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Husheng Liao - One of the best experts on this subject based on the ideXlab platform.
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An Accurate Identification of Extended XML Tree Pattern for Xquery Language
International Journal of Database Theory and Application, 2014Co-Authors: Husheng Liao, Junpeng ChenAbstract:In order to utilize high-performance XML tree pattern query (TPQ) for implementing of Xquery Language effectively, it is necessary to analysis the query plan and identify tree pattern from it. In this paper, we extend the functional intermediate Language FXQL, which is used to implement Xquery Language, with an extended XML generalized tree pattern representation (GTP++). Then, we propose an XML tree pattern identification approach, which is composed of a suit of query expression rewriting rules for extracting tree pattern and a GTP++ construction algorithm. Based on this approach, both explicit and implied propositional logic, various structural constraints and predicates can be extracted across nested query blocks in Xquery FLWOR expressions. The tree pattern identified by this approach is more holistic and precisely than previous methods. The approach expands the application of XML tree pattern query technology in the implementation of Xquery Language. Experiments show its effectiveness and practicability.
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A Formal Description of XML Tree Pattern Query for Xquery Language
International Journal of Database Theory and Application, 2014Co-Authors: Husheng Liao, Li XiaoqingAbstract:In order to express tree pattern query in query plan and take advantage of formal method to analyze its behavioral characteristics, this paper present a formal description of tree pattern query based on functional Language and denotational semantics. This description major focuses on behavior of a tree pattern query on matching against an eXtensible Markup Language (XML) document tree. First, we introduce a formal definition for a kind of extended generalized tree pattern (GTP++). Then we present a functional tree pattern description Language (XTPL) for GTP++ and give its complete denotational semantics based on a novel data structure, named WTree, which efficiently organizes this typical XML data query results and provides flexible data access method. In the end, we present the formal semantics of identifying tree pattern from path expressions. By using formal methods, the semantics of tree pattern query is consistent and analyzable. As the core operation of XML query, this formal description can provide an initial step for analyzing the correctness of XML queries, and improves the reliability and robustness of query processing methods.
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MLTwig: A Multi-Layer Tree Pattern Matching Approach for Xquery
Applied Mechanics and Materials, 2014Co-Authors: Husheng LiaoAbstract:Twig query, also known as tree pattern query (TPQ), is considered as the core operation of XML data queries. However, a complex XML query described by Xquery often cannot be represented by a single basic TPQ. Aiming at Xquery Language, this paper presents a multi-layer tree pattern representation method, named MTP, and a matching algorithm MLTwig, which can effectively use intermediate results of outer query to match inner tree pattern in MTP based on a novel data structure, WTree, thereby saving time and space. Experimental results show that this algorithm can improve the processing efficiency for Xquery expression which can be represented by MTP.
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Automatic Parallelization of Xquery Programs
Journal of Software, 2013Co-Authors: Husheng Liao, Weifeng Shan, Hongyu GaoAbstract:Xquery is a functional Language with implicit parallelism. It is an important approach to improve the efficiency of XML query by taking full advantage of multi-core environment in the parallel implementation of Xquery Language. In this paper, we propose an implementation method for parallelizing XML query represented by Xquery programs automatically. According to the features of its functional Language, an Xquery program is divided into a number of tasks that can be executed in parallel. Then, on the basis of the running cost evaluation, three kinds of parallelism are applied to different tasks and they are data parallelism, task parallelism and pipeline parallelism. Under the guidance of a novel scheduling strategy, the execution of the Xquery program is parallelized automatically. The experiments show that this approach improves the efficiency of the execution of Xquery programs and the computing resources of multi-core computer are used efficiently.
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WAIM - An algorithm for incremental maintenance of materialized XPath view
Web-Age Information Management, 2010Co-Authors: Xueyun Jin, Husheng LiaoAbstract:Cached materialized view has lots of benefits, but it has inconsistency problem when the data source is modified. This paper proposes an incremental maintenance algorithm IMA to implement incremental maintenance of materialized XPath view. The characteristics of IMA are: (1) It can establish an incremental maintenance program automatically; (2) The incremental maintenance program is simple and its function is reassembling the materialized XPath view to obtain a consistent view; (3) The incremental maintenance program is written in Xquery Language and can be executed by any Xquery engine; (4) The only auxiliary data used to maintain the materialized XPath view is the incremental maintenance program and its size cost is very small. Experiments have shown that this approach outperforms view recomputation.
