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2013-10-01 SLIDE 1IS 257 – Fall 2013
Physical Database Design
University of California, Berkeley
School of Information
I 257: Database Management
2013-10-01 SLIDE 2IS 257 – Fall 2013
Lecture Outline
• Review–Introduction to SQL–SQLite
• Physical Database Design• Access Methods
2013-10-01 SLIDE 3IS 257 – Fall 2013
Lecture Outline
• Review–Introduction to SQL–SQLite
• Physical Database Design• Access Methods
2013-10-01 SLIDE 4IS 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.
2013-10-01 SLIDE 5IS 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
2013-10-01 SLIDE 6IS 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]
2013-10-01 SLIDE 7IS 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...
2013-10-01 SLIDE 8IS 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
2013-10-01 SLIDE 9IS 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"));
2013-10-01 SLIDE 10IS 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
2013-10-01 SLIDE 11IS 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.
2013-10-01 SLIDE 12IS 257 – Fall 2013
Aggregate Functions
• Count• Avg• SUM• MAX• MIN• Others may be available in different
systems
2013-10-01 SLIDE 13IS 257 – Fall 2013
Using Aggregate functions
• SELECT attr1, Sum(attr2) AS name FROM tab1, tab2 ...
GROUP BY attr1, attr3 HAVING condition;
2013-10-01 SLIDE 14IS 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
2013-10-01 SLIDE 15IS 257 – Fall 2013
SQL Commands
• Data Definition Statements– For creation of relations/tables…
2013-10-01 SLIDE 16IS 257 – Fall 2013
Create Table
• CREATE TABLE table-name (attr1 attr-type PRIMARY KEY, attr2 attr-type,…,attrN attr-type);
• Adds a new table with the specified attributes (and types) to the database.
2013-10-01 SLIDE 17
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
2013-10-01 SLIDE 18IS 257 – Fall 2013
Creating a new table from existing tables
• Access and PostgreSQL Syntax:
SELECT [DISTINCT] attr1, attr2,…, attr3 INTO newtablename FROM rel1 r1, rel2 r2,… rel3 r3 WHERE condition1 {AND | OR} condition2 ORDER BY attr1 [DESC], attr3 [DESC]
2013-10-01 SLIDE 19IS 257 – Fall 2013
How to do it in MySQLmysql> SELECT * FROM foo;+---+| n |+---+| 1 |+---+
mysql> CREATE TABLE bar (m INT) SELECT n FROM foo;Query OK, 1 row affected (0.02 sec)Records: 1 Duplicates: 0 Warnings: 0
mysql> SELECT * FROM bar;+------+---+| m | n |+------+---+| NULL | 1 |+------+---+
2013-10-01 SLIDE 20
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
2013-10-01 SLIDE 21
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
2013-10-01 SLIDE 22
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
2013-10-01 SLIDE 23
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
2013-10-01 SLIDE 24
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
2013-10-01 SLIDE 25
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
2013-10-01 SLIDE 26
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
2013-10-01 SLIDE 27
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
2013-10-01 SLIDE 28
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
2013-10-01 SLIDE 29
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
2013-10-01 SLIDE 30
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
2013-10-01 SLIDE 31
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
2013-10-01 SLIDE 32
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
2013-10-01 SLIDE 33
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
2013-10-01 SLIDE 34
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
2013-10-01 SLIDE 35
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
2013-10-01 SLIDE 36IS 257 – Fall 2013
Database Design Process
ConceptualModel
LogicalModel
External Model
Conceptual requirements
Conceptual requirements
Conceptual requirements
Conceptual requirements
Application 1
Application 1
Application 2 Application 3 Application 4
Application 2
Application 3
Application 4
External Model
External Model
External Model
Internal Model
PhysicalDesign
2013-10-01 SLIDE 37IS 257 – Fall 2013
Physical Database Design
• Many physical database design decisions are implicit in the technology adopted– Also, organizations may have standards or an
“information architecture” that specifies operating systems, DBMS, and data access languages -- thus constraining the range of possible physical implementations.
