1. 2013-09-19 SLIDE 1IS 257 – Fall 2013 More on SQL (and SQLite) University of California, Berkeley School of Information I 257: Database Management

2. 2013-09-19 SLIDE 2IS 257 – Fall 2013 Lecture Outline Review –Relational Algebra and Calculus –Introduction to SQL More on SQL – creating and modifying data SQLite3 –Python and SQLite

3. 2013-09-19 SLIDE 3IS 257 – Fall 2013 Lecture Outline Review –Relational Algebra and Calculus –Introduction to SQL More on SQL – creating and modifying data SQLite3 –Python and SQLite

4. 2013-09-19 SLIDE 4IS 257 – Fall 2013 Relational Algebra Operations Select Project Product Union Intersect Difference Join Divide

5. 2013-09-19 SLIDE 5IS 257 – Fall 2013 Restrict (Select) Extracts specified tuples (rows) from a specified relation (table).

6. 2013-09-19 SLIDE 6IS 257 – Fall 2013 Project Extracts specified attributes(columns) from a specified relation.

7. 2013-09-19 SLIDE 7IS 257 – Fall 2013 Join Builds a relation from two specified relations consisting of all possible concatenated pairs, one from each of the two relations, such that in each pair the two tuples satisfy some condition. (E.g., equal values in a given col.) A1 B1 A2 B1 A3 B2 B1 C1 B2 C2 B3 C3 A1 B1 C1 A2 B1 C1 A3 B2 C2 (Natural or Inner) Join

8. 2013-09-19 SLIDE 8IS 257 – Fall 2013 Outer Join Outer Joins are similar to PRODUCT -- but will leave NULLs for any row in the first table with no corresponding rows in the second. A1 B1 A2 B1 A3 B2 A4 B7 B1 C1 B2 C2 B3 C3 A1 B1 C1 A2 B1 C1 A3 B2 C2 A4 * * Outer Join

9. 2013-09-19 SLIDE 9IS 257 – Fall 2013 Join Items

10. 2013-09-19 SLIDE 10IS 257 – Fall 2013 Relational Algebra What is the name of the customer who ordered Large Red Widgets? –Select “large Red Widgets” from Part as temp1 –Join temp1 with Line-item on Part # as temp2 –Join temp2 with Invoice on Invoice # as temp3 –Join temp3 with customer on cust # as temp4 –Project Name from temp4

11. 2013-09-19 SLIDE 11IS 257 – Fall 2013 Relational Calculus Relational Algebra provides a set of explicit operations (select, project, join, etc) that can be used to build some desired relation from the database. Relational Calculus provides a notation for formulating the definition of that desired relation in terms of the relations in the database without explicitly stating the operations to be performed SQL is based on the relational calculus.

12. 2013-09-19 SLIDE 12IS 257 – Fall 2013 SQL - History Structured Query Language SEQUEL from IBM San Jose ANSI 1992 Standard is the version used by most DBMS today (SQL92) Basic language is standardized across relational DBMSs. Each system may have proprietary extensions to standard.

13. 2013-09-19 SLIDE 13IS 257 – Fall 2013 SQL Uses Database Definition and Querying –Can be used as an interactive query language –Can be imbedded in programs Relational Calculus combines Select, Project and Join operations in a single command: SELECT

14. 2013-09-19 SLIDE 14IS 257 – Fall 2013 SELECT Syntax: –SELECT [DISTINCT] attr1, attr2,…, attr3 FROM rel1 r1, rel2 r2,… rel3 r3 WHERE condition1 {AND | OR} condition2 ORDER BY attr1 [DESC], attr3 [DESC]

15. 2013-09-19 SLIDE 15IS 257 – Fall 2013 Lecture Outline Review –Relational Algebra and Calculus –Introduction to SQL More on SQL – creating and modifying data SQLite3 –Python and SQLite

16. 2013-09-19 SLIDE 16IS 257 – Fall 2013 SELECT Syntax: –SELECT a.author, b.title FROM authors a, bibfile b, au_bib c WHERE a.AU_ID = c.AU_ID and c.accno = b.accno ORDER BY a.author ; Examples in Access...

