Sideways Information Passing for Push-Style Query Processing

Loading...
Thumbnail Image
Penn collection
Database Research Group (CIS)
Degree type
Discipline
Subject
sideways information passing
adaptive
push-style
adaptive information passing
Funder
Grant number
License
Copyright date
Distributor
Related resources
Contributor
Abstract

In many modern data management settings, data is queried from a central node or nodes, but is stored at remote sources. In such a setting it is common to perform "pushstyle" query processing, using multi-threaded pipelined hash joins and bushy query plans to compute parts of the query in parallel; to avoid idling, the CPU can switch between them as delays are encountered. This works well for simple select-project join queries, but increasingly, Web and integration applications require more complex queries with multiple joins and even nested subqueries. As we demonstrate in this paper, push-style execution of complex queries can be improved substantially via sideways information passing; push-style queries provide many opportunities for information passing that have not been studied in the past literature. We present adaptive information passing, a general runtime decision-making technique for reusing intermediate state from one query subresult to prune and reduce computation of other subresults. We develop two alternative schemes for performing adaptive information passing, which we study in several settings under a variety of workloads.

Advisor
Date of presentation
2008-04-07
Conference name
Database Research Group (CIS)
Conference dates
2023-05-17T02:49:07.000
Conference location
Date Range for Data Collection (Start Date)
Date Range for Data Collection (End Date)
Digital Object Identifier
Series name and number
Volume number
Issue number
Publisher
Publisher DOI
Journal Issue
Comments
Copyright 2008 IEEE. Reprinted from the IEEE 24th International Conference on Data Engineering, ICDE 2008, pages 774-783. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Pennsylvania's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
Recommended citation
Collection