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Minimal difference query and view matchingMinimal difference query and view matching description/claimsThe Patent Description & Claims data below is from USPTO Patent Application 20070192297, Minimal difference query and view matching. Brief Patent Description - Full Patent Description - Patent Application Claims
CROSS REFERENCE TO RELATED APPLICATIONS [0001]This application is a continuation of U.S. patent application Ser. No. 11/352,628, filed on Feb. 13, 2006, entitled "MINIMAL DIFFERENCE QUERY AND VIEW MATCHING", the entirety of which is incorporated herein by reference. BACKGROUND [0002]Data-intensive applications such as decision support and e-commerce rely on being able to integrate data from various sources. To accomplish this task, a data transformation query is created between a data source and target. A variety of issues have to be addressed in identifying such a query. The data is often inconsistent owing to factors such as data entry errors and missing information. These inconsistencies must be removed before the data can be loaded and used for analysis. This is further compounded by the presence of mismatches between the source and the target schemas that need to be reconciled. As a result, the problem of data integration is widely recognized to be a significant challenge. [0003]The space of reasonable transformation queries between data source and target can be enormous, and it is very difficult for users to consider and even conceive of all possible options. This is aggravated by the fact that a user may not understand the source data fully. As a result, users need to try different queries iteratively until a satisfactory result is obtained. Previously published work has thus identified the need for interactive tools that help users understand the impact of a transformation query. [0004]In such an interactive environment, it is natural to reason about the difference between queries. Even a small change to a transformation query, such as changing a join column, relaxing an equi-join to a join that exploits string similarities (also known as similarity joins), changing the thresholds for similarity comparison or adding an extra join can have substantial impact on the results of the query. It is therefore very natural to ask whether such a change produces tuples that are expected at the result but were previously absent or suppresses tuples that were erroneously generated. [0005]Of course, the difference between queries can be computed in SQL (Structure Language Query), using the EXCEPT, EXCEPT ALL or MINUS clause. However, the performance of this approach is highly inadequate, especially when the two queries are closely related to each other. In particular, assume there are two queries Q.sub.1 and Q.sub.2. Conventionally, the difference is computed by executing both Q.sub.1 and Q.sub.2 and then determining the difference. SUMMARY [0006]The following presents a simplified summary in order to provide a basic understanding of some aspects of the claimed subject matter. This summary is not an extensive overview. It is not intended to identify key/critical elements or to delineate the scope of the claimed subject matter. Its sole purpose is to present some concepts in a simplified form as a prelude to the more detailed description that is presented later. [0007]Briefly described the subject innovation pertains to systems and methods of efficiently computing the difference between queries. In accordance with one aspect of the subject innovation, a principled approach is employed based on identifying joins that can be eliminated when computing the query difference. This is characterized by defining the notion of a minimal difference query (MDQ) that roughly corresponds to minimizing the number of joins. Systems and methods are disclosed for obtaining the minimal difference query that are adapted to both set and bag semantics. [0008]In accordance with another aspect of the subject innovation, the systems and methods can be extended to exploit known or determined metadata including but not limited to functional dependencies (e.g., key constraints) and inclusion dependencies (e.g., foreign key constraints). This metadata can be employed to improve query difference performance further by providing an opportunity to eliminate additional joins, for example based on redundant conjuncts. [0009]According to yet another aspect of the subject innovation, the query difference system and method can be exploited to further the scope of view matching technology in the case when the results of a query are only partially covered by a view. This can be accomplished by, among other things, incorporating the aforementioned difference operations into view matching. In an interactive environment, this strategy widens the possibility of using the results of previously executed queries in answering a query. This approach is especially useful when the queries are closely related, as is often the case in an interactive environment. [0010]Additionally or alternatively, aspects of the subject innovation can be employed in an analytical tool (e.g., client and/or server side) useful in contexts including but not limited to data cleaning, data integration and schema matching. For example, utilizing such a tool an entity or individual can reason whether a specific change to a query produces tuples that were expected but not found or suppresses tuples that were erroneously returned. [0011]To the accomplishment of the foregoing and related ends, certain illustrative aspects of the claimed subject matter are described herein in connection with the following description and the annexed drawings. These aspects are indicative of various ways in which the subject matter may be practiced, all of which are intended to be within the scope of the claimed subject matter. Other advantages and novel features may become apparent from the following detailed description when considered in conjunction with the drawings. BRIEF DESCRIPTION OF THE DRAWINGS [0012]FIG. 1 is a block diagram of a query difference system. [0013]FIG. 2 is a block diagram of a difference component. [0014]FIG. 3 is a block diagram of a query difference system. [0015]FIG. 4 is a block diagram of a constraint difference component. [0016]FIG. 5 is a block diagram of a query difference system. [0017]FIG. 6 is a diagram of query and view portions with respect to view matching. [0018]FIG. 7 is a block diagram of a view matching system. [0019]FIG. 8 is a flow chart diagram of a method of generating a minimal set difference query. [0020]FIG. 9 is a flow chart diagram of a method of generating a minimal set difference query exploiting constraints. Continue reading about Minimal difference query and view matching... 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