AGM: A Dataflow Database Machine.

Lubomir Bic, Robert L. Hartmann: AGM: A Dataflow Database Machine. ACM Trans. Database Syst. 14(1): 114-146(1989)
  author    = {Lubomir Bic and
               Robert L. Hartmann},
  title     = {AGM: A Dataflow Database Machine},
  journal   = {ACM Trans. Database Syst.},
  volume    = {14},
  number    = {1},
  year      = {1989},
  pages     = {114-146},
  ee        = {, db/journals/tods/BicH89.html},
  bibsource = {DBLP,}


In recent years, a number of database machines consisting of large numbers of parallel processing elements have been proposed. Unfortunately, there are two main limitations in database processing that prevent a high degree of parallelism; these are the available I/O bandwidth of the underlying storage devices and the concurrency control mechanisms necessary to guarantee data integrity. The main problem with conventional approaches is the lack of a computational model capable of utilizing the potential of any significant number of processing elements and storage devices and, at the same time, preserving the integrity of the database.

This paper presents a database model and its associated architecture, which is based on the principles of data-driven computation. According to this model, the database is represented as a network in which each node is conceptually an independent, asynchronous processing element, capable of communicating with other nodes by exchanging messages along the network arcs. To answer a query, one or more such messages, called tokens, are created and injected into the network. These then propagate asynchronously through the network in search of results satisfying the given query.

The asynchronous nature of processing permits the model to be mapped onto a computer architecture consisting of large numbers of independent disk units and processing elements. This increases both the available I/O bandwidth as well as the processing potential of the machine. At the same time, new concurrency control and error recovery mechanisms are necessary to cope with the resulting parallelism.

Copyright © 1989 by the ACM, Inc., used by permission. Permission to make digital or hard copies is granted provided that copies are not made or distributed for profit or direct commercial advantage, and that copies show this notice on the first page or initial screen of a display along with the full citation.

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Referenced by

  1. Arun K. Thakore, Stanley Y. W. Su, Herman Lam: Algorithms for Asynchronous Parallel Processing of Object-Oriented Databases. IEEE Trans. Knowl. Data Eng. 7(3): 487-504(1995)
  2. Stanley Y. W. Su, Soon J. Hyun, Rahul B. Patel: A Parallel Pattern Search Algorithm for Processing Object-Oriented Databases in a Cellular Array Architecture. DASFAA 1993: 159-169
  3. Rishiyur S. Nikhil, Michael L. Heytens: Exploiting Parallelism in the Implementation of Agna, a Persistent Programming System. ICDE 1991: 660-669
  4. Douglas Stott Parker Jr., Richard R. Muntz, H. Lewis Chau: The Tangram Stream Query Processing System. ICDE 1989: 556-563
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