Introduction to Database Systems��Chapter 1

Instructor: Johannes Gehrke�johannes@cs.cornell.edu

Database Management Systems, R. Ramakrishnan and J. Gehrke

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What Is a DBMS?

• A very large, integrated collection of data.
• Models real-world enterprise.
• Entities (e.g., students, courses)
• Relationships (e.g., Madonna is taking CS564)
• A Database Management System (DBMS) is a software package designed to store and manage databases.

Database Management Systems, R. Ramakrishnan and J. Gehrke

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Historical Perspective

• Early 1960s
• Integrated data store, first general-purpose DBMS designed by Charles Bachman at GE
• Formed basis for network data model
• Bachman received Turing Award in 1973 for his work in database area

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Database Management Systems, R. Ramakrishnan and J. Gehrke

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Historical Perspective

• Late 1960s
• IBM developed Information Management System (IMS), used even today in many major installations
• IMS formed the basis for hierarchical data model
• American Airlines and IBM jointly developed SABRE for making airline reservations
• SABRE is used today to populate Web-based travel services such as Travelocity

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Historical Perspective

• 1970
• Edgar Codd, at IBM’s San Jose Research Laboratory, proposed relational data model.
• It sparked the rapid development of several DBMSs based on relational model, along with a rich body of theoretical results that placed the field on a firm foundation.
• Codd won 1981 Turing Award.
• Database systems matured as an academic discipline
• The benefits of DBMS were widely recognized, and the use of DBMSs for managing corporate data became standard practice.

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Historical Perspective

• 1980s
• Relational data model consolidated its position as dominant DBMS paradigm, and database systems continued to gain widespread use
• SQL query language, developed as part of IBM’s System R project, is now the standard query language
• SQL was standardized in late 1980s, and current standard SQL:1999 was adopted by ANSI and ISO

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Historical Perspective

• Late 1980s till 1990s
• Considerable research into more powerful query language and richer data model, with emphasis on supporting complex analysis of data from all parts of an enterprise
• Several vendors, e.g., IBM’s DB2, Oracle 8, Informix UDS, extended their systems with the ability to store new data types such as images and text, and to ask more complex queries
• Data warehouses have been developed by many vendors to consolidate data from several databases, and for carrying out specialized analysis

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File Systems vs DBMS

• Must write special programs to answer each question a user may want to ask about data
• Must protect data from inconsistent changes made by different users accessing data concurrently
• Must cope with system crashes to ensure data consistency
• Need to enforce security policies in which different users have permission to access different subsets of the data

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Why Use a DBMS?

• Data independence (see next page) and efficient access.
• Reduced application development time.
• Data integrity and security.
• Uniform data administration.
• Concurrent access, recovery from crashes.

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Program-data dependence --- Three file processing systems at Some Company

File descriptions are stored within each application program that

accesses a given file. Any change to a file structure requires changes

to the file descriptions for all programs that access the file.

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Why Study Databases??

• Shift from computation to information
• at the “low end”: scramble to webspace (a mess!)
• at the “high end”: scientific applications
• Datasets increasing in diversity and volume.
• Digital libraries, interactive video, Human Genome project, EOS project
• ... need for DBMS exploding
• DBMS encompasses most of CS
• OS, languages, theory, “A”I, multimedia, logic

?

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Data Models

• A data model is a collection of concepts for describing data.
• A schema is a description of a particular collection of data, using the a given data model.
• 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.

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Levels of Abstraction

• 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 1

View 2

View 3

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Example: University Database

• 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)
• Physical schema:
• Relations stored as unordered files.
• Index on first column of Students.
• External Schema (View):
• Course_info(cid:string,enrollment:integer)

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Data Independence

• Applications insulated from how data is structured and stored.
• Logical data independence: Protection from changes in logical structure of data (the capacity to change the conceptual schema without having to change external schemas or application programs).

• One of the most important benefits of using a DBMS!

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Data Independence (cont.)

• Physical data independence: Protection from changes in physical structure of data (the capacity to change the internal schema without having to change the conceptual (or external) schemas).

• One of the most important benefits of using a DBMS!

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Concurrency Control

• Concurrent execution of user programs is essential for good DBMS performance.
• Because disk accesses are frequent, and relatively slow, it is important to keep the cpu humming by working on several user programs concurrently.
• Interleaving actions of different user programs can lead to inconsistency: e.g., check is cleared while account balance is being computed.
• DBMS ensures such problems don’t arise: users can pretend they are using a single-user system.

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Transaction: An Execution of a DB Program

• Key concept is transaction, which is an atomic sequence of database actions (reads/writes).
• Each transaction, executed completely, must leave the DB in a consistent state if DB is consistent when the transaction begins.
• Users can specify some simple integrity constraints on the data, and the DBMS will enforce these constraints.
• Beyond this, the DBMS does not really understand the semantics of the data. (e.g., it does not understand how the interest on a bank account is computed).
• Thus, ensuring that a transaction (run alone) preserves consistency is ultimately the user’s responsibility!

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Scheduling Concurrent Transactions

• DBMS ensures that execution of {T1, ... , Tn} is equivalent to some serial execution T1’ ... Tn’.
• Before reading/writing an object, a transaction requests a lock on the object, and waits till the DBMS gives it the lock. All locks are released at the end of the transaction. (Strict 2PL locking protocol.)
• Idea: If an action of Ti (say, writing X) affects Tj (which perhaps reads X), one of them, say Ti, will obtain the lock on X first and Tj is forced to wait until Ti completes; this effectively orders the transactions.
• What if Tj already has a lock on Y and Ti later requests a lock on Y? (Deadlock!) Ti or Tj is aborted and restarted!

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Ensuring Atomicity

• DBMS ensures atomicity (all-or-nothing property) even if system crashes in the middle of a Xact.
• Idea: Keep a log (history) of all actions carried out by the DBMS while executing a set of Xacts:
• Before a change is made to the database, the corresponding log entry is forced to a safe location. (WAL protocol; OS support for this is often inadequate.)
• After a crash, the effects of partially executed transactions are undone using the log. (Thanks to WAL, if log entry wasn’t saved before the crash, corresponding change was not applied to database!)

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The Log

• The following actions are recorded in the log:
• Ti writes an object: the old value and the new value.
• Log record must go to disk before the changed page!
• Ti commits/aborts: a log record indicating this action.
• Log records chained together by Xact id, so it’s easy to undo a specific Xact (e.g., to resolve a deadlock).
• Log is often duplexed and archived on “stable” storage.
• All log related activities (and in fact, all CC related activities such as lock/unlock, dealing with deadlocks etc.) are handled transparently by the DBMS.

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Overview of System Architecture

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Databases make these folks happy ...

• End users and DBMS vendors
• DB application programmers
• E.g. smart webmasters
• Database administrator (DBA)
• Designs logical /physical schemas
• Handles security and authorization
• Data availability, crash recovery
• Database tuning as needs evolve

Must understand how a DBMS works!

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Structure of a DBMS

• A typical DBMS has a layered architecture.
• The figure does not show the concurrency control and recovery components.
• This is one of several possible architectures; each system has its own variations.

These layers

must consider

concurrency

control and

recovery

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Summary

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

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