The Pathfinder XQuery compiler has been enhanced by a new code generator that can target any SQL:1999-compliant relational database system (RDBMS). This code generator marks an important next step towards truly relational XQuery processing, a branch of database technology that aims to turn RDBMSs into highly efficient XML and XQuery processors without the need to invade the relational database kernel. Pathfinder, a retargetable front-end compiler, translates input XQuery expressions into DAG-shaped relational algebra plans. The code generator then turns these plans into sequences of either SQL:1999 statements or view definitions which jointly implement the (sometimes intricate) XQuery semantics. In a sense, this demonstration thus lets relational algebra and SQL swap their traditional roles in database query processing. The result is a code generator that (1) supports an almost complete dialect of XQuery, (2) can target any RDBMS with a SQL:1999 language interface, and (3) exhibits quite promising performance characteristics when run against high-volume XML data as well as complex XQuery expressions.

Abstract—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 traditional query languages for XML and RDF, focused on emerging preeminent exemplars in each field, and contrasts these languages with the field of keyword querying for XML and RDF. I.

We demonstrate an efficient LINQ to SQL provider and its significant impact on the runtime performance of LINQ programs that process large data volumes. This alternative provider is based on Ferry, compilation technology that lets relational database systems participate in the evaluation of first-order functional programs over nested, ordered data structures. The Ferry-based provider seamlessly hooks into the.NET LINQ framework and generates SQL code that strictly adheres to the semantics of the LINQ data model. Ferry comes with strong code size guarantees and complete support for the LINQ Standard Query Operator family, enabling a truly interactive and compelling LINQ demonstration. A variety of inspection holes may be opened to learn about the internals of the Ferry-based LINQ to SQL provider. 1. SINGLE-LINE CHANGE—BIG IMPACT “Will we be able to defeat the Bs this time? ” This can be a pressing question if you are the coach of team A. You peer at the large players table of this year’s Basketball season (Table 1), featuring the player data of all teams. A list of the individual team rosters and a classification of a team’s players by their position— center, forward, or guard—would be more helpful now. You reach for your laptop computer to start the C # development environment. A brief program, formulated using the.NET Framework’s Language Integrated Query facility (LINQ), will do the job. You quickly create a data context, a LINQ abstraction that represents (1) a connection to a relational database back-end as well as (2) selected tables hosted by this back-end (including table players). players team name pos eff

There has been a lot of research and industrial effort on building XQuery engines with different kinds of XML storage and index models. However, most of these efforts focus on building either an efficient XQuery engine with one kind of XML storage, index, view model in mind or a general XQuery engine without any consideration of the underlying XML storage, index and view model. We need an underlying framework to build an XQuery engine that can work with and provide optimization for different XML storage, index and view models. Besides XQuery, RDBMSs also support SQL/XML, a standard language that integrates XML and relational processing. There are industrial efforts for building hybrid XQuery and SQL/XML engines that support both languages so that users can manage and query both relational and XML data on one platform. However, we need a theoretical framework to optimize both SQL/XML and XQuery languages in one RDBMS. In this paper, we show our industrial work of building a combined XQuery and SQL/XML engine that is able to work and provide optimization for different kinds of XML storage and index models in Oracle XMLDB. This work is based on XML extended relational algebra as the underlying tuple-based logical algebra and incorporates tree and automata based physical algebra into the logical tuple-based algebra so as to provide optimization for different physical XML formulations. This results in logical and physical rewrite techniques to optimize XQuery and SQL/XML over a variety of physical XML storage, index and view models, including schema aware object relational XML storage with relational indexes, binary XML storage with schema agnostic path-value-order key XMLIndex, SQL/XML view over relational data and relational view over XML. Furthermore, we show the approach of leveraging cost based XML physical rewrite strategy to evaluate different physical rewrite plans. 1.

We introduce a controlled form of recursion in XQuery, an inflationary fixed point operator, familiar from the context of relational databases. This operator imposes restrictions on the expressible types of recursion, but we show that it is sufficiently versatile to capture a wide range of interesting use cases, including Regular XPath and its core transitive closure operator. While the optimization of general user-defined recursive functions in XQuery appears elusive, we describe how inflationary fixed points can be efficiently evaluated, provided that the recursive XQuery expressions are distributive. We test distributivity syntactically and algebraically, and provide experimental evidence that XQuery processors can benefit substantially from this mode of evaluation.

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.

We introduce a controlled form of recursion in XQuery, an inflationary fixed point operator, familiar from the context of relational databases. This operator imposes restrictions on the expressible types of recursion, but it is sufficiently versatile to capture a wide range of interesting use cases, including Regular XPath and its core transitive closure operator. While the optimization of general user-defined recursive functions in XQuery appears elusive, we describe how inflationary fixed points can be efficiently evaluated, provided that the recursive XQuery expressions are distributive. We test distributivity syntactically and algebraically, and provide experimental evidence that XQuery processors can benefit substantially from this mode of evaluation. 1.

XML has been explored by both research and industry communities. More than 5500 papers were published on different aspects of XML. With so many publications, it is hard for someone to decide where to start. Hence, this paper presents some of the research topics on XML, namely: XML on relational databases, query processing, views, data matching, and schema evolution. It then summarizes some (some!) of the most relevant or traditional papers on those subjects. 1.

Early approaches to XQuery processing proposed proprietary techniques to optimize and evaluate XQuery statements. In this chapter, we argue for an algebraic optimization and evaluation technique for XQuery as it allows us to benefit from experience gained with relational databases. An algebraic XQuery processing method requires a translation into an algebra representation. While many publications already exist on algebraic optimizations and evaluation techniques for XQuery, an assessment of translation techniques is required. Consequently, we give a comprehensive survey for translating XQuery into various query representations. We relate these approaches to the way normalization and translation is implemented in Natix and discuss these two steps in detail. In our experience, our translation method is a good basis for further optimizations and query evaluation.

Abstract—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 traditional query languages for XML and RDF, focused on emerging preeminent exemplars in each field, and contrasts these languages with the field of keyword querying for XML and RDF. I.