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SQL query optimization

reordering for a general class of queries
Authors: Piyush Goel; Bala Iyer;

SQL query optimization

Abstract

The strength of commercial query optimizers like DB2 comes from their ability to select an optimal order by generating all equivalent reorderings of binary operators. However, there are no known methods to generate all equivalent reorderings for a SQL query containing joins, outer joins, and groupby aggregations. Consequently, some of the reorderings with significantly lower cost may be missed. Using hypergraph model and a set of novel identities, we propose a method to reorder a SQL query containing joins, outer joins, and groupby aggregations. While these operators are sufficient to capture the SQL semantics, it is during their reordering that we identify a powerful primitive needed for a dbms. We report our findings of a simple, yet fundamental operator, generalized selection, and demonstrate its power to solve the problem of reordering of SQL queries containing joins, outer joins, and groupby aggregations.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
11
Average
Top 10%
Average
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