3,455 research outputs found

    First-Class Functions for First-Order Database Engines

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    We describe Query Defunctionalization which enables off-the-shelf first-order database engines to process queries over first-class functions. Support for first-class functions is characterized by the ability to treat functions like regular data items that can be constructed at query runtime, passed to or returned from other (higher-order) functions, assigned to variables, and stored in persistent data structures. Query defunctionalization is a non-invasive approach that transforms such function-centric queries into the data-centric operations implemented by common query processors. Experiments with XQuery and PL/SQL database systems demonstrate that first-order database engines can faithfully and efficiently support the expressive "functions as data" paradigm.Comment: Proceedings of the 14th International Symposium on Database Programming Languages (DBPL 2013), August 30, 2013, Riva del Garda, Trento, Ital

    Main Memory Implementations for Binary Grouping

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    An increasing number of applications depend on efficient storage and analysis features for XML data. Hence, query optimization and efficient evaluation techniques for the emerging XQuery standard become more and more important. Many XQuery queries require nested expressions. Unnesting them often introduces binary grouping. We introduce several algorithms implementing binary grouping and analyze their time and space complexity. Experiments demonstrate their performance

    Survey over Existing Query and Transformation Languages

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    A widely acknowledged obstacle for realizing the vision of the Semantic Web is the inability of many current Semantic Web approaches to cope with data available in such diverging representation formalisms as XML, RDF, or Topic Maps. A common query language is the first step to allow transparent access to data in any of these formats. To further the understanding of the requirements and approaches proposed for query languages in the conventional as well as the Semantic Web, this report surveys a large number of query languages for accessing XML, RDF, or Topic Maps. This is the first systematic survey to consider query languages from all these areas. From the detailed survey of these query languages, a common classification scheme is derived that is useful for understanding and differentiating languages within and among all three areas

    D4.5 Implementation

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    Apache Calcite: A Foundational Framework for Optimized Query Processing Over Heterogeneous Data Sources

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    Apache Calcite is a foundational software framework that provides query processing, optimization, and query language support to many popular open-source data processing systems such as Apache Hive, Apache Storm, Apache Flink, Druid, and MapD. Calcite's architecture consists of a modular and extensible query optimizer with hundreds of built-in optimization rules, a query processor capable of processing a variety of query languages, an adapter architecture designed for extensibility, and support for heterogeneous data models and stores (relational, semi-structured, streaming, and geospatial). This flexible, embeddable, and extensible architecture is what makes Calcite an attractive choice for adoption in big-data frameworks. It is an active project that continues to introduce support for the new types of data sources, query languages, and approaches to query processing and optimization.Comment: SIGMOD'1

    Reasoning & Querying – State of the Art

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    Various query languages for Web and Semantic Web data, both for practical use and as an area of research in the scientific community, have emerged in recent years. At the same time, the broad adoption of the internet where keyword search is used in many applications, e.g. search engines, has familiarized casual users with using keyword queries to retrieve information on the internet. Unlike this easy-to-use querying, traditional query languages require knowledge of the language itself as well as of the data to be queried. Keyword-based query languages for XML and RDF bridge the gap between the two, aiming at enabling simple querying of semi-structured data, which is relevant e.g. in the context of the emerging Semantic Web. This article presents an overview of the field of keyword querying for XML and RDF

    Oracle Database 10g: a beginner's guide

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    Integration af XML Data i TARGIT OLAP Systemet

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    Optimizing Analytical Queries over Semantic Web Sources

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    Using semantics in XML query processing

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