9/25/2001SIMS 257: Database Management Physical Database Design University of California, Berkeley School of Information Management and Systems SIMS 257: Database Management

9/25/2001SIMS 257: Database Management Review Database Design Process Normalization

9/25/2001SIMS 257: Database Management Database Design Process Conceptual Model Logical Model External Model Conceptual requirements Conceptual requirements Conceptual requirements Conceptual requirements Application 1 Application 2Application 3Application 4 Application 2 Application 3 Application 4 External Model External Model External Model Internal Model

9/25/2001SIMS 257: Database Management 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.

9/25/2001SIMS 257: Database Management 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)

9/25/2001SIMS 257: Database Management Normalization Boyce- Codd and Higher Functional dependencyof nonkey attributes on the primary key - Atomic values only Full Functional dependencyof nonkey attributes on the primary key No transitive dependency between nonkey attributes All determinants are candidate keys - Single multivalued dependency

9/25/2001SIMS 257: Database Management 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

9/25/2001SIMS 257: Database Management Unnormalized Relation

9/25/2001SIMS 257: Database Management First Normal Form

9/25/2001SIMS 257: Database Management Second Normal Form

9/25/2001SIMS 257: Database Management Second Normal Form

9/25/2001SIMS 257: Database Management Second Normal Form

9/25/2001SIMS 257: Database Management Third Normal Form

9/25/2001SIMS 257: Database Management Third Normal Form

9/25/2001SIMS 257: Database Management Most 3NF Relations are also BCNF

9/25/2001SIMS 257: Database Management 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

9/25/2001SIMS 257: Database Management 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.

9/25/2001SIMS 257: Database Management 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.

9/25/2001SIMS 257: Database Management 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.

9/25/2001SIMS 257: Database Management Downward Denormalization Customer ID Address Name Telephone Customer ID Address Name Telephone Order Order No Date Taken Date Dispatched Date Invoiced Cust ID Order Order No Date Taken Date Dispatched Date Invoiced Cust ID Cust Name Before:After:

9/25/2001SIMS 257: Database Management Upward Denormalization Order Order No Date Taken Date Dispatched Date Invoiced Cust ID Cust Name Order Order No Date Taken Date Dispatched Date Invoiced Cust ID Cust Name Order Price Order Item Order No Item No Item Price Num Ordered Order Item Order No Item No Item Price Num Ordered

9/25/2001SIMS 257: Database Management

9/25/2001SIMS 257: Database Management Today Physical Database Design Access Methods Indexes Based on McFadden Modern Database Management and Atre Database:Structured Techniques for Design, Performance and Management

9/25/2001SIMS 257: Database Management Database Design Process Conceptual Model Logical Model External Model Conceptual requirements Conceptual requirements Conceptual requirements Conceptual requirements Application 1 Application 2Application 3Application 4 Application 2 Application 3 Application 4 External Model External Model External Model Internal Model Physical Design

9/25/2001SIMS 257: Database Management 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

9/25/2001SIMS 257: Database Management 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

9/25/2001SIMS 257: Database Management 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

9/25/2001SIMS 257: Database Management 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

9/25/2001SIMS 257: Database Management 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

9/25/2001SIMS 257: Database Management 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 eliminated illegal values) for the associated attribute and can support the required data manipulations (e.g. numerical or string operations)

9/25/2001SIMS 257: Database Management 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 chars)

9/25/2001SIMS 257: Database Management 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 E38 to – E–45 for negative values and from E–45 to E38 for positive values.4 bytes Double –Stores numbers from – E308 to – E–324 for negative values and from E308 to E–324 for positive values.158 bytes Replication ID –Globally unique identifier (GUID)N/A16 bytes

9/25/2001SIMS 257: Database Management Controlling Data Integrity Default values Range control Null value control Referential integrity Handling missing data

9/25/2001SIMS 257: Database Management 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

9/25/2001SIMS 257: Database Management Designing Physical Files/Internal Model Overview terminology Access methods

9/25/2001SIMS 257: Database Management Physical Design Internal Model/Physical Model Operating System Access Methods Data Base User request DBMS Internal Model Access Methods External Model Interface 1 Interface 3 Interface 2

9/25/2001SIMS 257: Database Management 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.

9/25/2001SIMS 257: Database Management 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

9/25/2001SIMS 257: Database Management Internal Model Access Methods Many types of access methods: –Physical Sequential –Indexed Sequential –Indexed Random –Inverted –Direct –Hashed Differences in –Access Efficiency –Storage Efficiency

9/25/2001SIMS 257: Database Management 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)

9/25/2001SIMS 257: Database Management 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

9/25/2001SIMS 257: Database Management Index Sequential Data File Block 1 Block 2 Block 3 Address Block Number 123…123… Actual Value Dumpling Harty Texaci... Adams Becker Dumpling Getta Harty Mobile Sunoci Texaci

9/25/2001SIMS 257: Database Management Indexed Sequential: Two Levels Address 789…789… Key Value Address 1212 Key Value Address 3434 Key Value Address 5656 Key Value

9/25/2001SIMS 257: Database Management 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

9/25/2001SIMS 257: Database Management Indexed Random Address Block Number Actual Value Adams Becker Dumpling Getta Harty Becker Harty Adams Getta Dumpling

9/25/2001SIMS 257: Database Management Btree F | | P | | Z | R | | S | | Z |H | | L | | P |B | | D | | F | Devils Aces Boilers Cars Minors Panthers Seminoles Flyers Hawkeyes Hoosiers

9/25/2001SIMS 257: Database Management 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

9/25/2001SIMS 257: Database Management Inverted CH145 cs201 ch145 cs623 Address Block Number 123…123… Actual Value CH 145 CS 201 CS 623 PH 345 CH , 103,104 CS CS , 106 Adams Becker Dumpling Getta Harty Mobile Student name Course Number

9/25/2001SIMS 257: Database Management 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

9/25/2001SIMS 257: Database Management 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

9/25/2001SIMS 257: Database Management Comparative Access Methods Factor Storage space Sequential retrieval on primary key Random Retr. Multiple Key Retr. Deleting records Adding records Updating records Sequential No wasted space Very fast Impractical Possible but needs a full scan can create wasted space requires rewriting file usually requires rewriting file Indexed No wasted space for data but extra space for index Moderately Fast Very fast with multiple indexes OK if dynamic OK if dynamic Easy but requires Maintenance of indexes Hashed more space needed for addition and deletion of records after initial load Impractical Very fast Not possible very easy