Physical Database Design University of California Berkeley School
Physical Database Design University of California, Berkeley School of Information Management and Systems SIMS 202: Information Organization and Retrieval IS 257 - Fall 2002. 10. 01 - SLIDE 1
Lecture Outline • Review – Normalization • Physical Database Design • Access Methods IS 257 - Fall 2002. 10. 01 - SLIDE 2
Lecture Outline • Review – Normalization • Physical Database Design • Access Methods IS 257 - Fall 2002. 10. 01 - SLIDE 3
Database Design Process Application 1 External Model Application 2 Application 3 Application 4 External Model Application 1 Conceptual requirements Application 2 Conceptual requirements Application 3 Conceptual requirements Conceptual Model Logical Model Internal Model Application 4 Conceptual requirements IS 257 - Fall 2002. 10. 01 - SLIDE 4
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. IS 257 - Fall 2002. 10. 01 - SLIDE 5
Normal Forms • • • First Normal Form (1 NF) Second Normal Form (2 NF) Third Normal Form (3 NF) Boyce-Codd Normal Form (BCNF) Fourth Normal Form (4 NF) Fifth Normal Form (5 NF) IS 257 - Fall 2002. 10. 01 - SLIDE 6
Normalization No transitive dependency between nonkey attributes All determinants are candidate keys - Single multivalued dependency IS 257 - Fall 2002 Boyce. Codd and Higher Functional dependency of nonkey attributes on the primary key - Atomic values only Full Functional dependency of nonkey attributes on the primary key 2002. 10. 01 - SLIDE 7
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 IS 257 - Fall 2002. 10. 01 - SLIDE 8
Unnormalized Relation IS 257 - Fall 2002. 10. 01 - SLIDE 9
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. IS 257 - Fall 2002. 10. 01 - SLIDE 10
First Normal Form IS 257 - Fall 2002. 10. 01 - SLIDE 11
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 IS 257 - Fall 2002. 10. 01 - SLIDE 12
Second Normal Form IS 257 - Fall 2002. 10. 01 - SLIDE 13
Second Normal Form IS 257 - Fall 2002. 10. 01 - SLIDE 14
Second Normal Form IS 257 - Fall 2002. 10. 01 - SLIDE 15
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 3 NF IS 257 - Fall 2002. 10. 01 - SLIDE 16
Third Normal Form IS 257 - Fall 2002. 10. 01 - SLIDE 17
Third Normal Form IS 257 - Fall 2002. 10. 01 - SLIDE 18
Boyce-Codd Normal Form • Most 3 NF relations are also BCNF relations. • A 3 NF 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 IS 257 - Fall 2002. 10. 01 - SLIDE 19
BCNF Relations IS 257 - Fall 2002. 10. 01 - SLIDE 20
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 IS 257 - Fall 2002. 10. 01 - SLIDE 21
Fifth Normal Form • A relation is in 5 NF 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. IS 257 - Fall 2002. 10. 01 - SLIDE 22
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. IS 257 - Fall 2002. 10. 01 - SLIDE 23
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. IS 257 - Fall 2002. 10. 01 - SLIDE 24
Downward Denormalization Customer ID Address Name Telephone Before: Order No Date Taken Date Dispatched Date Invoiced Cust ID IS 257 - Fall 2002 After: Customer ID Address Name Telephone Order No Date Taken Date Dispatched Date Invoiced Cust ID Cust Name 2002. 10. 01 - SLIDE 25
Upward Denormalization Order No Date Taken Date Dispatched Date Invoiced Cust ID Cust Name Order Item Order No Item Price Num Ordered IS 257 - Fall 2002 Order No Date Taken Date Dispatched Date Invoiced Cust ID Cust Name Order Price Order Item Order No Item Price Num Ordered 2002. 10. 01 - SLIDE 26
Lecture Outline • Review – Normalization • Physical Database Design • Access Methods IS 257 - Fall 2002. 10. 01 - SLIDE 27
Database Design Process Application 1 External Model Application 2 Application 3 Application 4 External Model Application 1 Conceptual requirements Application 2 Conceptual requirements Application 3 Conceptual requirements Conceptual Model Logical Model Internal Model Application 4 Conceptual requirements IS 257 - Fall 2002 Physical Design 2002. 10. 01 - SLIDE 28
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 IS 257 - Fall 2002. 10. 01 - SLIDE 29
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 IS 257 - Fall 2002. 10. 01 - SLIDE 30
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 IS 257 - Fall 2002. 10. 01 - SLIDE 31
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 IS 257 - Fall 2002. 10. 01 - SLIDE 32