17. 2013-09-19 SLIDE 17IS 257 – Fall 2013 SELECT Conditions = equal to a particular value >= greater than or equal to a particular value > greater than a particular value <= less than or equal to a particular value <> not equal to a particular value LIKE “*term*” (may be other wild cards in other systems) IN (“opt1”, “opt2”,…,”optn”) BETWEEN val1 AND val2 IS NULL

18. 2013-09-19 SLIDE 18IS 257 – Fall 2013 Relational Algebra Selection using SELECT Syntax: –SELECT * FROM rel1 WHERE condition1 {AND | OR} condition2;

19. 2013-09-19 SLIDE 19IS 257 – Fall 2013 Relational Algebra Projection using SELECT Syntax: –SELECT [DISTINCT] attr1, attr2,…, attr3 FROM rel1 r1, rel2 r2,… rel3 r3;

20. 2013-09-19 SLIDE 20IS 257 – Fall 2013 Relational Algebra Join using SELECT Syntax: –SELECT * FROM rel1 r1, rel2 r2 WHERE r1.linkattr = r2.linkattr ;

21. 2013-09-19 SLIDE 21IS 257 – Fall 2013 Sorting SELECT BIOLIFE.[Common Name], BIOLIFE.[Length (cm)] FROM BIOLIFE ORDER BY BIOLIFE.[Length (cm)] DESC; Note: the square brackets are not part of the standard, But are used in Access for names with embedded blanks

22. 2013-09-19 SLIDE 22IS 257 – Fall 2013 Subqueries SELECT SITES.[Site Name], SITES.[Destination no] FROM SITES WHERE sites.[Destination no] IN (SELECT [Destination no] from DEST where [avg temp (f)] >= 78); Can be used as a form of JOIN.

23. 2013-09-19 SLIDE 23IS 257 – Fall 2013 Aggregate Functions Count Avg SUM MAX MIN Others may be available in different systems

24. 2013-09-19 SLIDE 24IS 257 – Fall 2013 Using Aggregate functions SELECT attr1, Sum(attr2) AS name FROM tab1, tab2... GROUP BY attr1, attr3 HAVING condition;

25. 2013-09-19 SLIDE 25IS 257 – Fall 2013 Using an Aggregate Function SELECT DIVECUST.Name, Sum([Price]*[qty]) AS Total FROM (DIVECUST INNER JOIN DIVEORDS ON DIVECUST.[Customer No] = DIVEORDS.[Customer No]) INNER JOIN DIVEITEM ON DIVEORDS.[Order No] = DIVEITEM.[Order No] GROUP BY DIVECUST.Name HAVING (((DIVECUST.Name) Like "*Jazdzewski"));

26. 2013-09-19 SLIDE 26IS 257 – Fall 2013 GROUP BY SELECT DEST.[Destination Name], Count(*) AS Expr1 FROM DEST INNER JOIN DIVEORDS ON DEST.[Destination Name] = DIVEORDS.Destination GROUP BY DEST.[Destination Name] HAVING ((Count(*))>1); Provides a list of Destinations with the number of orders going to that destination

27. 2013-09-19 SLIDE 27IS 257 – Fall 2013 Lecture Outline Review –Relational Algebra and Calculus –Introduction to SQL More on SQL – creating and modifying data SQLite3 –Python and SQLite

28. 2013-09-19 SLIDE 28IS 257 – Fall 2013 SQL Commands Data Definition Statements –For creation of relations/tables…

29. 2013-09-19 SLIDE 29 Create Table CREATE TABLE table-name (attr1 attr- type PRIMARYKEY, attr2 attr-type,…,attrN attr-type); –Adds a new table with the specified attributes (and types) to the database. In MySQL (5.5+) and SQLite3 –CREATE TABLE newtablename AS SELECT … Creates new table with contents from SELECT command including data types IS 257 – Fall 2013

30. 2013-09-19 SLIDE 30 INSERT INSERT INTO table-name (col1, col2, col3, …, colN) VALUES (val1, val2, val3,…, valN); INSERT INTO table-name (col1, col2, col3, …, colN) SELECT… Column list is optional, if omitted assumes all columns in table definition and order IS 257 – Fall 2013

