bit strings –Bit(n) –Bit varying(n) Boolean –True, false or unknown Integers –Int or integer –Shortint

109. 6 109 Data Types cntd Floating point numbers: –FLOAT or REAL –DOUBLE for higher precision –DECIMAL(n,d) n: total number of digits d: number of digits to the right of decimal point DATE and TIME: –DATETIME MONEY BINARY

110. 6 110 Deleting a Table DROP TABLE table_name DROP DATABASE database_name

111. 6 111 Modifying Relation Schemas ALTER TABLE table_name ADD/DROP/MODIFY column_name ALTER TABLE authors ADD birth_date datetime null ALTER TABLE authors MODIFY birth_date char(10) ALTER TABLE authors DROP birth_date

112. 6 112 Default Values The default of defaults: NULL Specifying default values: CREATE TABLE Person( name VARCHAR(30) not null, social-security-number CHAR(11) not null, age SHORTINT DEFAULT 100 null, city VARCHAR(30) DEFAULT “Houston” null, gender CHAR(1) DEFAULT “?”, Birthdate DATE null,

113. 6 113 Indexes REALLY important to speed up query processing time. Suppose we have a relation Person (name, social security number, age, city) An index on “social security number” enables us to fetch a tuple for a given ssn very efficiently (not have to scan the whole table). The problem of deciding which indexes to put on the relations is very hard! (it’s called: physical database design).

114. 6 114 Indexes Think of each table as being stored in several disk sectors, possibly on more than one disk. Searching for a tuple based on some attribute requires scanning the entire table (I.e. all sectors and possibly several disks where table is stored). An index is like the index of a book. It’s a lookup table gives the physical location of a tuples based on the values an indexed attribute(s).

115. 6 115 Creating Indexes CREATE INDEX ssnIndex ON Person(social-security-number) Indexes can be created on more than one attribute: CREATE INDEX doubleindex ON Person (name, social-security-number) Why not create indexes on everything?

116. 6 116 Indexes Mechanism for user/application to get improved performance from DBMS. It speeds up retrieval of data from large databases Somewhat similar to a book index: when looking for a particular subject to read, you don’t want to read every page to find the topic of interest. An index on a column allows the system to match values from that column without having to scan through all storage. An index is basically a table that provides logical pointers to the physical location of the data.

117. 6 117 Indexes Index on attribute R.A: - Creates additional persistent data structure stored with the database. - Can dramatically speed up certain operations: e.g. Find all R tuples where R.A = v Find all R and S tuples where R.A = S.B

118. 6 118 Indexes SELECT * FROM Student WHERE name = "Mary" Without index: Scan all Student tuples. With index: Go "directly" to tuples with name = "Mary".

119. 6 119 Creating an index CREATE INDEX IndexName ON Table_name(Column_name) Create index NameIndex On Students (Name) Create index auIndex On authors (au_id)

120. 6 120 UNIQUE Index Create UNIQUE index auIndex On authors (au_id) No duplicate values in the indexed column are allowed

121. 6 121 Composite Indexes SELECT * FROM Student WHERE name = "Mary" and GPA > 3.5 Could use: –Index on Student.name – Index on Student.GPA –Index on (Student.name,Student.GPA) Create index NameGPAIndex On Students (Name, GPA)

122. 6 122 Composite Index Create index auNameInd On authors (au_lname, au_fname) Needed when composite primary key

123. 6 123 Indexes Why not index every column in every table? Choosing which indexes to create is a difficult design issue the decision depends on size of tables and most importantly query/update load. Generally, you want to put indexes on columns you use frequently in retrieval, especially: –Primary key columns –Columns used frequently in joins (foreign keys) –Columns searched frequently for ranges of values –column searched frequently e.g. fname, lname

124. 6 124 Indexes Indexes should be avoided for Columns that are rarely referenced in queries Columns that are updated frequently Columns that have only few distinct values –e.g. gender: male, female Small tables with few rows