Jesús M. Almendros-jiménez - One of the best experts on this subject based on the ideXlab platform.
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XQOWL: An Extension of Xquery for OWL Querying and Reasoning
Electronic Proceedings in Theoretical Computer Science, 2015Co-Authors: Jesús M. Almendros-jiménezAbstract:One of the main aims of the so-called Web of Data is to be able to handle heterogeneous resources where data can be expressed in either XML or RDF. The design of programming Languages able to handle both XML and RDF data is a key target in this context. In this paper we present a framework called XQOWL that makes possible to handle XML and RDF/OWL data with Xquery. XQOWL can be considered as an extension of the Xquery Language that connects Xquery with SPARQL and OWL reasoners. XQOWL embeds SPARQL queries (via Jena SPARQL engine) in Xquery and enables to make calls to OWL reasoners (HermiT, Pellet and FaCT++) from Xquery. It permits to combine queries against XML and RDF/OWL resources as well as to reason with RDF/OWL data. Therefore input data can be either XML or RDF/OWL and output data can be formatted in XML (also using RDF/OWL XML serialization).
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OTM Conferences - Fuzzy XPath Queries in Xquery
On the Move to Meaningful Internet Systems: OTM 2014 Conferences, 2014Co-Authors: Jesús M. Almendros-jiménez, Alejandro Luna, Ginés MorenoAbstract:We have recently designed a fuzzy extension of the XPath Language which provides ranked answers to flexible queries taking profit of fuzzy variants of and, or and avg operators for XPath conditions, as well as two structural constraints, called down and deep, for which a certain degree of relevance is associated. In this work, we describe how to implement the proposed fuzzy XPath with the Xquery Language. Basically, we have defined an Xquery library able to fuzzily handle XPath expressions in such a way that our proposed fuzzy XPath can be encoded as Xquery expressions. The advantages of our approach is that any Xquery processor can handle a fuzzy version of XPath by using the library we have implemented.
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OTM Conferences - Embedding OWL Querying and Reasoning into Xquery
On the Move to Meaningful Internet Systems: OTM 2014 Conferences, 2014Co-Authors: Jesús M. Almendros-jiménezAbstract:In this paper we present a framework called XQOWL that makes possible to handle XML and RDF/OWL data with Xquery. XQOWL can be considered as an extension of the Xquery Language that connects Xquery with SPARQL and OWL reasoners. XQOWL embeds SPARQL queries (via Jena SPARQL engine) into Xquery and enables to make calls to OWL reasoners (HermiT, Pellet and FaCT++) from Xquery. It permits to combine queries against XML and RDF/OWL resources as well as to reason with RDF/OWL data. Therefore input data can be either XML or RDF/OWL and output data can be formatted in XML (also using RDF/OWL XML serialization).
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APWeb - Querying and reasoning with RDF(S)/OWL in Xquery
Web Technologies and Applications, 2011Co-Authors: Jesús M. Almendros-jiménezAbstract:In this paper we investigate how to use the Xquery Language for querying and reasoning with RDF(S)/OWL-style ontologies. Our proposal allows the handling of RDF(S)/OWL triples by means of a Xquery library for the Semantic Web, and it encodes RDF(S)/OWL reasoning by means of Xquery functions. We have tested and implemented the approach.
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INAP - Extending Xquery for semantic web reasoning
Lecture Notes in Computer Science, 2011Co-Authors: Jesús M. Almendros-jiménezAbstract:In this paper we investigate an extension of the Xquery Language for querying and reasoning with OWL-style ontologies. The proposed extension incorporates new primitives (i.e. boolean operators) in Xquery for the querying and reasoning with OWL-style triples in such a way that Xquery can be used as query Language for the Semantic Web. In addition, we propose a Prolog-based implementation of the extension.
Jan Rittinger - One of the best experts on this subject based on the ideXlab platform.
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EDBT - Let SQL drive the Xquery workhorse (Xquery join graph isolation)
Proceedings of the 13th International Conference on Extending Database Technology - EDBT '10, 2010Co-Authors: Torsten Grust, Manuel Mayr, Jan RittingerAbstract:A purely relational account of the true Xquery semantics can turn any relational database system into an Xquery processor. Compiling nested expressions of the fully compositional Xquery Language, however, yields odd algebraic plan shapes featuring scattered distributions of join operators that currently overwhelm commercial SQL query optimizers. This work rewrites such plans before submission to the relational database back-end. Once cast into the shape of join graphs, we have found off-the-shelf relational query optimizers---the B-tree indexing subsystem and join tree planner, in particular---to cope and even be autonomously capable of "reinventing" advanced processing strategies that have originally been devised specifically for the Xquery domain, e.g., XPath step reordering, axis reversal, and path stitching. Performance assessments provide evidence that relational query engines are among the most versatile and efficient Xquery processors readily available today.