31. 2013-09-19 SLIDE 31 Database Security Most modern DBMS (like Oracle, MySQL, SQL Server, etc) have extensive options for securing the database –Users have logins and passwords just like for a shared OS –You can control which users can access which data, and whether they can only read or can modify and write the data they have access to SQLite3 lacks all of this – so be careful how you use it… IS 257 – Fall 2013

32. 2013-09-19 SLIDE 32 Database Security Virtually all E-Commerce and many other web sites use a DBMS behind the web interface The way the most web sites get pwned by hackers is by SQL injection attacks How they work: –If a server is not cleaning up input data (say a user registering for the system) –Input additional SQL in the data to do nasty stuff… IS 257 – Fall 2013

33. 2013-09-19 SLIDE 33IS 257 – Fall 2013 Access Data Types (Not MySQL) Numeric (1, 2, 4, 8 bytes, fixed or float) Text (255 max) Memo (64000 max) Date/Time (8 bytes) Currency (8 bytes, 15 digits + 4 digits decimal) Autonumber (4 bytes) Yes/No (1 bit) OLE (limited only by disk space) Hyperlinks (up to 64000 chars)

34. 2013-09-19 SLIDE 34IS 257 – Fall 2013 Access Numeric types Byte –Stores numbers from 0 to 255 (no fractions). 1 byte Integer – Stores numbers from –32,768 to 32,767 (no fractions) 2 bytes Long Integer(Default) –Stores numbers from –2,147,483,648 to 2,147,483,647 (no fractions). 4 bytes Single –Stores numbers from -3.402823E38 to –1.401298E–45 for negative values and from 1.401298E–45 to 3.402823E38 for positive values.4 bytes Double –Stores numbers from –1.79769313486231E308 to – 4.94065645841247E–324 for negative values and from 1.79769313486231E308 to 4.94065645841247E–324 for positive values.158 bytes Replication ID –Globally unique identifier (GUID)N/A16 bytes

35. 2013-09-19 SLIDE 35IS 257 – Fall 2013 Oracle Data Types CHAR (size) -- max 2000 VARCHAR2(size) -- up to 4000 DATE DECIMAL, FLOAT, INTEGER, INTEGER(s), SMALLINT, NUMBER, NUMBER(size,d) –All numbers internally in same format… LONG, LONG RAW, LONG VARCHAR –up to 2 Gb -- only one per table BLOB, CLOB, NCLOB -- up to 4 Gb BFILE -- file pointer to binary OS file

36. 2013-09-19 SLIDE 36IS 257 – Fall 2013 MySQL Data Types MySQL supports all of the standard SQL numeric data types. These types include the exact numeric data types (INTEGER, SMALLINT, DECIMAL, and NUMERIC), as well as the approximate numeric data types (FLOAT, REAL, and DOUBLE PRECISION). The keyword INT is a synonym for INTEGER, and the keyword DEC is a synonym for DECIMAL Numeric (can also be declared as UNSIGNED) –TINYINT (1 byte) –SMALLINT (2 bytes) –MEDIUMINT (3 bytes) –INT (4 bytes) –BIGINT (8 bytes) –NUMERIC or DECIMAL –FLOAT –DOUBLE (or DOUBLE PRECISION)

37. 2013-09-19 SLIDE 37IS 257 – Fall 2013 MySQL Data Types The date and time types for representing temporal values are DATETIME, DATE, TIMESTAMP, TIME, and YEAR. Each temporal type has a range of legal values, as well as a “zero” value that is used when you specify an illegal value that MySQL cannot represent –DATETIME '0000-00-00 00:00:00' –DATE '0000-00-00' –TIMESTAMP (4.1 and up) '0000-00-00 00:00:00' –TIMESTAMP (before 4.1) 00000000000000 –TIME '00:00:00' –YEAR 0000

38. 2013-09-19 SLIDE 38IS 257 – Fall 2013 MySQL Data Types The string types are CHAR, VARCHAR, BINARY, VARBINARY, BLOB, TEXT, ENUM, and SET Maximum length for CHAR is 255 and for VARCHAR is 65,535 VARCHAR uses 1 or 2 bytes for the length For longer things there is BLOB and TEXT

