1. 9/26/2000SIMS 257: Database Management Physical Database Design University of California, Berkeley School of Information Management and Systems SIMS 257: Database Management

2. 9/26/2000SIMS 257: Database Management Review Normalization Denormalization

3. 9/26/2000SIMS 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

4. 9/26/2000SIMS 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.

5. 9/26/2000SIMS 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

6. 9/26/2000SIMS 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

7. 9/26/2000SIMS 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

8. 9/26/2000SIMS 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. 9/26/2000SIMS 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

10. 9/26/2000SIMS 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

11. 9/26/2000SIMS 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

12. 9/26/2000SIMS 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)

13. 9/26/2000SIMS 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 64000 chars)

14. 9/26/2000SIMS 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 -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.158 bytes Replication ID –Globally unique identifier (GUID)N/A16 bytes

15. 9/26/2000SIMS 257: Database Management Controlling Data Integrity Default values Range control Null value control Referential integrity Handling missing data

16. 9/26/2000SIMS 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

17. 9/26/2000SIMS 257: Database Management Designing Physical Files/Internal Model Overview terminology Access methods

18. 9/26/2000SIMS 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

19. 9/26/2000SIMS 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.

20. 9/26/2000SIMS 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

21. 9/26/2000SIMS 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

22. 9/26/2000SIMS 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)

23. 9/26/2000SIMS 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

24. 9/26/2000SIMS 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

25. 9/26/2000SIMS 257: Database Management Indexed Sequential: Two Levels Address 789…789… Key Value 385 678 805 001 003. 150 705 710. 785 251. 385 455 480. 536 605 610. 678 791. 805 Address 1212 Key Value 150 385 Address 3434 Key Value 536 678 Address 5656 Key Value 785 805

26. 9/26/2000SIMS 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

27. 9/26/2000SIMS 257: Database Management Indexed Random Address Block Number 2132121321 Actual Value Adams Becker Dumpling Getta Harty Becker Harty Adams Getta Dumpling

28. 9/26/2000SIMS 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

29. 9/26/2000SIMS 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

30. 9/26/2000SIMS 257: Database Management Inverted CH145 cs201 ch145 cs623 Address Block Number 123…123… Actual Value CH 145 CS 201 CS 623 PH 345 CH 145 101, 103,104 CS 201 102 CS 623 105, 106 Adams Becker Dumpling Getta Harty Mobile Student name Course Number

31. 9/26/2000SIMS 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

32. 9/26/2000SIMS 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

33. 9/26/2000SIMS 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