Dbms intro


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Dbms intro

  1. 1. Databases and Database Management Systems (Based on Chapters 1-2) 1
  2. 2. • DBMS concepts and architecture• ER model• Relational Databases• Relational Algebra• Query Languages (SQL)• Database Design : Normalization and Functional Dependencies• Storage and Indexing• Emerging Trends in Database Technology – Web Data management, XML, Web mining, 2
  3. 3. 1. Basic DefinitionsDatabase: A collection of related data.Data: Known facts that can be recorded and have an implicit meaning.Mini-world: Some part of the real world about which data is stored in a database. For example, consider student names, student grades and transcripts at a university. 3
  4. 4. Approximation• The data stored in a database often tries to capture some aspect of the real-world in an approximate manner• Often not all real-world information is (or can be) captured – Generally, only the information, which is estimated to be needed for decision-making, is recorded in the database 4
  5. 5. Summarization• Sometimes, data could be stored in a database in a summarized form• Example1: In a student database, the “grades” column provides a summary – It does not record explicitly what the student scored in mid-sems, end-sems, labs etc• Example 2: In a database containing sales info, the number of units (of a product) sold may be shown as a single aggregated number – That is, it may not record explicitly how many units were sold during each hour, but only records the total sales for the whole day 5
  6. 6. Summarization, materiality and usefulness• The extent to which you summarize the data largely depends on the intended use of the database• Example: If you just want to know a student’s grades, recording the summarized grade is adequate – But if you also want to know whether the student is good in theory or in lab work, you would need to record theory and lab grades separately• Materiality criteria: Is recording the data at a certain level of detail relevant to decision-making (i.e., intended use of the data)? – Too much detail may not be required, and could even be counter-productive e.g., clouding decision-making 6
  7. 7. Semantics of the data• Semantics of the data: What does the data really mean?• Sometimes, by looking at a column name e.g., student name, you will know that this column contains student names• But assume a column name called “student grades” – This does not really tell you how the grades were calculated, and a grade of B corresponds to what absolute score etc 7
  8. 8. Semantics of the data• Now assume a column called “Total sales” in a sales database – This does not really tell you whether the information is about total sales for 1 day, 1 month or 1 year – Are the total sales figures about the sales done only within India, or this is about worldwide sales? – These total sales figures pertain to which month? – Does this include/exclude the effect of refunds (returned products e.g., due to defects)? – Do these sales figures correspond to some marketing campaign or sales strategy of the company? (Example: If you offer 50% discount, you are highly likely to sell more than if you offer 2% discount) – What percentage of the sales were done in bulk e.g., to suppliers instead of individual consumers? 8
  9. 9. Semantics of the data• Bottomline: To be able to query and use the data, you need to understand clearly what the data means, the context surrounding the data and the assumptions associated with the data• Without understanding the semantics of the data, you cannot figure out and interpret the meaning of the query results that the database will provide to you 9
  10. 10. Database Management System (DBMS): A software package/ system to facilitate the creation and maintenance of a computerized database.It• defines (data types, structures, constraints)• construct (storing data on some storage mediumcontrolled by DBMS)• manipulate (querying, update, report generation) databases for various applications.Database System: The DBMS software together with the data itself. Sometimes, the applications are also included. 10
  11. 11. 2. Example of a Database (Conceptual Data Model)Mini-world for the example: Part of a UNIVERSITY environment. Some mini-world entities (Data elements):- STUDENTs- COURSEs- SECTIONs (of COURSEs)- (academic) DEPARTMENTs- INSTRUCTORs Some mini-world relationships:- SECTIONs are of specific COURSEs- STUDENTs take SECTIONs- COURSEs have prerequisite COURSEs- INSTRUCTORs teach SECTIONs- COURSEs are offered by DEPARTMENTs- STUDENTs major in DEPARTMENTs 11
  12. 12. Figure 1.1: A simplified database system environment,illustrating the concepts and terminology discussed in Section 1.1 12
  13. 13. Figure 1.2: An example of a database that stores student records and their grades. 13
