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Database Management Systems 1 Introduction to Database Systems Instructor: Xintao Wu Ramakrishnan & Gehrke.

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Presentation on theme: "Database Management Systems 1 Introduction to Database Systems Instructor: Xintao Wu Ramakrishnan & Gehrke."— Presentation transcript:

1 Database Management Systems 1 Introduction to Database Systems Instructor: Xintao Wu Ramakrishnan & Gehrke

2 Database Management Systems 2 Ramakrishnan & Gehrke http://www.sigmod.org/record/issues/0606/index.html

3 Database Management Systems 3 Ramakrishnan & Gehrke History v 60s C. Bachman GE network data model v Late 60s IBM IMS hierarchical data model v 70 E. Codd relational model v 80s SQL IBM R transaction J. Gray v Late 80s-90s DB2, Oracle, Informix, Sybase v 90s- Data warehouse, internet, v 2009- NoSQL, NewSQL Turing award and Turing test? Turing award listTuring award list Turing websiteTuring website

4 Database Management Systems 4 Ramakrishnan & Gehrke What Is a DBMS? v A very large, integrated collection of data. v Models real-world enterprise. – Entities (e.g., students, courses) – Relationships (e.g., Madonna is taking ITCS6160) v A Database Management System (DBMS) is a software package designed to maintain and utilize databases.

5 Database Management Systems 5 Ramakrishnan & Gehrke Why Use a DBMS? v Data independence and efficient access. v Reduced application development time. v Data integrity and security. v Uniform data administration. v Concurrent access, recovery from crashes.

6 Database Management Systems 6 6

7 7 Ramakrishnan & Gehrke Data Models v A data model is a collection of concepts for describing data. v A schema is a description of a particular collection of data, using the given data model. v The relational model of data is the most widely used model today. –Main concept: relation, basically a table with rows and columns. –Every relation has a schema, which describes the columns, or fields.

8 Database Management Systems 8 Ramakrishnan & Gehrke Levels of Abstraction v Many views, single conceptual (logical) schema and physical schema. –Views describe how users see the data. –Conceptual schema defines logical structure –Physical schema describes the files and indexes used. * Schemas are defined using DDL; data is modified/queried using DML. Physical Schema Conceptual Schema View 1View 2View 3

9 Database Management Systems 9 Ramakrishnan & Gehrke Example: University Database v Conceptual schema: – Students(sid: string, name: string, login: string, age: integer, gpa:real) – Courses(cid: string, cname:string, credits:integer) – Enrolled(sid:string, cid:string, grade:string) v Physical schema: –Relations stored as unordered files. –Index on first column of Students. v External Schema (View): – Course_info(cid:string,enrollment:integer)

10 Database Management Systems 10 Ramakrishnan & Gehrke Data Independence v Applications insulated from how data is structured and stored. v Logical data independence : Protection from changes in logical structure of data. v Physical data independence : Protection from changes in physical structure of data. * One of the most important benefits of using a DBMS!

11 Database Management Systems 11 Ramakrishnan & Gehrke Structure of a DBMS v A typical DBMS has a layered architecture. v The figure does not show the concurrency control and recovery components. v This is one of several possible architectures; each system has its own variations. Query Optimization and Execution Relational Operators Files and Access Methods Buffer Management Disk Space Management DB These layers must consider concurrency control and recovery

12 Database Management Systems 12 Ramakrishnan & Gehrke Transaction Management: ACID properties v A v A tomicity: All actions in the Xact happen, or none happen. v C v C onsistency: If each Xact is consistent, and the DB starts consistent, it ends up consistent. v I v I solation: Execution of one Xact is isolated from that of other Xacts. v D v D urability: If a Xact commits, its effects persist. v The Recovery Manager guarantees Atomicity & Durability whereas the Concurrency Control guarantees Consistency & Isolation.

13 Database Management Systems 13 Ramakrishnan & Gehrke Motivation of concurrency control v Consistency v Isolation v Example –Two parallel transactions T1 and T2 –Serial execution –Execution with interleaving actions –Example shown on board

14 Database Management Systems 14 Example v Consider two transactions ( Xacts ): T1:BEGIN A=A+100, B=B-100 END T2:BEGIN A=1.06*A, B=1.06*B END v Intuitively, the first transaction is transferring $100 from B’s account to A’s account. The second is crediting both accounts with a 6% interest payment. v There is no guarantee that T1 will execute before T2 or vice-versa, if both are submitted together. However, the net effect must be equivalent to these two transactions running serially in some order.

15 Database Management Systems 15 Example (Contd.) v Consider a possible interleaving ( schedule ): T1: A=A+100, B=B-100 T2: A=1.06*A, B=1.06*B v This is OK. But what about: T1: A=A+100, B=B-100 T2: A=1.06*A, B=1.06*B v The DBMS’s view of the second schedule: T1: R(A), W(A), R(B), W(B) T2: R(A), W(A), R(B), W(B)

16 Database Management Systems 16 Ramakrishnan & Gehrke Motivation of recovery management v Atomicity: –Transactions may abort (“Rollback”). v Durability: –What if DBMS stops running? (Causes?) crash! v Desired Behavior after system restarts: –T1, T2 & T3 should be durable. –T4 & T5 should be aborted (effects not seen). T1 T2 T3 T4 T5

17 Database Management Systems 17 Ramakrishnan & Gehrke Summary v DBMS used to maintain, query large datasets. v Benefits include recovery from system crashes, concurrent access, quick application development, data integrity and security. v Levels of abstraction give data independence. v A DBMS typically has a layered architecture. v DBAs hold responsible jobs and are well-paid! v DBMS R&D is one of the broadest, most exciting areas in CS.


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