Physical Database Design

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Physical Database Design

• University of California, Berkeley
• School of Information
• IS 257 Database Management

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Lecture Outline

• Review
• Normalization
• Physical Database Design
• Access Methods

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Lecture Outline

• Review
• Normalization
• Physical Database Design
• Access Methods

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Database Design Process
Application 1
Application 2
Application 3
Application 4
External Model
External Model
External Model
External Model
Application 1
Conceptual requirements
Application 2
Conceptual Model
Logical Model
Conceptual requirements
Internal Model
Application 3
Conceptual requirements
Application 4
Conceptual requirements
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Normalization

• Normalization theory is based on the observation
  that relations with certain properties are more
  effective in inserting, updating and deleting
  data than other sets of relations containing the
  same data
• Normalization is a multi-step process beginning
  with an unnormalized relation
• Hospital example from Atre, S. Data Base
  Structured Techniques for Design, Performance,
  and Management.

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Normal Forms

• First Normal Form (1NF)
• Second Normal Form (2NF)
• Third Normal Form (3NF)
• Boyce-Codd Normal Form (BCNF)
• Fourth Normal Form (4NF)
• Fifth Normal Form (5NF)

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Normalization
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Unnormalized Relations

• First step in normalization is to convert the
  data into a two-dimensional table
• In unnormalized relations data can repeat within
  a column

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Unnormalized Relation
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First Normal Form

• To move to First Normal Form a relation must
  contain only atomic values at each row and
  column.
• No repeating groups
• A column or set of columns is called a Candidate
  Key when its values can uniquely identify the row
  in the relation.

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First Normal Form
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Second Normal Form

• A relation is said to be in Second Normal Form
  when every nonkey attribute is fully functionally
  dependent on the primary key.
• That is, every nonkey attribute needs the full
  primary key for unique identification

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Second Normal Form
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Second Normal Form
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Second Normal Form
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Third Normal Form

• A relation is said to be in Third Normal Form if
  there is no transitive functional dependency
  between nonkey attributes
• When one nonkey attribute can be determined with
  one or more nonkey attributes there is said to be
  a transitive functional dependency.
• The side effect column in the Surgery table is
  determined by the drug administered
• Side effect is transitively functionally
  dependent on drug so Surgery is not 3NF

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Third Normal Form
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Third Normal Form
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Boyce-Codd Normal Form

• Most 3NF relations are also BCNF relations.
• A 3NF relation is NOT in BCNF if
• Candidate keys in the relation are composite keys
  (they are not single attributes)
• There is more than one candidate key in the
  relation, and
• The keys are not disjoint, that is, some
  attributes in the keys are common

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BCNF Relations
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Fourth Normal Form

• Any relation is in Fourth Normal Form if it is
  BCNF and any multivalued dependencies are trivial
• Eliminate non-trivial multivalued dependencies by
  projecting into simpler tables

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Fifth Normal Form

• A relation is in 5NF if every join dependency in
  the relation is implied by the keys of the
  relation
• Implies that relations that have been decomposed
  in previous NF can be recombined via natural
  joins to recreate the original relation.

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Normalization

• Normalization is performed to reduce or eliminate
  Insertion, Deletion or Update anomalies.
• However, a completely normalized database may not
  be the most efficient or effective
  implementation.
• Denormalization is sometimes used to improve
  efficiency.

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Denormalization

• Usually driven by the need to improve query speed
• Query speed is improved at the expense of more
  complex or problematic DML (Data manipulation
  language) for updates, deletions and insertions.

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Downward Denormalization
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Upward Denormalization
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Using RDBMS to help normalize

• Example database Cookie
• Database of books, libraries, publisher and
  holding information for a shared (union) catalog

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Cookie relationships
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Cookie BIBFILE relation
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How to Normalize?

• Currently no way to have multiple authors for a
  given book, and there is duplicate data spread
  over the BIBFILE table
• Can we use the DBMS to help us normalize?
• Access example

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Lecture Outline

• Review
• Normalization
• Using Relational DBs in normalization
• Physical Database Design
• Access Methods

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Database Design Process
Application 1
Application 2
Application 3
Application 4
External Model
External Model
External Model
External Model
Application 1
Conceptual requirements
Application 2
Conceptual Model
Logical Model
Conceptual requirements
Internal Model
Application 3
Conceptual requirements
Application 4
Conceptual requirements
PhysicalDesign
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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

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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

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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

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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

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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

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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)

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Access Data Types

• 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)

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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 1.401298E45
  for negative values and from 1.401298E45 to
  3.402823E38 for positive values. 4 bytes
• Double
• Stores numbers from 1.79769313486231E308 to
  4.94065645841247E324 for negative values and
  from 1.79769313486231E308 to 4.94065645841247E324
  for positive values. 15 8 bytes
• Replication ID
• Globally unique identifier (GUID) N/A 16 bytes

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Controlling Data Integrity

• Default values
• Range control
• Null value control
• Referential integrity (next time)
• Handling missing data

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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

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Designing Physical/Internal Model

• Overview
• terminology
• Access methods

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Physical Design

• Internal Model/Physical Model

User request
Interface 1
Interface 2
Operating System Access Methods
Interface 3
Data Base
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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.

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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

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Internal Model Access Methods

• Many types of access methods
• Physical Sequential
• Indexed Sequential
• Indexed Random
• Inverted
• Direct
• Hashed
• Differences in
• Access Efficiency
• Storage Efficiency

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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)

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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

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Index Sequential
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Indexed Sequential Two Levels
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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

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Indexed Random
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Btree
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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

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Inverted
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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

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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

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Comparative Access Methods
Indexed No wasted space for data but extra space
for index Moderately Fast Moderately Fast Very
fast with multiple indexes OK if dynamic OK if
dynamic Easy but requires Maintenance of indexes
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Database Creation in Access

• Simplest to use a design view
• wizards are available, but less flexible
• Need to watch the default values
• Helps to know what the primary key is, or if one
  is to be created automatically
• Automatic creation is more complex in other RDBMS
  and ORDBMS
• Need to make decision about the physical storage
  of the data

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Database Creation in Access

• Some Simple Examples

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Next Time

• Indexes and when to index
• Integrity Constraints
• Referential Integrity