Physical Database Design

1. Physical Database Design University of California, Berkeley School of Information IS 257: Database Management

2. Lecture Outline • Review • Normalization • Physical Database Design • Access Methods

3. Lecture Outline • Review • Normalization • Physical Database Design • Access Methods

4. 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 requirements Conceptual Model Logical Model Internal Model Application 3 Conceptual requirements Application 4 Conceptual requirements

5. 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.

6. 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)

7. Normalization Unnormalized Relations First normal form Functional dependencyof nonkey attributes on the primary key - Atomic values only Second normal form No transitive dependency between nonkey attributes Third normal form Boyce- Codd and Higher Full Functional dependencyof nonkey attributes on the primary key All determinants are candidate keys - Single multivalued dependency

8. 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. Unnormalized Relation

10. 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.

11. First Normal Form

12. 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

13. Second Normal Form

14. Second Normal Form

15. Second Normal Form

16. 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

17. Third Normal Form

18. Third Normal Form

19. 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

20. BCNF Relations

21. 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

22. 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.

23. 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.

24. 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.

25. Downward Denormalization Before: After: 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 Customer ID Address Name Telephone

26. Upward Denormalization 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 Order No Date Taken Date Dispatched Date Invoiced Cust ID Cust Name Order Item Order No Item No Item Price Num Ordered

27. Using RDBMS to help normalize • Example database: Cookie • Database of books, libraries, publisher and holding information for a shared (union) catalog

28. Cookie relationships

29. Cookie BIBFILE relation

30. 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…

31. Lecture Outline • Review • Normalization • Using Relational DBs in normalization • Physical Database Design • Access Methods

32. 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 requirements Conceptual Model Logical Model Internal Model Application 3 Conceptual requirements Application 4 Conceptual requirements PhysicalDesign

33. 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

34. 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

35. 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

36. 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

37. 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

38. 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)

39. 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)

40. 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

41. Controlling Data Integrity • Default values • Range control • Null value control • Referential integrity (next time) • Handling missing data

42. 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

43. Designing Physical/Internal Model • Overview • terminology • Access methods

44. Physical Design DBMS External Model Internal Model Access Methods • Internal Model/Physical Model User request Interface 1 Interface 2 Operating System Access Methods Interface 3 Data Base

45. 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.

46. 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

47. Internal Model Access Methods • Many types of access methods: • Physical Sequential • Indexed Sequential • Indexed Random • Inverted • Direct • Hashed • Differences in • Access Efficiency • Storage Efficiency

48. 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)

49. 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

50. Index Sequential Data File Block 1 Block 2 Block 3 Adams Becker Dumpling Actual Value Address Block Number Dumpling Harty Texaci ... 1 2 3 … Getta Harty Mobile Sunoci Texaci