The Case for Enhanced Abstract Data Types.

Praveen Seshadri, Miron Livny, Raghu Ramakrishnan: The Case for Enhanced Abstract Data Types. VLDB 1997: 66-75
  author    = {Praveen Seshadri and
               Miron Livny and
               Raghu Ramakrishnan},
  editor    = {Matthias Jarke and
               Michael J. Carey and
               Klaus R. Dittrich and
               Frederick H. Lochovsky and
               Pericles Loucopoulos and
               Manfred A. Jeusfeld},
  title     = {The Case for Enhanced Abstract Data Types},
  booktitle = {VLDB'97, Proceedings of 23rd International Conference on Very
               Large Data Bases, August 25-29, 1997, Athens, Greece},
  publisher = {Morgan Kaufmann},
  year      = {1997},
  isbn      = {1-55860-470-7},
  pages     = {66-75},
  ee        = {db/conf/vldb/SeshadriLR97.html},
  crossref  = {DBLP:conf/vldb/97},
  bibsource = {DBLP,}


The explosion in complex multi-media content makes it crucial for database systems to support such data efficiently. We make the case that the next generation of object-relational database systems should be based on Enhanced Abstract Data Type (E-ADT) technology, rather than on the ``blackbox'' ADTs used in current systems. An E-ADT is an abstract data type that exposes the semantics of its methods. Query optimizations are performed using these semantics, resulting in efficient query processing. The added functionality does not compromise the modularity of data types and the extensibility of the type system. Fundamental architectural changes are required to build such a database system; these have been explored through the implementation of E-ADTs in PREDATOR. Initial performance results demonstrate an order of magnitude in performance improvements.

Copyright © 1997 by the VLDB Endowment. Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the VLDB copyright notice and the title of the publication and its date appear, and notice is given that copying is by the permission of the Very Large Data Base Endowment. To copy otherwise, or to republish, requires a fee and/or special permission from the Endowment.

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Printed Edition

Matthias Jarke, Michael J. Carey, Klaus R. Dittrich, Frederick H. Lochovsky, Pericles Loucopoulos, Manfred A. Jeusfeld (Eds.): VLDB'97, Proceedings of 23rd International Conference on Very Large Data Bases, August 25-29, 1997, Athens, Greece. Morgan Kaufmann 1997, ISBN 1-55860-470-7
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Electronic Edition

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Referenced by

  1. Manuel Rodriguez-Martinez, Nick Roussopoulos: MOCHA: A Self-Extensible Database Middleware System for Distributed Data Sources. SIGMOD Conference 2000: 213-224
  2. Michael Jaedicke, Bernhard Mitschang: User-Defined Table Operators: Enhancing Extensibility for ORDBMS. VLDB 1999: 494-505
  3. Arunprasad P. Marathe, Kenneth Salem: Query Processing Techniques for Arrays. SIGMOD Conference 1999: 323-334
  4. William O'Connell, Felipe Cariño, G. Linderman: Optimizer and Parallel Engine Extensions for Handling Expensive Methods Based on Large Objects. ICDE 1999: 304-313
  5. Vladimir Zadorozhny: Cost-based Magic for Web Queries (Extended Abstract). ADBIS (Short Papers) 1999: 185-192
  6. Praveen Seshadri: Predator: A Resource for Database Research. SIGMOD Record 27(1): 16-20(1998)
  7. Ling Lin, Tore Risch: Querying Continuous Time Sequences. VLDB 1998: 170-181
  8. Tolga Urhan, Michael J. Franklin, Laurent Amsaleg: Cost Based Query Scrambling for Initial Delays. SIGMOD Conference 1998: 130-141
  9. Michael Jaedicke, Bernhard Mitschang: On Parallel Processing of Aggregate and Scalar Functions in Object-Relational DBMS. SIGMOD Conference 1998: 379-389
  10. Michael W. Godfrey, Tobias Mayr, Praveen Seshadri, Thorsten von Eicken: Secure and Portable Database Extensibility. SIGMOD Conference 1998: 390-401
  11. Hubert Naacke, Georges Gardarin, Anthony Tomasic: Leveraging Mediator Cost Models with Heterogeneous Data Sources. ICDE 1998: 351-360
  12. Praveen Seshadri, Miron Livny, Raghu Ramakrishnan: E-ADTs: Turbo-Charging Complex Data. IEEE Data Eng. Bull. 19(4): 11-18(1996)
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