Efficient bottom-up computation of queries on stratified databases

Balbin, Isaac; Port, Graeme S.; Ramamohanarao, Kotagiri; Meenakshi, K.

doi:10.1016/0743-1066(91)90030-s

Cited by 53 publications

(38 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The result fact(xa 2 ) is an equally valid conclusion that is either a generalization of or equivalent to fact(Lil ). There is no danger in deriving these more general facts.…”

Section: Generalizing Derived Factsmentioning

confidence: 93%

Upside-down meta-interpretation of the model elimination theorem-proving procedure for deduction and abduction

Stickel

1994

J Autom Reasoning

View full text Add to dashboard Cite

Typical bottom-up, forward-chaining reasoning systems such as hyperresolution lack goaldirectedness while typical top-down, backward-chaining reasoning systems like Prolog or model elimination repeatedly solve the same goals. Reasoning systems that are goal-directed and avoid repeatedly solving the same goals can be constructed by formulating the topdown methods metatheoretically for execution by a bottom-up reasoning system (hence, "upside-down meta-interpretation" is being used). This also facilitates the use of flexible search strategies, such as merit-ordered search, that are common to bottom-up interpreters. The model elimination theorem proving procedure, its extension by an assumption rule for abduction and its restriction to Horn clauses, are adapted here for such upside-down metainterpretation. This work can be regarded as an extension of the magic set method for query evaluation in deductive databases to both non-Horn clauses and abductive reasoning.

show abstract

“…The result fact(xa 2 ) is an equally valid conclusion that is either a generalization of or equivalent to fact(Lil ). There is no danger in deriving these more general facts.…”

Section: Generalizing Derived Factsmentioning

confidence: 93%

Upside-down meta-interpretation of the model elimination theorem-proving procedure for deduction and abduction

Stickel

1994

J Autom Reasoning

View full text Add to dashboard Cite

show abstract

“…The algorithm starts from the set of free variables of the magic set, and removes variables whenever doing so does not reduce the impact of the magic. performed -for instance, the magic-sets transformation can introduce unsafe recursion [1], which must be handled appropriately. The details are relatively straightforward and thus omitted.…”

Section: Figure 3: Determining the Magic Setmentioning

confidence: 99%

Adding magic to an optimising datalog compiler

Sereni¹,

Avgustinov²,

Moor³

2008

Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data

View full text Add to dashboard Cite

The magic-sets transformation is a useful technique for dramatically improving the performance of complex queries, but it has been observed that this transformation can also drastically reduce the performance of some queries. Successful implementations of magic in previous work require integration with the database optimiser to make appropriate decisions to guide the transformation (the sideways informationpassing strategy, or SIPS).This paper reports on the addition of the magic-sets transformation to a fully automatic optimising compiler from Datalog to SQL with no support from the database optimiser. We present an algorithm for making a good choice of SIPS using heuristics based on the sizes of relations. To achieve this, we define an abstract interpretation of Datalog programs to estimate the sizes of relations in the program.The effectiveness of our technique is evaluated over a substantial set of over a hundred queries, and in the context of the other optimisations performed by our compiler. It is shown that using the SIPS chosen by our algorithm, query performance is often significantly improved, as expected, but more importantly performance is never significantly degraded on queries that cannot benefit from magic.

show abstract

“…There have been several magic-set algorithms reported in the literature. 2o ,2\, 24 A common trait among these algorithms is that, based on the adornment of the head and body literals, some new positive literals are introduced into the body of rules, and new rules are added to the program which define these literals. The new literals are called magic literals and are related to the existing literals of the program as follows.…”

Section: The Magic-set Algorithmmentioning

confidence: 99%

On the bottom-up evaluation of recursive queries

Chen

1998

Int. J. Intell. Syst.

View full text Add to dashboard Cite

In this article, we present an optimal bottom-up evaluation method for handling both linear and nonlinear recursion. Based on the well-known magic-set method. we develop a technique: labeling to record the cyclic paths during the execution of the first phase of the magic-set method and suspending the computation for the cyclic data in the second phase to avoid the redundant evaluation.Then we postpone this computation to an iteration process (the third phase) which evaluates the remaining answers only along each cyclic path. In this way. we can guarantee the completeness.In addition. for a large class of programs we further optimize our method by elaborating the iteration process and generating most answers for each cyclic path directly from the intermediate results instead of evaluating them by performing algebraic operations (after some of the answers for the first cyclic path are produced). Because the cost of generating an answer is much less than that of evaluating an answer, this optimization is significant.

show abstract

Efficient bottom-up computation of queries on stratified databases

Cited by 53 publications

References 15 publications

Upside-down meta-interpretation of the model elimination theorem-proving procedure for deduction and abduction

Upside-down meta-interpretation of the model elimination theorem-proving procedure for deduction and abduction

Adding magic to an optimising datalog compiler

On the bottom-up evaluation of recursive queries

Contact Info

Product

Resources

About