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ICDE - Xquery Join Graph Isolation: Celebrating 30+ Years of Xquery Processing Technology
2009 IEEE 25th International Conference on Data Engineering, 2009Co-Authors: Torsten Grust, Manuel Mayr, Jan RittingerAbstract:A purely relational account of the true Xquery semantics can turn any relational database system into an Xquery processor. Compiling nested expressions of the fully compositional Xquery Language, however, yields odd algebraic plan shapes featuring scattered distributions of join operators that currently overwhelm commercial SQL query optimizers. This work rewrites such plans before submission to the relational database back-end. Once cast into the shape of join graphs, we have found off-the-shelf relational query optimizers — the B-tree indexing subsystem and join tree planner, in particular — to cope and even be autonomously capable of "reinventing" advanced processing strategies that have originally been devised specifically for the Xquery domain, e.g., XPath step reordering, axis reversal, and path stitching. Performance assessments provide evidence that relational query engines are among the most versatile and efficient Xquery processors readily available today.
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Xquery Join Graph Isolation
arXiv: Databases, 2008Co-Authors: Torsten Grust, Manuel Mayr, Jan RittingerAbstract:A purely relational account of the true Xquery semantics can turn any relational database system into an Xquery processor. Compiling nested expressions of the fully compositional Xquery Language, however, yields odd algebraic plan shapes featuring scattered distributions of join operators that currently overwhelm commercial SQL query optimizers. This work rewrites such plans before submission to the relational database back-end. Once cast into the shape of join graphs, we have found off-the-shelf relational query optimizers--the B-tree indexing subsystem and join tree planner, in particular--to cope and even be autonomously capable of "reinventing" advanced processing strategies that have originally been devised specifically for the Xquery domain, e.g., XPath step reordering, axis reversal, and path stitching. Performance assessments provide evidence that relational query engines are among the most versatile and efficient Xquery processors readily available today.
Till Westmann - One of the best experts on this subject based on the ideXlab platform.
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SIGMOD Conference - Graphical Xquery in the aqualogic data services platform
Proceedings of the 2010 international conference on Management of data - SIGMOD '10, 2010Co-Authors: Vinayak Borkar, Michael J. Carey, Sebu Koleth, Alexander Kotopoulis, Kautul Mehta, Joshua Spiegel, Sachin Thatte, Till WestmannAbstract:The AquaLogic Data Services Platform (ALDSP) is a middleware platform developed at BEA Systems for building services, referred to as data services, that integrate, access, and manipulate information coming from multiple heterogeneous sources of data (including databases, files, and other services). ALDSP uses functions that produce and consume XML to model heterogeneous information sources, so the integration logic for data access services in ALDSP is specified declaratively using the Xquery Language. A challenge that we faced in developing ALDSP was providing effective graphical tooling to help data service developers to develop information integration queries. In this paper, we describe the graphical Xquery Editor (XQE) that resulted from our attempt to tackle this challenge. XQE handles the full Xquery Language and provides a robust two-way editing experience involving both graphical and source views of each query. XQE is novel in being the first commercial graphical Xquery editor to support both of these features.
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ICDE - XQSE: An Xquery Scripting Extension for the AquaLogic Data Services Platform
2008 IEEE 24th International Conference on Data Engineering, 2008Co-Authors: Vinayak Borkar, Michael J. Carey, Till Westmann, Daniel Engovatov, Dmitry Lychagin, Warren WongAbstract:The AquaLogic Data Services Platform (ALDSP) is a BEA middleware platform for creating services that access and manipulate information drawn from multiple heterogeneous sources of data. The integration logic for read services is specified declaratively using the Xquery Language. ALDSP 3.0, available in December 2007, includes a new Xquery-based Scripting Extension - XQSE - that enables developers to write procedural as well as declarative logic without leaving the Xquery world. In this paper, we describe the XQSE extensions to Xquery and show how they help to support important new classes of data services in ALDSP 3.0.
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Experiences with Xquery Processing for Data and Service Federation.
