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Damien Sereni

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Oege De Moor

Max Schaefer

Mathieu Verbaere

A method and system is provided for computing an approximation of the results of a query. The approximation represents a superset of all possible results, by computing a set of records of types (as opposed to a set of records of values, which is the normal result of a query). This is different from conventional systems, which typically infer types for each field individually. For each record of types, one may also keep track of equalities of fields to improve the precision of the approximation. The approximation can be used to detect erroneous parts of queries that always return an empty result, regardless of the contents of the data source. Furthermore, the same approximation is also useful in performing optimizations: first, by eliminating parts of procedure calls that are guaranteed to be irrelevant to the calling context, and second, by eliminating unnecessary type tests in the query.

Approximating query results by relations over types for error detection and optimization

A method and system is provided for computing an approximation of the number of distinct results of a query over a relational data source. The approximation uses information about dependencies between fields of relations, in particular the number of distinct values of a field for each possible value of another field. This information can be obtained by analysis of the data stored in the relational data source, or may be specified as annotations to a database schema. An approximation of the number of results is and the dependencies between fields of each part of the query are computed. The approximation can be used to reorder parts of a query, by using the estimated size of parts to guide reordering. The approximation can further be used to determine which parts of a query are relevant to the evaluation of a subquery, which can be used to guide the magic sets transformation.

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Damien Sereni