2013-09-19 SLIDE 1IS 257 – Fall 2013 More on SQL (and SQLite) University of California, Berkeley...
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Transcript of 2013-09-19 SLIDE 1IS 257 – Fall 2013 More on SQL (and SQLite) University of California, Berkeley...
2013-09-19 SLIDE 1IS 257 – Fall 2013
More on SQL (and SQLite)
University of California, Berkeley
School of Information
I 257: Database Management
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
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
2013-09-19 SLIDE 4IS 257 – Fall 2013
Relational Algebra Operations
• Select• Project• Product• Union• Intersect• Difference• Join• Divide
2013-09-19 SLIDE 5IS 257 – Fall 2013
Restrict (Select)
• Extracts specified tuples (rows) from a specified relation (table).
2013-09-19 SLIDE 6IS 257 – Fall 2013
Project
• Extracts specified attributes(columns) from a specified relation.
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 B1A2 B1A3 B2
B1 C1B2 C2B3 C3
A1 B1 C1A2 B1 C1A3 B2 C2
(Naturalor Inner)
Join
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 B1A2 B1A3 B2A4 B7
B1 C1B2 C2B3 C3
A1 B1 C1A2 B1 C1A3 B2 C2A4 * *
Outer Join
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
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.
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.
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
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]
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
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...
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
2013-09-19 SLIDE 18IS 257 – Fall 2013
Relational Algebra Selection using SELECT
• Syntax:– SELECT * FROM rel1 WHERE condition1
{AND | OR} condition2;
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;
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 ;
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
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.
2013-09-19 SLIDE 23IS 257 – Fall 2013
Aggregate Functions
• Count• Avg• SUM• MAX• MIN• Others may be available in different
systems
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;
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"));
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
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
2013-09-19 SLIDE 28IS 257 – Fall 2013
SQL Commands
• Data Definition Statements– For creation of relations/tables…
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
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
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
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
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)
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. 15 8 bytes
• Replication ID– Globally unique identifier (GUID) N/A 16 bytes
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
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)
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
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
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
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.
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
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
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
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
2013-09-19 SLIDE 45
SQLite3 Command line[dhcp137:~] ray% sqlite3 test.dbSQLite version 3.6.22Enter ".help" for instructionsEnter SQL statements terminated with a ";"sqlite> .tablessqlite> create table stuff (id int, name varchar(30),address varchar(50));sqlite> .tablesstuffsqlite> 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
2013-09-19 SLIDE 46
Wildcard searchingsqlite> 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 SmithBob JonesJohn Smithsqlite>
IS 257 – Fall 2013
2013-09-19 SLIDE 47
Create backups
sqlite> .dumpPRAGMA 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> .schemaCREATE TABLE stuff (id int, name varchar(30),address varchar(50));
IS 257 – Fall 2013
2013-09-19 SLIDE 48
Creating Tables from Tablessqlite> create table names as select name, id from stuff;sqlite> .schemaCREATE TABLE names(name TEXT,id INT);CREATE TABLE stuff (id int, name varchar(30),address varchar(50));sqlite> select * from names;Jane Smith|1Bob Jones|2John Smith|3sqlite> create table names2 as select name as xx, id as key from stuff;sqlite> .schemaCREATE 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> .schemaCREATE TABLE names(name TEXT,id INT);CREATE TABLE stuff (id int, name varchar(30),address varchar(50));
IS 257 – Fall 2013
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
2013-09-19 SLIDE 50
SQLite3 from Python[dhcp137:~] ray% pythonPython 2.5.1 (r251:54869, Apr 18 2007, 22:08:04) [GCC 4.0.1 (Apple Computer, Inc. build 5367)] on darwinType "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
2013-09-19 SLIDE 51
SQLite3 from Python[dhcp137:~] ray% pythonPython 2.5.1 (r251:54869, Apr 18 2007, 22:08:04) [GCC 4.0.1 (Apple Computer, Inc. build 5367)] on darwinType "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()... <sqlite3.Cursor object at 0x46eb90>SQLite version: 3.3.14>>> IS 257 – Fall 2013
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
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
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
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
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)")... <sqlite3.Cursor object at 0x107fafc00>>>>
IS 257 – Fall 2013
2013-09-19 SLIDE 57
From the SQLite3 command line[dhcp137:~] ray% sqlite3 newtest.dbSQLite version 3.6.22Enter ".help" for instructionsEnter SQL statements terminated with a ";"sqlite> select * from cars;1|Audi|526422|Mercedes|571273|Skoda|90004|Volvo|290005|Bentley|3500006|Hummer|414007|Volkswagen|216008|Citroen|21000sqlite>
INSERT more data…sqlite> select * from cars;1|Audi|526422|Mercedes|571273|Skoda|90004|Volvo|290005|Bentley|4500006|Hummer|414007|Volkswagen|216008|Citroen|2100010|Audi|5100011|Mercedes|5500012|Mercedes|5630013|Volvo|3150014|Volvo|3100015|Audi|5200017|Hummer|4240016|Hummer|42400
IS 257 – Fall 2013
2013-09-19 SLIDE 58
Use Aggregates to summarize data
#!/usr/bin/python2.7# -*- coding: utf-8 -*-import sqlite3 as liteimport 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