• We will be concerned with some of the possible physical implementation issues
2013-10-01 SLIDE 38IS 257 – Fall 2013
Physical Database Design
• The primary goal of physical database design is data processing efficiency
• We will concentrate on choices often available to optimize performance of database services
• Physical Database Design requires information gathered during earlier stages of the design process
2013-10-01 SLIDE 39IS 257 – Fall 2013
Physical Design Information
• Information needed for physical file and database design includes:– Normalized relations plus size estimates for them– Definitions of each attribute– Descriptions of where and when data are used
• entered, retrieved, deleted, updated, and how often
– Expectations and requirements for response time, and data security, backup, recovery, retention and integrity
– Descriptions of the technologies used to implement the database
2013-10-01 SLIDE 40IS 257 – Fall 2013
Physical Design Decisions
• There are several critical decisions that will affect the integrity and performance of the system– Storage Format– Physical record composition– Data arrangement– Indexes– Query optimization and performance tuning
2013-10-01 SLIDE 41IS 257 – Fall 2013
Storage Format
• Choosing the storage format of each field (attribute). The DBMS provides some set of data types that can be used for the physical storage of fields in the database
• Data Type (format) is chosen to minimize storage space and maximize data integrity
2013-10-01 SLIDE 42IS 257 – Fall 2013
Objectives of data type selection
• Minimize storage space• Represent all possible values• Improve data integrity• Support all data manipulations• The correct data type should, in minimal
space, represent every possible value (but eliminate illegal values) for the associated attribute and can support the required data manipulations (e.g. numerical or string operations)
2013-10-01 SLIDE 43IS 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)
2013-10-01 SLIDE 44IS 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
2013-10-01 SLIDE 45IS 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
2013-10-01 SLIDE 46IS 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)
2013-10-01 SLIDE 47IS 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
2013-10-01 SLIDE 48IS 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
2013-10-01 SLIDE 49IS 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
2013-10-01 SLIDE 50IS 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.
2013-10-01 SLIDE 51IS 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
2013-10-01 SLIDE 52IS 257 – Fall 2013
Controlling Data Integrity
• Default values• Range control• Null value control• Referential integrity (next time)• Handling missing data
2013-10-01 SLIDE 53IS 257 – Fall 2013
Designing Physical Records
• A physical record is a group of fields stored in adjacent memory locations and retrieved together as a unit
• Fixed Length and variable fields
2013-10-01 SLIDE 54IS 257 – Fall 2013
Designing Physical/Internal Model
• Overview• terminology• Access methods
2013-10-01 SLIDE 55IS 257 – Fall 2013
Physical Design
• Internal Model/Physical Model
OperatingSystem
Access Methods
DataBase
User request
DBMSInternal ModelAccess Methods
External Model
Interface 1
Interface 3
Interface 2
2013-10-01 SLIDE 56IS 257 – Fall 2013
Physical Design
• Interface 1: User request to the DBMS. The user presents a query, the DBMS determines which physical DBs are needed to resolve the query
• Interface 2: The DBMS uses an internal model access method to access the data stored in a logical database.
• Interface 3: The internal model access methods and OS access methods access the physical records of the database.
2013-10-01 SLIDE 57IS 257 – Fall 2013
Physical File Design
• A Physical file is a portion of secondary storage (disk space) allocated for the purpose of storing physical records
• Pointers - a field of data that can be used to locate a related field or record of data
• Access Methods - An operating system algorithm for storing and locating data in secondary storage
• Pages - The amount of data read or written in one disk input or output operation
2013-10-01 SLIDE 58IS 257 – Fall 2013
Lecture Outline
• Review–Relational Algebra and Calculus–Introduction to SQL
• Physical Database Design• Access Methods
2013-10-01 SLIDE 59IS 257 – Fall 2013
Internal Model Access Methods
• Many types of access methods:– Physical Sequential– Indexed Sequential– Indexed Random– Inverted– Direct– Hashed
• Differences in – Access Efficiency– Storage Efficiency
2013-10-01 SLIDE 60IS 257 – Fall 2013
Physical Sequential
• Key values of the physical records are in logical sequence
• Main use is for “dump” and “restore”• Access method may be used for storage
as well as retrieval• Storage Efficiency is near 100%• Access Efficiency is poor (unless fixed
size physical records)
2013-10-01 SLIDE 61IS 257 – Fall 2013
Indexed Sequential
• Key values of the physical records are in logical sequence
• Access method may be used for storage and retrieval
• Index of key values is maintained with entries for the highest key values per block(s)
• Access Efficiency depends on the levels of index, storage allocated for index, number of database records, and amount of overflow
• Storage Efficiency depends on size of index and volatility of database
2013-10-01 SLIDE 62IS 257 – Fall 2013
Index Sequential
Data File
Block 1
Block 2
Block 3
AddressBlockNumber
1
2
3
…
ActualValue
Dumpling
Harty
Texaci
...