  14. 14. File Processing and DBMSFile Systems : – Store data over long periods of time – Store large amount of dataHowever : – No guarantee that data is not lost if not backed up – No support to query languages – No efficient access to data items unless the location is known – Application depends on the data definitions (structures) – Change to data definition will affect the application programs – Single view of the data – Separate files for each application – Limited control to multiple accesses - Data viewed as physically stored 14
  15. 15. 3. Main Characteristics of Database Technology- Self-contained nature of a database system: A DBMS catalog stores the description (structure, type, storage format of each entities) of the database. The description is called meta-data). This allows the DBMS software to work with different databases.- To understand meta-data, think of a web-page which contains certain tags- Example: A webpage containing a UNIX tutorial could have tags related to some of the UNIX commands 15
  16. 16. Meta-data- Meta-data is essentially “data about the data” - Often meta-data is a set of keywords which try to approximately describe the data- Meta-data is often used for facilitating search 16
  17. 17. Main characteristics (Cont.)• Insulation between programs and data: Called program-data independence. Allows changing data storage structures and operations without having to change the DBMS access programs.• You will see this concept of “independence” throughout CS in general• The whole idea of creating layers is to ensure that whatever you change in one layer will have no effect on the other layer 17
  18. 18. Main characteristics (Cont.)• Data Abstraction: A data model is used to hide storage details and present the users with a conceptual view of the database; does not include how data is stored and how the operations are implemented.• Now can anyone tell me why data abstraction is important? – Answer is on the next slide 18
  19. 19. Why is data abstraction important?• We do not want the user to be burdened with all the details of how the data is being actually stored, which data structures are being used etc• If we did not have any data abstraction, databases would not be very usable/consumable because we cannot expect every user to go through this learning curve of understanding data structures, storage, indexing etc before they can even start to use a database• Users of databases come from diverse backgrounds i.e., they are not necessarily only CS majors 19
  20. 20. • Support of multiple views of the data: Each user may see a different view of the database, which describes only the data of interest to that user. – This could sometimes relate to access control • Example: The professor is allowed to see all student grades, but each student can only see his own grade from the database• Sharing of Data and Multiple users 20
  21. 21. Figure 1.3: Internal storage format for a STUDENT RECORD 21
  22. 22. Figure 1.4:Two views derived from the example database shown in Figure 1.2 (a) The student transcript view. (b) The course prerequisite view. 22
  23. 23. DBA – Database Administrator- Responsible for authorizing access to the database, coordinating, monitoring its use, acquiring hardware, software needed.Database designers- Responsible for identifying the data to be stored, storage structure to represent and store data. This is done by a team of professionals in consultation with users, and applications needed. 23
  24. 24. Type of data stored: Temporal angle- The type of data to be stored often changes over time- For example: The amount of data stored now per customer interaction is much more than the amount of data that used to be stored 10 years ago- Storing more data about a given user allows for more personalized services (some privacy constraints exist)- In practice, as more personalization becomes desirable, you need to store data at a more detailed level 24
  25. 25. 4. Additional Benefits of Database Technology- Controlling redundancy in data storage and in development and maintenance efforts.- Sharing of data among multiple users.- Restricting unauthorized access to data.- Providing multiple interfaces to different classes of users.- Representing complex relationships among data.- Enforcing integrity constraints on the database.- Providing backup and recovery services.- Potential for enforcing standards.- Flexibility to change data structures.- Reduced application development time.- Availability of up-to-date information.• Economies of scale. 25
  26. 26. Figure 1.5: The redundant storage of Data items. (a) ControlledRedundancy: Including StudentName and CourseNumber in the grade_report file. (b) Uncontrolled redundancy: A GRADE_REPORT record that is inconsistent with the STUDENT records in Figure 1.2, because the Name of student number 17 is Smith, not Brown. 26
