Efficient generation of query plans containing group-by, join, and groupjoin
| Autor: | Pit Fender, Guido Moerkotte, Marius Eich |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Recursive join
Hash join Theoretical computer science Computer science Sort-merge join Joins 02 engineering and technology Query optimization Eager evaluation Hardware and Architecture 020204 information systems 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Pruning (decision trees) Functional dependency Heuristics Information Systems |
| Zdroj: | The VLDB Journal. 27:617-641 |
| ISSN: | 0949-877X 1066-8888 |
| DOI: | 10.1007/s00778-017-0476-3 |
| Popis: | It has been a recognized fact for many years that query execution can benefit from pushing grouping operators down in the operator tree and applying them before a join. This so-called eager aggregation reduces the size(s) of the join argument(s), making join evaluation faster. Lately, the idea enjoyed a revival when it was applied to outer joins for the first time and incorporated in a state-of-the-art plan generator. However, the recent approach is highly dependent on the use of heuristics because of the exponential growth of the search space that goes along with eager aggregation. Finding an optimal solution for larger queries calls for effective optimality-preserving pruning mechanisms to reduce the search space size as far as possible. By a more thorough investigation of functional dependencies and keys, we provide a set of new pruning criteria and extend the idea of eager aggregation further by combining it with the introduction of groupjoins. We evaluate the resulting plan generator with respect to runtime and memory consumption. |
| Databáze: | OpenAIRE |
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