AdamsBecker
Dumpling
GettaHarty
MobileSunociTexaci
2013-10-01 SLIDE 63IS 257 – Fall 2013
Indexed Sequential: Two Levels
Address
7
8
9
…
Key Value
385
678
805
001003
.
.150
705710
.
.785
251..
385
455480
.
.536
605610
.
.678
791..
805
Address
1
2
Key Value
150
385
Address
3
4
Key Value
536
678
Address
5
6
Key Value
785
805
2013-10-01 SLIDE 64IS 257 – Fall 2013
Indexed Random
• Key values of the physical records are not necessarily in logical sequence
• Index may be stored and accessed with Indexed Sequential Access Method
• Index has an entry for every data base record. These are in ascending order. The index keys are in logical sequence. Database records are not necessarily in ascending sequence.
• Access method may be used for storage and retrieval
2013-10-01 SLIDE 65IS 257 – Fall 2013
Indexed Random
AddressBlockNumber
2
1
3
2
1
ActualValue
Adams
Becker
Dumpling
Getta
Harty
BeckerHarty
AdamsGetta
Dumpling
2013-10-01 SLIDE 66IS 257 – Fall 2013
Btree
F | | P | | Z |
R | | S | | Z |H | | L | | P |B | | D | | F |
Devils
AcesBoilersCars
MinorsPanthers
Seminoles
Flyers
HawkeyesHoosiers
2013-10-01 SLIDE 67IS 257 – Fall 2013
Inverted
• Key values of the physical records are not necessarily in logical sequence
• Access Method is better used for retrieval• An index for every field to be inverted may
be built• Access efficiency depends on number of
database records, levels of index, and storage allocated for index
2013-10-01 SLIDE 68IS 257 – Fall 2013
Inverted
AddressBlockNumber
1
2
3
…
ActualValue
CH 145
CS 201
CS 623
PH 345
CH 145101, 103,104
CS 201102
CS 623
105, 106
Adams
Becker
Dumpling
Getta
Harty
Mobile
Studentname
CourseNumber
CH145
cs201
ch145
ch145
cs623
cs623
2013-10-01 SLIDE 69IS 257 – Fall 2013
Direct
• Key values of the physical records are not necessarily in logical sequence
• There is a one-to-one correspondence between a record key and the physical address of the record
• May be used for storage and retrieval• Access efficiency always 1• Storage efficiency depends on density of
keys• No duplicate keys permitted
2013-10-01 SLIDE 70IS 257 – Fall 2013
Hashing
• Key values of the physical records are not necessarily in logical sequence
• Many key values may share the same physical address (block)
• May be used for storage and retrieval• Access efficiency depends on distribution of
keys, algorithm for key transformation and space allocated
• Storage efficiency depends on distibution of keys and algorithm used for key transformation
2013-10-01 SLIDE 71IS 257 – Fall 2013
Comparative Access Methods
IndexedNo wasted space for databut extra space for index
Moderately Fast
Moderately FastVery fast with multiple indexesOK if dynamic OK if dynamic
Easy but requiresMaintenance ofindexes
FactorStorage spaceSequential retrieval on primary keyRandom Retr.Multiple Key Retr.Deleting records
Adding records
Updating records
SequentialNo wasted space
Very fast
ImpracticalPossible but needsa full scancan create wasted spacerequires rewriting fileusually requires rewriting file
Hashedmore space needed foraddition and deletion ofrecords after initial load
Impractical
Very fast
Not possiblevery easy
very easy
very easy