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Database Systems “Breaking Out of the Box”. Avi Silberschatz Stan Zdonik Bell Laboratories Brown University July 7, 1997. The Paper’s Theme (Strategic Directions).

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Database systems breaking out of the box l.jpg

Database Systems “Breaking Out of the Box”

Avi Silberschatz Stan Zdonik

Bell Laboratories Brown University

July 7, 1997

Mehmet Uner


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The Paper’s Theme (Strategic Directions)

  • Database Research should be devoted to the problems of data management no matter where and in what form the data might be found.

  • Database management skills should be applied to new data management environments that potentially require radically new software architectures.

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Outline

  • Introduction

  • Background

  • Our Skills

  • Scenarios

  • Barriers

  • Research

  • Conclusions

  • References

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Introduction

  • The field of database systems research and development has been very successful over its 30 year history.

  • It has led to $10 billion industry that touches virtually every major company in the world.

  • Unthinkable to manage large volume of valuable information that keeps corporations runing without support from commercial database management systems (DBMS).

  • DBMS is a very complex system incorporating a rich set of technologies.

  • Suited for solving problems of large-scale data management in the corporate setting.

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DBMS

DBMS Requirements:

  • Execution Overhead.

  • High level of expertise to install and maintain.

  • Only manages data in fairly specific file formats.

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Solution

At the same time:

  • Data is changing rapidly.

  • Data is stored in different places (e.g. files)

  • Data is obtained in large volumes from external sources like sensors.

    Solution:

  • Not full-blown DBMS, a lighter-weight solution

  • Instead of using an existing tool in a new application, it is better to embed reusable components.

  • Use database system components, techniques and experience in new ways.

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Examples

  • Some examples that could benefit from data management techniques but that typically do not make heavy use of database products:

    • World Wide Web

    • Personal Information Systems (e-mail)

    • News Services

    • Scientific Applications

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Background

  • Database field born with release of IMS in 60’s.

    • IBM Product

    • Managed data as hierarchies

    • Data has value, manage independently of application

  • Codasyl, most well known successor

    • Based on graph-based structure.

  • Ted Codd published a paper in 1970

    • Suggested relational model.

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Background

  • Object Oriented Principles in 80’s

    • Allow users to create their own application-specific types that can be managed by the DBMS.

  • Hybrid model in 90’s

    • Embeds object-oriented features in a relational context.

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Our Skills

  • Database Management Systems have been concerned with the following problems:

    • High Performance

    • Correctness

    • Maintainability

    • Reliability

  • From point of view of slow-memory devices that must be shared by multiple concurrent users

  • This approach leads to a set of skills and techniques that can be applied and extended to other problems.

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Skills and Techniques

  • Data Modeling

    • Language for defining structure of database

    • Language for manipulating those structures.

  • Query Languages

    • High-level language to retrieve data from the database. (SQL)

  • Query Optimization and evaluation

  • State-based views

    • Restricted and reorganized view of database.

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Skills and Techniques

  • Data Management

    • Automatic maintenance of data structures

    • Efficient Movement of data

  • Transactions

    • A response to correctness problems introduced by concurrent access and update

  • Distributed Systems

  • Scalable Systems

    • Database systems have been tuned to efficiently and reliably handle data volumes that exceed the size of the the physical memory by several orders of magnitude.

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Scenarios

  • The way for future data management systems

  • The technology that would support these scenarios constitutes a research agenda for the next decade.

    1) Instant Virtual Enterprise

    2) Personal Information Systems

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Instant Virtual Enterprise

  • An “instant virtual enterprise” (IVE) is a group of companies, that do not routinely function as a unit.

  • Come together to respond to a customer order or request for proposal.

  • Computer integrated manufacturing (CIM) is an example of an environment requiring IVE cooperation.

  • Engineering side

    • Design, Production, Quality Assurance

  • Administrative side

    • Planning, Production Control, Resource Management

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Instant Virtual Enterprise

  • Companies in IVE needs to exchange and manage large amounts of data

  • Companies will have many heterogeneous databases

  • Sharing and exchanging data with coordinating information is critical

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Company A

Company Q

Company R

Company S

IVE Scenario

Building an oil pipeline

Engineering Firm (IVE)

License their design

Engineering Analysis

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Company T

Company U

Company V

Company W

IVE Scenario

Actual Fabrication

Casting

Design file conversion service

Documentation and Archiving

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IVE Scenario

  • Database Capabilities Needed:

    • Executing a query for the design

    • Data translation services for engineering analysis

    • Coordination and configuration management

    • Changes to an object in one subsystem require changes to one or more related objects in other subsystems.

    • Security and access control over the information

    • Archiving of information, even after the IVE disbands

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Personal Information Systems Scenario

  • Provides information to an individual

  • Uses PID (Personal Information Device)

    • PDA

    • Handheld PC

    • Laptop

  • Equipped with wireless network connection

  • Access to internet Anywhere, Anytime.

