Database Research Group (CIS)

Document Type

Conference Paper

Date of this Version

April 2008

Comments

Copyright 2008 IEEE. Reprinted from the IEEE 24th International Conference on Data Engineering, ICDE 2008, pages 774-783.

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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.

Keywords

sideways information passing, adaptive, push-style, adaptive information passing

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Date Posted: 31 October 2008

This document has been peer reviewed.