  27. 27. 5 When not to use a DBMS Main inhibitors (costs) of using a DBMS:- High initial investment and possible need for additional hardware.- Overhead for providing generality, security, recovery, integrity, and concurrency control. When a DBMS may be unnecessary:- If the database and applications are simple, well defined, and not expected to change.- If there are stringent real-time requirements that may not be met because of DBMS overhead.- If access to data by multiple users is not required. When no DBMS may suffice: - If the database system is not able to handle the complexity of data because of modeling limitations- If the database users need special operations not supported by the DBMS. 27
  28. 28. 6. Data ModelsData Model: A set of concepts to describe the structure (data types, relationships) of a database, and certain constraints that the database should obey.Data Model Operations: Operations for specifying database retrievals and updates by referring to the concepts of the data model. 28
  29. 29. Categories of data models:- Conceptual (high-level, semantic) data models: Provide concepts that are close to the way many users perceive data. (Also called entity-based or object-based data models.) - Physical (low-level, internal) data models: Provide concepts that describe details of how data is stored in the computer.- Implementation (record-oriented) data models: Provide concepts that fall between the above two, balancing user views with some computer storage details. 29
  30. 30. 6A. HISTORY OF DATA MODELS• Relational Model: proposed in 1970 by E.F. Codd (IBM), first commercial system in 1981-82. Now in several commercial products (ORACLE, SYBASE, INFORMIX, INGRES).• Network Model: the first one to be implemented by Honeywell in 1964-65 (IDS System). Adopted heavily due to the support by CODASYL (CODASYL - DBTG report of 1971). Later implemented in a large variety of systems - IDMS (Cullinet - now CA), DMS 1100 (Unisys), IMAGE (H.P.), VAX -DBMS (Digital).• Hierarchical Data Model : implemented in a joint effort by IBM and North AmericanRockwell around 1965. Resulted in the IMS family of systems. The most popular model.Other system based on this model: System 2k (SAS inc.) 30•
  31. 31. Object-oriented Data Model(s) : several models have been proposed for implementing in a database system. One set comprises models of persistent O-O Programming Languages such as C++ (e.g., in OBJECTSTORE or VERSANT), and Smalltalk (e.g., in GEMSTONE). Additionally, systems like O2, ORION (at MCC - then ITASCA), IRIS (at H.P.- used in Open OODB).• Object-Relational Models : Most Recent Trend. Exemplified in ILLUSTRA and UNiSQL systems. 31
  32. 32. Figure 2.1: Schema diagram for the database of Figure 1.2 32
  33. 33. 7. Schemas versus InstancesDatabase Schema: The description of a database. Includes descriptions of the database structure and the constraints that should hold on the database.Schema Diagram: A diagrammatic display of (some aspects of) a database Schema.Database Instance: The actual data stored in a database at a particular moment in time . Also called database state (or occurrence).The database schema changes very infrequently . The database state changes every time the database is updated . Schema is also called intension, whereas state is called extension. 33
  34. 34. 8. Three-Schema ArchitectureProposed to support DBMS characteristics of:- Program-data independence.- Support of multiple views of the data.Defines DBMS schemas at three levels :- Internal schema at the internal level to describe datastorage structures and access paths. Typically uses a physicaldata model.- Conceptual schema at the conceptual level to describe thestructure and constraints for the whole database. Uses aconceptual or an implementation data model.- 34
  35. 35. External schemas at the external level to describe the various user views. Usually uses the same data model as the conceptual level.Mappings among schema levels are also needed. Programs refer to an external schema, and are mapped by the DBMS to the internal schema for execution. 35
  36. 36. Figure 2.2: Illustrating the three-schema architecture 36
  37. 37. 9 Data IndependenceLogical Data Independence: The capacity to change the conceptual schema without having to change the external schemas and their application programs.Physical Data Independence: The capacity to change the internal schema without having to change the conceptual schema.When a schema at a lower level is changed, only the mappings between this schema and higher-level schemas need to be changed in a DBMS that fully supports data independence. The higher- level schemas themselves are unchanged.Hence, the application programs need not be changed since they refer to the external schemas. 37