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 IS 257 - Fall 2002. 10. 01 - SLIDE 33
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) IS 257 - Fall 2002. 10. 01 - SLIDE 34
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) IS 257 - Fall 2002. 10. 01 - SLIDE 35
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. 402823 E 38 to – 1. 401298 E– 45 for negative values and from 1. 401298 E– 45 to 3. 402823 E 38 for positive values. 4 bytes • Double – Stores numbers from – 1. 79769313486231 E 308 to – 4. 94065645841247 E– 324 for negative values and from 1. 79769313486231 E 308 to 4. 94065645841247 E– 324 for positive values. 15 8 bytes • Replication ID – Globally unique identifier (GUID) IS 257 - Fall 2002 N/A 16 bytes 2002. 10. 01 - SLIDE 36
Controlling Data Integrity • • • Default values Range control Null value control Referential integrity Handling missing data IS 257 - Fall 2002. 10. 01 - SLIDE 37
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 IS 257 - Fall 2002. 10. 01 - SLIDE 38
Designing Physical/Internal Model • Overview • terminology • Access methods IS 257 - Fall 2002. 10. 01 - SLIDE 39
Physical Design • Internal Model/Physical Model User request Interface 1 External Model DBMS Internal Model Access Methods Interface 2 Operating System Access Methods Interface 3 Data Base IS 257 - Fall 2002. 10. 01 - SLIDE 40
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. IS 257 - Fall 2002. 10. 01 - SLIDE 41
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 IS 257 - Fall 2002. 10. 01 - SLIDE 42
Internal Model Access Methods • Many types of access methods: – Physical Sequential – Indexed Random – Inverted – Direct – Hashed • Differences in – Access Efficiency – Storage Efficiency IS 257 - Fall 2002. 10. 01 - SLIDE 43
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) IS 257 - Fall 2002. 10. 01 - SLIDE 44
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 IS 257 - Fall 2002. 10. 01 - SLIDE 45
Index Sequential Data File Actual Value IS 257 - Fall 2002 Address Block Number Dumpling 1 Harty 2 Texaci 3 . . . … Adams Becker Dumpling Block 1 Getta Harty Block 2 Mobile Sunoci Texaci Block 3 2002. 10. 01 - SLIDE 46
Indexed Sequential: Two Levels Key Value Address 150 1 385 2 001 003. . 150 Address 385 7 678 8 805 9 … Key Value Address 536 3 678 4 Key Value 251. . 385 455 480. . 536 605 610. . 678 Address 785 5 805 6 791. . 805 IS 257 - Fall 2002 705 710. . 785 2002. 10. 01 - SLIDE 47
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 IS 257 - Fall 2002. 10. 01 - SLIDE 48
Indexed Random Becker Harty Actual Value Address Block Number Adams 2 Becker 1 Dumpling 3 Getta 2 Harty 1 Adams Getta Dumpling IS 257 - Fall 2002. 10. 01 - SLIDE 49
Btree F B || D || F| || P || Z| H || L || P| R || S || Z| Devils Aces Boilers Cars IS 257 - Fall 2002 Flyers Hawkeyes Hoosiers Minors Panthers Seminoles 2002. 10. 01 - SLIDE 50
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 IS 257 - Fall 2002. 10. 01 - SLIDE 51
Inverted CH 145 101, 103, 104 Actual Value Address Block Number CH 145 1 CS 201 2 CS 623 3 PH 345 … CS 201 102 Student name Course Number Adams CH 145 Becker cs 201 Dumpling ch 145 Getta ch 145 Harty cs 623 Mobile cs 623 CS 623 105, 106 IS 257 - Fall 2002. 10. 01 - SLIDE 52
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 IS 257 - Fall 2002. 10. 01 - SLIDE 53
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 IS 257 - Fall 2002. 10. 01 - SLIDE 54
Comparative Access Methods Factor Storage space Sequential retrieval on primary key Random Retr. Multiple Key Retr. Deleting records Sequential No wasted space Indexed Hashed No wasted space for data but extra space for index more space needed for addition and deletion of records after initial load Very fast Moderately Fast Impractical Moderately Fast Very fast with multiple indexes OK if dynamic Very fast OK if dynamic very easy Easy but requires Maintenance of indexes very easy Impractical Possible but needs a full scan create wasted space Adding records requires rewriting file Updating records usually requires rewriting file IS 257 - Fall 2002 Not possible very easy 2002. 10. 01 - SLIDE 55
Next Time • Indexes and when to index • Integrity Constraints • Referential Integrity IS 257 - Fall 2002. 10. 01 - SLIDE 56
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