39. 2013-09-19 SLIDE 39IS 257 – Fall 2013 MySQL Data Types A BLOB is a binary large object that can hold a variable amount of data. The four BLOB types are TINYBLOB, BLOB, MEDIUMBLOB, and LONGBLOB. These differ only in the maximum length of the values they can hold The four TEXT types are TINYTEXT, TEXT, MEDIUMTEXT, and LONGTEXT. These correspond to the four BLOB types and have the same maximum lengths and storage requirements TINY=1byte, BLOB and TEXT=2bytes, MEDIUM=3bytes, LONG=4bytes

40. 2013-09-19 SLIDE 40IS 257 – Fall 2013 MySQL Data Types BINARY and VARBINARY are like CHAR and VARCHAR but are intended for binary data of 255 bytes or less ENUM is a list of values that are stored as their addresses in the list –For example, a column specified as ENUM('one', 'two', 'three') can have any of the values shown here. The index of each value is also shown: Value = Index NULL = NULL ‘’ = 0 'one’ = 1 ‘two’ = 2 ‘three’ = 3 –An enumeration can have a maximum of 65,535 elements.

41. 2013-09-19 SLIDE 41IS 257 – Fall 2013 MySQL Data Types The final string type (for this version) is a SET A SET is a string object that can have zero or more values, each of which must be chosen from a list of allowed values specified when the table is created. SET column values that consist of multiple set members are specified with members separated by commas (‘,’) For example, a column specified as SET('one', 'two') NOT NULL can have any of these values: –'' –'one' –'two' –'one,two‘ A set can have up to 64 member values and is stored as an 8byte number

42. 2013-09-19 SLIDE 42IS 257 – Fall 2013 Lecture Outline Review –Relational Algebra and Calculus –Introduction to SQL More on SQL – creating and modifying data SQLite3 –Python and SQLite

43. 2013-09-19 SLIDE 43 SQLite3 Light-weight implementation of a relational DBMS (~340Kb) –Includes most of the features of full DBMS –Intended to be imbedded in programs Available on iSchool servers and for other machines as open source Used as the data manager in iPhone apps and Firefox (among many others) Databases are stored as files in the OS IS 257 – Fall 2013

44. 2013-09-19 SLIDE 44 SQLite3 Data types SQLite uses a more general dynamic type system. In SQLite, the datatype of a value is associated with the value itself, not with its container Types are: –NULL: The value is a NULL value. –INTEGER: The value is a signed integer, stored in 1, 2, 3, 4, 6, or 8 bytes depending on the magnitude of the value –REAL: The value is a floating point value, stored as an 8-byte IEEE floating point number. –TEXT. The value is a text string, stored using the database encoding (UTF-8, UTF-16BE or UTF-16LE). (default max 1,000,000,000 chars) –BLOB. The value is a blob of data, stored exactly as it was input. IS 257 – Fall 2013

45. 2013-09-19 SLIDE 45 SQLite3 Command line [dhcp137:~] ray% sqlite3 test.db SQLite version 3.6.22 Enter ".help" for instructions Enter SQL statements terminated with a ";" sqlite>.tables sqlite> create table stuff (id int, name varchar(30),address varchar(50)); sqlite>.tables stuff sqlite> insert into stuff values (1,'Jane Smith',"123 east st."); sqlite> select * from stuff; 1|Jane Smith|123 east st. sqlite> insert into stuff values (2, 'Bob Jones', '234 west st.'); sqlite> insert into stuff values (3, 'John Smith', '567 North st.'); sqlite> update stuff set address = "546 North st." where id = 1; sqlite> select * from stuff; 1|Jane Smith|546 North st. 2|Bob Jones|234 west st. 3|John Smith|567 North st. IS 257 – Fall 2013

46. 2013-09-19 SLIDE 46 Wildcard searching sqlite> select * from stuff where name like '%Smith%'; 1|Jane Smith|546 North st. 3|John Smith|567 North st. sqlite> select * from stuff where name like 'J%Smith%'; 1|Jane Smith|546 North st. 3|John Smith|567 North st. sqlite> select * from stuff where name like 'Ja%Smith%'; 1|Jane Smith|546 North st. sqlite> select * from stuff where name like 'Jones'; sqlite> select * from stuff where name like '%Jones'; 2|Bob Jones|234 west st. sqlite> select name from stuff...> ; Jane Smith Bob Jones John Smith sqlite> IS 257 – Fall 2013

