Reassessing Top-Down Join Enumeration

Finding an optimal execution order of join operations is a crucial task in every cost-based query optimizer. Since there are many possible join trees for a given query, the overhead of the join (tree) enumeration algorithm per valid join tree should be minimal. In the case of a clique-shaped query g...

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Bibliographic Details
Published in:IEEE transactions on knowledge and data engineering Vol. 24; no. 10; pp. 1803 - 1818
Main Authors: Fender, Pit, Moerkotte, Guido
Format: Journal Article
Language:English
Published: New York IEEE 01.10.2012
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Complexity
Complexity theory
Cost function
Data structures
Dynamic programming
Enumeration
graph partitioning
Graphs
Heuristic algorithms
join ordering
memoization
minimal cut
Optimization
Partitioning algorithms
Query optimization
Query processing
Studies
Tasks
top-down join enumeration
Trees
ISSN:1041-4347, 1558-2191
Online Access:Get full text
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Summary:Finding an optimal execution order of join operations is a crucial task in every cost-based query optimizer. Since there are many possible join trees for a given query, the overhead of the join (tree) enumeration algorithm per valid join tree should be minimal. In the case of a clique-shaped query graph, the best known top-down algorithm has a complexity of \Theta (n^2) per join tree, where n is the number of relations. In this paper, we present an algorithm that has an according O(1) complexity in this case. We show experimentally that this more theoretical result has indeed a high impact on the performance in other nonclique settings. This is especially true for cyclic query graphs. Further, we evaluate the performance of our new algorithm and compare it with the best top-down and bottom-up algorithms described in the literature.
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ISSN:1041-4347
1558-2191
DOI:10.1109/TKDE.2011.235