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Physical Database Design University of California, Berkeley School of Information Management and Systems SIMS 257: Database Management IS 257 – Spring 2004 2004-02-10 SLIDE 1 Lecture Outline • Review – Normalization • Physical Database Design • Access Methods IS 257 – Spring 2004 2004-02-10 SLIDE 2 Lecture Outline • Review – Normalization • Physical Database Design • Access Methods IS 257 – Spring 2004 2004-02-10 SLIDE 3 Database Design Process Application 1 External Model Application 2 Application 3 Application 4 External Model External Model 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 – Spring 2004 2004-02-10 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 – Spring 2004 2004-02-10 SLIDE 5 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) IS 257 – Spring 2004 2004-02-10 SLIDE 6 Normalization No transitive dependency between nonkey attributes All determinants are candidate keys - Single multivalued dependency IS 257 – Spring 2004 BoyceCodd and Higher Functional dependency of nonkey attributes on the primary key - Atomic values only Full Functional dependency of nonkey attributes on the primary key 2004-02-10 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 – Spring 2004 2004-02-10 SLIDE 8 Unnormalized Relation Patient # Surgeon # 145 1111 311 Surg. date Patient Name Jan 1, 1995; June 12, 1995 John White Patient Addr Surgeon 15 New St. New York, NY 243 1234 467 2345 189 Jan 8, 1996 Charles Brown 4876 145 Nov 5, 1995 Hal Kane 5123 145 May 10, 1995 Paul Kosher Charles Field 10 Main St. Patricia Rye, NY Gold Dogwood Lane Harrison, David NY Rosen 55 Boston Post Road, Chester, CN Beth Little Blind Brook Mamaronec k, NY Beth Little 6845 243 Apr 5, 1994 Dec 15, 1984 Ann Hood Hilton Road Larchmont, Charles NY Field IS 257 – Spring 2004 Postop drug Drug side effects Gallstone s removal; Beth Little Kidney Michael stones Penicillin, Diamond removal none- Apr 5, 1994 May 10, 1995 Mary Jones Surgery rash none Eye Cataract removal Thrombos Tetracyclin Fever is removal e none none Open Heart Surgery Cholecyst ectomy Gallstone s Removal Eye Cornea Replacem ent Eye cataract removal Cephalosp orin none Demicillin none none none Tetracyclin e Fever 2004-02-10 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 – Spring 2004 2004-02-10 SLIDE 10 First Normal Form Patient # Surgeon # Surgery DatePatient Name Patient Addr Surgeon Name 1111 145 01-Jan-95 John White 1111 311 12-Jun-95 John White 15 New St. New York, NY 15 New St. New York, NY 1234 243 05-Apr-94 Mary Jones 10 Main St. Rye, NY 1234 467 10-May-95 Mary Jones 2345 4876 5123 6845 6845 189 145 145 243 243 IS 257 – Spring 2004 Charles 08-Jan-96 Brown 10 Main St. Rye, NY Dogwood Lane Harrison, NY 05-Nov-95 Hal Kane 55 Boston Post Road, Chester, CN 05-Apr-94 Ann Hood 15-Dec-84 Ann Hood Hilton Road Larchmont, NY Drug adminSide Effects Charles Field Gallstone s removal Kidney stones removal Eye Cataract removal Patricia Gold Thrombos is removal none none David Rosen Open Heart Surgery none Beth Little Cholecyst ectomy Demicillin Beth Little Michael Diamond Blind Brook Mamaronec 10-May-95 Paul Kosher k, NY Beth Little Hilton Road Larchmont, NY Surgery Penicillin rash none none Tetracyclin e Fever Cephalosp orin Charles Field Gallstone s Removal none Eye Cornea Replacem Tetracyclin ent e Charles Field Eye cataract removal none none none Fever none 2004-02-10 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 – Spring 2004 2004-02-10 SLIDE 12 Second Normal Form Patient # 1111 1234 2345 4876 5123 6845 IS 257 – Spring 2004 Patient Name Patient Address 15 New St. New John White York, NY 10 Main St. Rye, Mary Jones NY Charles Dogwood Lane Brown Harrison, NY 55 Boston Post Hal Kane Road, Chester, Blind Brook Paul Kosher Mamaroneck, NY Hilton Road Ann Hood Larchmont, NY 2004-02-10 SLIDE 13 Second Normal Form Surgeon # Surgeon Name 145 Beth Little 189 David Rosen 243 Charles Field 311 Michael Diamond 467 Patricia Gold IS 257 – Spring 2004 2004-02-10 SLIDE 14 Second Normal Form Patient # Surgeon # Surgery Date 1111 1111 1234 1234 2345 4876 Drug Admin Side Effects 145 Gallstones 01-Jan-95 removal Kidney Penicillin rash 311 stones 12-Jun-95 removal none none 243 Eye Cataract 05-Apr-94 removal Tetracycline Fever 467 Thrombosis 10-May-95 removal 189 Open Heart 08-Jan-96 Surgery Cephalospori n none 145 Cholecystect 05-Nov-95 omy Demicillin none none none none none 5123 145 6845 243 6845 243 IS 257 – Spring 2004 Surgery Gallstones 10-May-95 Removal Eye cataract 15-Dec-84 removal Eye Cornea 05-Apr-94 Replacement none none Tetracycline Fever 2004-02-10 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 3NF IS 257 – Spring 2004 2004-02-10 SLIDE 16 Third Normal Form Patient # Surgeon # Surgery Date Surgery Drug Admin 1111 145 1111 311 01-Jan-95 Gallstones removal Kidney stones 12-Jun-95 removal 1234 243 05-Apr-94 Eye Cataract removal Tetracycline 1234 467 10-May-95 Thrombosis removal 2345 189 08-Jan-96 Open Heart Surgery Cephalosporin 4876 145 05-Nov-95 Cholecystectomy Demicillin 5123 145 10-May-95 Gallstones Removal none 6845 243 none 6845 243 15-Dec-84 Eye cataract removal Eye Cornea 05-Apr-94 Replacement IS 257 – Spring 2004 Penicillin none none Tetracycline 2004-02-10 SLIDE 17 Third Normal Form Drug Admin IS 257 – Spring 2004 Side Effects Cephalosporin none Demicillin none none none Penicillin rash Tetracycline Fever 2004-02-10 SLIDE 18 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 IS 257 – Spring 2004 2004-02-10 SLIDE 19 BCNF Relations Patient # Patient Name IS 257 – Spring 2004 Patient # 1111 John White 1111 1234 Mary Jones Charles 2345 Brown 1234 4876 Hal Kane 4876 5123 Paul Kosher 5123 6845 Ann Hood 6845 2345 Patient Address 15 New St. New York, NY 10 Main St. Rye, NY Dogwood Lane Harrison, NY 55 Boston Post Road, Chester, Blind Brook Mamaroneck, NY Hilton Road Larchmont, NY 2004-02-10 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 – Spring 2004 2004-02-10 SLIDE 21 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. IS 257 – Spring 2004 2004-02-10 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 – Spring 2004 2004-02-10 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 – Spring 2004 2004-02-10 SLIDE 24 Downward Denormalization Before: Customer ID Address Name Telephone Order Order No Date Taken Date Dispatched Date Invoiced Cust ID IS 257 – Spring 2004 After: Customer ID Address Name Telephone Order Order No Date Taken Date Dispatched Date Invoiced Cust ID Cust Name 2004-02-10 SLIDE 25 Upward Denormalization Order Order No Date Taken Date Dispatched Date Invoiced Cust ID Cust Name Order Item Order No Item No Item Price Num Ordered IS 257 – Spring 2004 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 2004-02-10 SLIDE 26 Lecture Outline • Review – Normalization • Physical Database Design • Access Methods IS 257 – Spring 2004 2004-02-10 SLIDE 27 Database Design Process Application 1 External Model Application 2 Application 3 Application 4 External Model External Model 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 – Spring 2004 Physical Design 2004-02-10 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 – Spring 2004 2004-02-10 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 – Spring 2004 2004-02-10 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 – Spring 2004 2004-02-10 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 – Spring 2004 2004-02-10 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 – Spring 2004 2004-02-10 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 – Spring 2004 2004-02-10 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 – Spring 2004 2004-02-10 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 -3.402823E38 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 IS 257 – Spring 2004 16 bytes 2004-02-10 SLIDE 36 Controlling Data Integrity • • • • • Default values Range control Null value control Referential integrity Handling missing data IS 257 – Spring 2004 2004-02-10 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 – Spring 2004 2004-02-10 SLIDE 38 Designing Physical/Internal Model • Overview • terminology • Access methods IS 257 – Spring 2004 2004-02-10 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 – Spring 2004 2004-02-10 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 – Spring 2004 2004-02-10 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 – Spring 2004 2004-02-10 SLIDE 42 Internal Model Access Methods • Many types of access methods: – Physical Sequential – Indexed Sequential – Indexed Random – Inverted – Direct – Hashed • Differences in – Access Efficiency – Storage Efficiency IS 257 – Spring 2004 2004-02-10 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 – Spring 2004 2004-02-10 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 – Spring 2004 2004-02-10 SLIDE 45 Index Sequential Data File Actual Value IS 257 – Spring 2004 Address Block Number Dumpling 1 Harty 2 Texaci 3 ... … Adams Becker Dumpling Block 1 Getta Harty Block 2 Mobile Sunoci Texaci Block 3 2004-02-10 SLIDE 46 Indexed Sequential: Two Levels Key Value 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 – Spring 2004 705 710 . . 785 2004-02-10 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 – Spring 2004 2004-02-10 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 – Spring 2004 2004-02-10 SLIDE 49 Btree F B || D || F| || P || Z| H || L || P| R || S || Z| Devils Aces Boilers Cars IS 257 – Spring 2004 Flyers Hawkeyes Hoosiers Minors Panthers Seminoles 2004-02-10 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 – Spring 2004 2004-02-10 SLIDE 51 Inverted Student name Course Number CH 145 101, 103,104 Actual Value Address Block Number CH 145 1 CS 201 2 CS 623 3 PH 345 … Adams CH145 Becker cs201 Dumpling ch145 CS 201 102 Getta ch145 Harty cs623 Mobile cs623 CS 623 105, 106 IS 257 – Spring 2004 2004-02-10 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 – Spring 2004 2004-02-10 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 – Spring 2004 2004-02-10 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 can create wasted space Adding records requires rewriting file Updating records usually requires rewriting file IS 257 – Spring 2004 Not possible very easy 2004-02-10 SLIDE 55 Next Time • Indexes and when to index • Integrity Constraints • Referential Integrity IS 257 – Spring 2004 2004-02-10 SLIDE 56