47. 2013-09-19 SLIDE 47 Create backups sqlite>.dump PRAGMA foreign_keys=OFF; BEGIN TRANSACTION; CREATE TABLE stuff (id int, name varchar(30),address varchar(50)); INSERT INTO "stuff" VALUES(1,'Jane Smith','546 North st.'); INSERT INTO "stuff" VALUES(2,'Bob Jones','234 west st.'); INSERT INTO "stuff" VALUES(3,'John Smith','567 North st.'); COMMIT; sqlite>.schema CREATE TABLE stuff (id int, name varchar(30),address varchar(50)); IS 257 – Fall 2013

48. 2013-09-19 SLIDE 48 Creating Tables from Tables sqlite> create table names as select name, id from stuff; sqlite>.schema CREATE TABLE names(name TEXT,id INT); CREATE TABLE stuff (id int, name varchar(30),address varchar(50)); sqlite> select * from names; Jane Smith|1 Bob Jones|2 John Smith|3 sqlite> create table names2 as select name as xx, id as key from stuff; sqlite>.schema CREATE TABLE names(name TEXT,id INT); CREATE TABLE names2(xx TEXT,"key" INT); CREATE TABLE stuff (id int, name varchar(30),address varchar(50)); sqlite> drop table names2; sqlite>.schema CREATE TABLE names(name TEXT,id INT); CREATE TABLE stuff (id int, name varchar(30),address varchar(50)); IS 257 – Fall 2013

49. 2013-09-19 SLIDE 49 Using SQLite3 from Python SQLite is available as a loadable python library –You can use any SQL commands to create, add data, search, update and delete IS 257 – Fall 2013

50. 2013-09-19 SLIDE 50 SQLite3 from Python [dhcp137:~] ray% python Python 2.5.1 (r251:54869, Apr 18 2007, 22:08:04) [GCC 4.0.1 (Apple Computer, Inc. build 5367)] on darwin Type "help", "copyright", "credits" or "license" for more information. >>> import sqlite3 >>> sqlite3.version '2.3.2’ >>> sqlite3.sqlite_version '3.3.14' >>> IS 257 – Fall 2013

51. 2013-09-19 SLIDE 51 SQLite3 from Python [dhcp137:~] ray% python Python 2.5.1 (r251:54869, Apr 18 2007, 22:08:04) [GCC 4.0.1 (Apple Computer, Inc. build 5367)] on darwin Type "help", "copyright", "credits" or "license" for more information. >>> import sqlite3 as lite >>> import sys >>> con = None >>> try:... con = lite.connect('newtest.db')... cur = con.cursor()... cur.execute('SELECT SQLITE_VERSION()')... data = cur.fetchone()... print "SQLite version: %s" % data... except lite.Error, e:... print "Error %s:" % e.args[0]... sys.exit(1)... finally:... if con:... con.close()... SQLite version: 3.3.14 >>> IS 257 – Fall 2013

52. 2013-09-19 SLIDE 52 SQLite3 from Python #!/usr/bin/python2.7 # -*- coding: utf-8 -*- import sqlite3 as lite import sys # our data is defined as a tuple of tuples… cars = ( (1, 'Audi', 52642), (2, 'Mercedes', 57127), (3, 'Skoda', 9000), (4, 'Volvo', 29000), (5, 'Bentley', 350000), (6, 'Hummer', 41400), (7, 'Volkswagen', 21600) ) con = lite.connect(’newtest.db') with con: cur = con.cursor() cur.execute("DROP TABLE IF EXISTS Cars") cur.execute("CREATE TABLE Cars(Id INT, Name TEXT, Price INT)") cur.executemany("INSERT INTO Cars VALUES(?, ?, ?)", cars) IS 257 – Fall 2013