  38. 38. 10. DBMS LanguagesData Definition Language (DDL): Used by the DBA and database designers to specify the conceptual schema of a database.In many DBMSs, the DDL is also used to define internal and external schemas (views). In some DBMSs, separate storage definition language (SDL) and view definition language (VDL) are used to define internal and external schemas.Data Manipulation Language (DML): Used to specify database retrievals and updates. - DML commands (data sublanguage) can be embedded in a general-purpose programming language (host language), such as COBOL, PL/1 or PASCAL. - Alternatively, stand-alone DML commands can be applied directly (query language). 38
  39. 39. High Level or non-Procedural DML – Describes what data to be retrieved rather than how to retrieve. - Process many records at a time - SQL Low Level or Procedural DML – It needs constructs for both, what to retrieve and what to retrieve - Uses looping etc. like programming languages Only access one record at a time 39
  40. 40. 11. DBMS Interfaces-Stand-alone query language interfaces.- Programmer interfaces for embedding DML in programminglanguages:- Pre-compiler Approach- Procedure (Subroutine) Call Approach- User-friendly interfaces:- Menu-based- Graphics-based (Point and Click, Drag and Drop etc.)- Forms-based- Natural language- Combinations of the above- Speech as Input (?) and Output- Web Browser as an interface- 40
  41. 41. Parametric interfaces using function keys. - Report generation languages. - Interfaces for the DBA: - Creating accounts, granting authorizations - Setting system parameters - Changing schemas or access path 41
  42. 42. Figure 2.3: Typical component modules of a DBMS. Dotted linesshow accesses that are under the control of the stored data manager. 42
  43. 43. 13. Database System Utilities To perform certain functions such as: - Loading data stored in files into a database. - Backing up the database periodically on tape. - Reorganizing database file structures. - Report generation utilities. - Performance monitoring utilities. - Other functions, such as sorting , user monitoring , data compression , etc. Data dictionary / repository: - Used to store schema descriptions and other information such as design decisions, application program descriptions, user information, usage standards, etc. - Active data dictionary is accessed by DBMS software and users/DBA. 43- Passive data dictionary is accessed by users/DBA only.
  44. 44. 14. Classification of DBMSs Based on the data model used: - Traditional: Relational, Network, Hierarchical. - Emerging: Object-oriented, Object-relational. Other classifications: - Single-user (typically used with micro- computers) vs. multi-user (most DBMSs). - Centralized (uses a single computer with one database) vs. distributed (uses multiple computers, multiple databases)Distributed Database Systems have now come to be known as client server based database systems because they do not support a totally distributed environment, but rather a set of database servers supporting a set of clients. 44
  45. 45. Weekly assignment• Go through the lecture slides thoroughly – Your TA will send you a link to inform you where to download the lecture slides• Reading assignment: – Read Chapters 1-2 of your textbook• If you have any doubts/questions, pls let me know 45
  46. 46. Weekly assignment• Remember that in this course, you will often need to understand the concepts of Chapter N before you can deal with Chapter N+1• Do not fall behind the class 46
  47. 47. Weekly assignment (Cont.)– Refer to the following: http://www2.sims.berkeley.edu/research/projects/how-much-info- 2003/ • This website provides information about how much data exists in the world, and will broaden your perspective on data management in general • Reading through the entire website is not required for this course, but I want all of you to read through the “Summary of Findings” http://www2.sims.berkeley.edu/research/projects/how-much-info- 2003/execsum.htm • While reading, pay particular attention to Section 5, where the authors discuss issues concerning assumptions and estimates • Questions about the exact numbers will not be asked in your exams, but you should be prepared to answer questions about the general material in the “Summary of Findings” e.g., 47 assumptions, estimates etc
  48. 48. Weekly assignment• After reading through the “Summary of Findings”, prepare a 1-2 page report to indicate what you learned by reading through the material• Submit the report to your course TA in hard-copy format latest by Jan 22, 5 pm IST – No submissions will be accepted after the deadline 48
  49. 49. Weekly assignment• You can choose to format the report in any way you like – Focus on the content of the report, not on minor details such as font size, what font to use etc – The report will be graded based on content, hence mention only the key points – You will get full grade in this assignment as long as you mention some key points that you learned – Printouts are preferable, but handwritten reports are also ok as long as your handwriting is understandable 49
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