Title
AGM: a dataflow database machine
Abstract
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.
Year
DOI
Venue
1989
10.1145/62032.62037
ACM Trans. Database Syst.
Keywords
DocType
Volume
database model,parallel processing element,O bandwidth,asynchronous processing element,large number,dataflow database machine,processing potential,computational model,database machine,processing element,database processing
Journal
14
Issue
ISSN
Citations 
1
0362-5915
18
PageRank 
References 
Authors
20.36
16
2
Name
Order
Citations
PageRank
Lubomir Bic1332125.18
Robert L. Hartmann24137.10