53. 2013-09-19 SLIDE 53 Another Example #!/usr/bin/python # -*- coding: utf-8 -*- import sqlite3 as lite import sys con = lite.connect(':memory:') with con: cur = con.cursor() cur.execute("CREATE TABLE Friends(Id INTEGER PRIMARY KEY, Name TEXT);") cur.execute("INSERT INTO Friends(Name) VALUES ('Tom');") cur.execute("INSERT INTO Friends(Name) VALUES ('Rebecca');") cur.execute("INSERT INTO Friends(Name) VALUES ('Jim');") cur.execute("INSERT INTO Friends(Name) VALUES ('Robert');") lid = cur.lastrowid print "The last Id of the inserted row is %d" % lid IS 257 – Fall 2013

54. 2013-09-19 SLIDE 54 Retrieving Data #!/usr/bin/python # -*- coding: utf-8 -*- import sqlite3 as lite import sys #connect to the cars database… con = lite.connect(’newtest.db') with con: cur = con.cursor() cur.execute("SELECT * FROM Cars") rows = cur.fetchall() for row in rows: print row ray% python2.7 retrnewtest.py (1, u'Audi', 52642) (2, u'Mercedes', 57127) (3, u'Skoda', 9000) (4, u'Volvo', 29000) (5, u'Bentley', 350000) (6, u'Hummer', 41400) (7, u'Volkswagen', 21600) (8, u'Citroen', 21000) ray% IS 257 – Fall 2013

55. 2013-09-19 SLIDE 55 Updating data cur.execute("UPDATE Cars set Price = 450000 where Name = 'Bentley'") cur.execute("SELECT * FROM Cars") rows = cur.fetchall() for row in rows: print row (1, u'Audi', 52642) (2, u'Mercedes', 57127) (3, u'Skoda', 9000) (4, u'Volvo', 29000) (5, u'Bentley', 450000) (6, u'Hummer', 41400) (7, u'Volkswagen', 21600) (8, u'Citroen', 21000) ray% IS 257 – Fall 2013

56. 2013-09-19 SLIDE 56 Add another row… [dhcp137:~] ray% python2.7 Python 2.7.2 (default, Oct 11 2012, 20:14:37) [GCC 4.2.1 Compatible Apple Clang 4.0 … >>> import sqlite3 as lite >>> import sys >>> >>> con = lite.connect(’newtest.db') >>> >>> with con:... cur = con.cursor()... cur.execute("INSERT INTO Cars VALUES(8,'Citroen',21000)")... >>> IS 257 – Fall 2013

57. 2013-09-19 SLIDE 57 From the SQLite3 command line [dhcp137:~] ray% sqlite3 newtest.db SQLite version 3.6.22 Enter ".help" for instructions Enter SQL statements terminated with a ";" sqlite> select * from cars; 1|Audi|52642 2|Mercedes|57127 3|Skoda|9000 4|Volvo|29000 5|Bentley|350000 6|Hummer|41400 7|Volkswagen|21600 8|Citroen|21000 sqlite> INSERT more data… sqlite> select * from cars; 1|Audi|52642 2|Mercedes|57127 3|Skoda|9000 4|Volvo|29000 5|Bentley|450000 6|Hummer|41400 7|Volkswagen|21600 8|Citroen|21000 10|Audi|51000 11|Mercedes|55000 12|Mercedes|56300 13|Volvo|31500 14|Volvo|31000 15|Audi|52000 17|Hummer|42400 16|Hummer|42400 IS 257 – Fall 2013

58. 2013-09-19 SLIDE 58 Use Aggregates to summarize data #!/usr/bin/python2.7 # -*- coding: utf-8 -*- import sqlite3 as lite import sys con = lite.connect('newtest.db') with con: cur = con.cursor() cur.execute("SELECT Name, AVG(Price) FROM Cars GROUP BY Name") rows = cur.fetchall() for row in rows: print row ray% python2.7 aggnewtest.py (u'Audi', 51880.666666666664) (u'Bentley', 450000.0) (u'Citroen', 21000.0) (u'Hummer', 42066.666666666664) (u'Mercedes', 56142.333333333336) (u'Skoda', 9000.0) (u'Volkswagen', 21600.0) (u'Volvo', 30500.0) IS 257 – Fall 2013

59. 2013-09-19 SLIDE 59 Next week I am away During class sessions Chan & JT will have informal workshops to help you understand and use SQL better and help in designing you conceptual model for your personal DB IS 257 – Fall 2013