IEEE Data(base) Engineering Bulletin, 2008Co-Authors: Michael Blow, Vinayak Borkar, Michael J. Carey, Joshua Spiegel, Daniel Engovatov, Dmitry Lychagin, Panagiotis Reveliotis, Till WestmannAbstract:In this paper, we describe our experiences in building and evolving an Xquery engine with a focus on data and service federation use cases. The engine that we discuss is a core component of the BEA AquaLogic Data Services Platform product (recently re-released under the name Oracle Data Service Integrator). This Xquery engine was designed to provide efficient query and update capabilities over various classes of enterprise data sources, serving as the data access layer in a service-oriented architecture (SOA). The goal of this paper is to give an architectural overview of the engine, discussing some of the key implementation techniques that were employed as well as several Xquery Language extensions that were introduced to address common data and service integration problems and challenges.
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the bea streaming Xquery processor
Very Large Data Bases, 2004Co-Authors: Daniela Florescu, Till Westmann, Chris Hillery, Donald Kossmann, Paul J Lucas, F Riccardi, J Carey, Arvind SundararajanAbstract:This paper describes the design, implementation, and performance characteristics of a commercial Xquery processing engine, the BEA streaming Xquery processor. This Xquery engine was designed to provide high performance for message-processing applications, i.e., for transforming XML data streams. The engine is a central component of the 8.1 release of BEA’s WebLogic Integration (WLI) product. The BEA Xquery engine is fully compliant with the August 2002 draft of the W3C XML Query Language specification and we are currently porting it to the latest version of the Xquery Language (July 2004). A goal of this paper is to describe how a fully compliant yet efficient Xquery engine has been built from a few relatively simple components and well-understood technologies.
Torsten Grust - One of the best experts on this subject based on the ideXlab platform.
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EDBT - Let SQL drive the Xquery workhorse (Xquery join graph isolation)
Proceedings of the 13th International Conference on Extending Database Technology - EDBT '10, 2010Co-Authors: Torsten Grust, Manuel Mayr, Jan RittingerAbstract:A purely relational account of the true Xquery semantics can turn any relational database system into an Xquery processor. Compiling nested expressions of the fully compositional Xquery Language, however, yields odd algebraic plan shapes featuring scattered distributions of join operators that currently overwhelm commercial SQL query optimizers. This work rewrites such plans before submission to the relational database back-end. Once cast into the shape of join graphs, we have found off-the-shelf relational query optimizers---the B-tree indexing subsystem and join tree planner, in particular---to cope and even be autonomously capable of "reinventing" advanced processing strategies that have originally been devised specifically for the Xquery domain, e.g., XPath step reordering, axis reversal, and path stitching. Performance assessments provide evidence that relational query engines are among the most versatile and efficient Xquery processors readily available today.
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ICDE - Xquery Join Graph Isolation: Celebrating 30+ Years of Xquery Processing Technology
2009 IEEE 25th International Conference on Data Engineering, 2009Co-Authors: Torsten Grust, Manuel Mayr, Jan RittingerAbstract:A purely relational account of the true Xquery semantics can turn any relational database system into an Xquery processor. Compiling nested expressions of the fully compositional Xquery Language, however, yields odd algebraic plan shapes featuring scattered distributions of join operators that currently overwhelm commercial SQL query optimizers. This work rewrites such plans before submission to the relational database back-end. Once cast into the shape of join graphs, we have found off-the-shelf relational query optimizers — the B-tree indexing subsystem and join tree planner, in particular — to cope and even be autonomously capable of "reinventing" advanced processing strategies that have originally been devised specifically for the Xquery domain, e.g., XPath step reordering, axis reversal, and path stitching. Performance assessments provide evidence that relational query engines are among the most versatile and efficient Xquery processors readily available today.
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Xquery Join Graph Isolation
arXiv: Databases, 2008Co-Authors: Torsten Grust, Manuel Mayr, Jan RittingerAbstract:A purely relational account of the true Xquery semantics can turn any relational database system into an Xquery processor. Compiling nested expressions of the fully compositional Xquery Language, however, yields odd algebraic plan shapes featuring scattered distributions of join operators that currently overwhelm commercial SQL query optimizers. This work rewrites such plans before submission to the relational database back-end. Once cast into the shape of join graphs, we have found off-the-shelf relational query optimizers--the B-tree indexing subsystem and join tree planner, in particular--to cope and even be autonomously capable of "reinventing" advanced processing strategies that have originally been devised specifically for the Xquery domain, e.g., XPath step reordering, axis reversal, and path stitching. Performance assessments provide evidence that relational query engines are among the most versatile and efficient Xquery processors readily available today.