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Personal Information Systems Scenario

  • Tightly integrated with individual’s activities. From morning to bed time.

  • In the morning

    • Local Weather Report

    • List of Reminders

    • List of Morning Meetings

    • Best Route from home to work

    • Personalized Headlines

    • Personalized Investment Report

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Personal Information Systems Scenario

  • Throughout the day

    • Tasks for the day

    • List of customers to contact

    • Summary of breaking news

    • Best Driving Routes in the city

  • At the end of the day

    • Next day’s activities

    • Appointments

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Personal Information Systems Scenario

  • PID must continuosly query remote databases and monitor broadcast information

  • PID will magnify today’s client-server performance, scalibility and reliability problems

  • Where should data reside, PID or Server?

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Barriers

  • DBMS provides a tightly controlled and highly uniform environment

  • For the new applications, database functionality should be provided outside of the limits of a DBMS.

  • For the vision represented in the scenarios, a number of technical barriers must be removed.

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Barriers

  • Overhead

    • System requirements, expertise, planning, monetary cost

    • Builder of personalized newspaper service do not use DBMS because there is no need for many of the advanced features.

    • A subset of the traditional database services are needed by many new applications

  • Scale

    • Greater volume of data (petabytes)

    • Hundreds of servers, client population even larger

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Barriers

  • Schema Organization

    • First create a schema to describe the structure of the database and populate the database

    • Many applications currently create data independently of a database system. (scientific applications, web sites)

    • Schema is incomplete or inconsistent.

    • Schema management facilities is needed to adapt the dynamic nature of foreign data.

  • Data Quality

    • Information accessed form a WAN may be of varying quality.

    • Future information systems must be able to react to the quality of the data source.

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Barriers

  • Heterogeneity

    • Data exists in many forms

    • These dissimilar formats must be integrated to allow applications to access data in a high-level and uniform way

  • Query Complexity

    • Different characteristics in future environments

      • Conventional, minimize number of disk access

      • Future, minimize total “information bill”

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Barriers

  • Ease of Use

    • Highly-trained, full-time staff is assumed to manage a DBMS

    • Yet most users have no training in database tech.

    • Simple set of interfaces needed.

  • Security

    • As the amount of shared information grows, the need to restrict access to specific users of for specific use arises.

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Barriers

  • Guaranting Acceptable Outcomes

    • Transacation managemnet, a barrier to both system performance and ability to specify acceptable outcomes

    • New or enchanced transaction technology is needed

    • Making data unavaliable is not acceptable

    • Aborting transactions is unacceptable

  • Technology Transfer

    • Barrier between research and industry

      • Insufficient knowledge of each other

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Research

  • In order to achieve the vision and overcome these barriers, a number of central research topics must be addressed:

    • Extensibility and Componentization

    • Imprecise Results

    • Schemaless Databases

    • Ease-of Use

    • New transaction Model

    • Query Optimization

    • Data Movement

    • Security

    • Database Mining

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Research

  • Extensibility and Componentization

    • DBMS in a modular way

    • Lighter-weight applications

  • Imprecise Results

    • In the web search engines do not provide 100% accuracy

    • A general theory of imprecision must be developed

  • Schemaless Databases

    • Able to work with unstructured data

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Research

  • Ease-of-use

    • Better database interfaces are required.

  • New transaction Models

    • Overcome blocking.

    • Provides Correctness.

  • Query Optimization

    • New indexing methods, query processing strategies.

    • Cheaper but slower response time.

    • Sensitive to bandwidth and power considerations.

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Research

  • Data Movement

    • In a distributed environment, the cost of moving data can be extremely high

    • Asymmetric communication channels, (low bandwidth lines)

  • Security

    • Formulation of an authorization model

    • Interoperability between differen security policies

  • Database Mining

    • Machine Learning

    • Statistical Analysis

    • Database Technologies

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Conclusions

  • Database research must be broadly defined.

  • Database community must apply its experience and expertise to new areas and new solution packet must be found.

  • The vision is an integration that supports the application of database functionality in small modules that give just the right capability.

  • These modules should also represent a unified theory of information that allows for the querying information of all types without having to switch languages or paradigms.

Mehmet Uner


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References

  • E. F. Codd, “A relational Model for Large Shared Databanks”, Communications of the ACM, 13:6,(June 1970), pp. 377-387.

  • J. Gray,http://www.cs.washington.edu/homes/lazowska/cra/database.html

  • A. Silberschatz, M. Stonebraker, and J. Ullman, “Database Systems: Achievements and Opportunities,” SIGMOD Record, 19:4, pp.6-22.

  • A. Silberschatz, M. Stonebraker, and J. Ullman, “Database Systems: Achievements and Opportunities Into the 21st Century”, http://www.cs.stanford.edu/pub/papers/lagii.ps

  • J. Toole and P. Young, http://www.hpcc.gov/cic/forum/CIC_Cover.html

Mehmet Uner


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Thanks!

Any Questions?

Mehmet Uner


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