MonetDB/XQuery: a fast XQuery processor powered by a relational engine

Relational XQuery systems try to re-use mature relational data management infrastructures to create fast and scalable XML database technology. This paper describes the main features, key contributions, and lessons learned while implementing such a system. Its architecture consists of (i) a range-based encoding of XML documents into relational tables, (ii) a compilation technique that translates XQuery into a basic relational algebra, (iii) a restricted (order) property-aware peephole relational query optimization strategy, and (iv) a mapping from XML update statements into relational updates. Thus, this system implements all essential XML database functionalities (rather than a single feature) such that we can learn from the full consequences of our architectural decisions. While implementing this system, we had to extend the state-of-the-art with a number of new technical contributions, such as loop-lifted staircase join and efficient relational query evaluation strategies for XQuery theta-joins with existential semantics. These contributions as well as the architectural lessons learned are also deemed valuable for other relational back-end engines. The performance and scalability of the resulting system is evaluated on the XMark benchmark up to data sizes of 11GB. The performance section also provides an extensive benchmark comparison of all major XMark results published previously, which confirm that the goal of purely relational XQuery processing, namely speed and scalability, was met

Pathfinder: XQuery - The Relational Way

Relational query processors are probably the best understood (as well as the best engineered) query engines available today. Although carefully tuned to process instances of the relational model (tables of tuples), these processors can also provide a foundation for the evaluation of "alien" (non-relational) query languages: if a relational encoding of the alien data model and its associated query language is given, the RDBMS may act like a special-purpose processor for the new language

An Inflationary Fixed Point Operator in XQuery

We introduce a controlled form of recursion in XQuery, inflationary fixed points, familiar in the context of relational databases. This imposes restrictions on the expressible types of recursion, but we show that inflationary fixed points nevertheless are sufficiently versatile to capture a wide range of interesting use cases, including the semantics of Regular XPath and its core transitive closure construct. While the optimization of general user-defined recursive functions in XQuery appears elusive, we will describe how inflationary fixed points can be efficiently evaluated, provided that the recursive XQuery expressions exhibit a distributivity property. We show how distributivity can be assessed both, syntactically and algebraically, and provide experimental evidence that XQuery processors can substantially benefit during inflationary fixed point evaluation.Comment: 11 pages, 10 figures, 2 table

06472 Abstracts Collection - XQuery Implementation Paradigms

From 19.11.2006 to 22.11.2006, the Dagstuhl Seminar 06472 ``XQuery Implementation Paradigms'' was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

A Programming Language for Web Service Development

There is now widespread acceptance of Web services and service-oriented architectures. But despite the agreement on key Web services standards there remain many challenges. Programming environments based on WSDL support go some way to facilitating Web service development. However Web services fundamentally rely on XML and Schema, not on contemporary programming language type systems such as those of Java or .NET. Moreover, Web services are based on a messaging paradigm and hence bring forward the traditional problems of messaging systems including concurrency control and message correlation. It is easy to write simple synchronous Web services using traditional programming languages; however more realistic scenarios are surprisingly difficult to implement. To alleviate these issues we propose a programming language which directly supports Web service development. The language leverages XQuery for native XML processing, supports implicit message correlation and has high level join calculus-style concurrency control. We illustrate the features of the language through a motivating example

MonetDB/XQuery - Consistent & Efficient Updates on the Pre/Post Plane

Relational XQuery processors aim at leveraging mature relational DBMS query processing technology to provide scalability and efficiency. To achieve this goal, various storage schemes have been proposed to encode the tree structure of XML documents in flat relational tables. Basically, two classes can be identified: (1) encodings using fixed-length surrogates, like the preorder ranks in the pre/post encoding [5] or the equivalent pre/size/level encoding [8], and (2) encodings using variable-length surrogates, like, e.g., ORDPATH [9] or P-PBiTree [12]. Recent research [1] showed a clear advantage of the former for efficient evaluation of XPath location steps, exploiting techniques like cheap node order tests, positional lookup, and node skipping in staircase join [7]. However, once updates are involved, variable-length surrogates are often considered the better choice, mainly as a straightforward implementation of structural XML updates using fixed-length surrogates faces two performance bottlenecks: (i) high physical cost (the preorder ranks of all nodes following the update position must be modified—on average 50% of the document), and (ii) low transaction concurrency (updating the size of all ancestor nodes causes lock contention on the document root)

AsterixDB: A Scalable, Open Source BDMS

AsterixDB is a new, full-function BDMS (Big Data Management System) with a feature set that distinguishes it from other platforms in today's open source Big Data ecosystem. Its features make it well-suited to applications like web data warehousing, social data storage and analysis, and other use cases related to Big Data. AsterixDB has a flexible NoSQL style data model; a query language that supports a wide range of queries; a scalable runtime; partitioned, LSM-based data storage and indexing (including B+-tree, R-tree, and text indexes); support for external as well as natively stored data; a rich set of built-in types; support for fuzzy, spatial, and temporal types and queries; a built-in notion of data feeds for ingestion of data; and transaction support akin to that of a NoSQL store. Development of AsterixDB began in 2009 and led to a mid-2013 initial open source release. This paper is the first complete description of the resulting open source AsterixDB system. Covered herein are the system's data model, its query language, and its software architecture. Also included are a summary of the current status of the project and a first glimpse into how AsterixDB performs when compared to alternative technologies, including a parallel relational DBMS, a popular NoSQL store, and a popular Hadoop-based SQL data analytics platform, for things that both technologies can do. Also included is a brief description of some initial trials that the system has undergone and the lessons learned (and plans laid) based on those early "customer" engagements