Our experimental analysis of several popular XPath processors reveals a striking fact: Query evaluation in each of the systems requires time exponential in the size of queries in the worst case. We show that XPath can be processed much more efficiently, and propose main-memory algorithms for this problem with polynomial-time combined query evaluation complexity. Moreover, we present two fragments of XPath for which linear-time query processing algorithms exist. 1

... In this paper we first describe the XFilter and YFilter approaches and present results of a detailed performance comparison of structure matching for these algorithms as well as a hybrid approach. The results show that the path sharing employed by YFilter can provide order-of-magnitude performance benefits. We then propose two alternative techniques for extending YFilter's shared structure matching with support for valuebased predicates, and compare the performance of these two techniques. The results of this latter study demonstrate some key differences between shared XML filtering and traditional database query processing. Finally, we describe how the YFilter approach is extended to handle more complicated queries containing nested path expressions.

We present the design and implementation of the XSQ system for querying streaming XML data using XPath 1.0. Using a clean design based on a hierarchical arrangement of pushdown transducers augmented with buffers, XSQ supports features such as multiple predicates, closures, and aggregation. XSQ not only provides high throughput, but is also memory ef£cient: It buffers only data that must be buffered by any streaming XPath processor. We also present an empirical study of the performance characteristics of XPath features, as embodied by XSQ and several other systems.

Publish/subscribe systems have demonstrated the ability to scale to large numbers of users and high data rates when providing content-based data dissemination services on the Internet. However, their services are limited by the data semantics and query expressiveness that they support. On the other hand, the recent work on selective dissemination of XML data has made significant progress in moving from XML filtering to the richer functionality of transformation for result customization, but in general has ignored the challenges of deploying such XML-based services on an Internet-scale. In this paper, we address these challenges in the context of incorporating the rich functionality of XML data dissemination in a highly scalable system. We present the architectural design of ONYX, a system based on an overlay network. We identify the salient technical challenges in supporting XML filtering and transformation in this environment and propose techniques for solving them.

The XML Stream Machine (XSM) system is a novel XQuery processing paradigm that is tuned to the efficient processing of sequentially accessed XML data (streams). The system compiles a given XQuery into an XSM, which is an XML stream transducer, i.e., an abstract device that takes as input one or more XML data streams and produces one or more output streams, potentially using internal buffers. We present a systematic way to translate XQueries into efficient XSMs: First the XQuery is translated into a network of XSMs that correspond to the basic operators of the XQuery language and exchange streams. The network is reduced to a single XSM by repeated application of an XSM composition operation that is optimized to reduce the number of tests and actions that the XSM performs as well as the number of intermediate buffers that it uses. Finally, the optimized XSM is compiled into a C program. First empirical results illustrate the performance benefits of the XSM-based processor.

We introduce an extension of the XQuery language, FluX, that supports event-based query processing and the conscious handling of main memory buffers. Purely event-based queries of this language can be executed on streaming XML data in a very direct way. We then develop an algorithm that allows to efficiently rewrite XQueries into the event-based FluX language. This algorithm uses order constraints from a DTD to schedule event handlers and to thus minimize the amount of buffering required for evaluating a query. We discuss the various technical aspects of query optimization and query evaluation within our framework. This is complemented with an experimental evaluation of our approach.

Abstract. Traditional content based publish/subscribe (pub/sub) systems allow users to express stateless subscriptions evaluated on individual events. However, many applications such as monitoring RSS streams, stock tickers, or management of RFID data streams require the ability to handle stateful subscriptions. In this paper, we introduce Cayuga, a stateful pub/sub system based on nondeterministic finite state automata (NFA). Cayuga allows users to express subscriptions that span multiple events, and it supports powerful language features such as parameterization and aggregation, which significantly extend the expressive power of standard pub/sub systems. Based on a set of formally defined language operators, the subscription language of Cayuga provides non-ambiguous subscription semantics as well as unique opportunities for optimizations. We experimentally demonstrate that common optimization techniques used in NFA-based systems such as state merging have only limited effectiveness, and we propose novel efficient indexing methods to speed up subscription processing. In a thorough experimental evaluation we show the efficacy of our approach. 1

We propose the model of nested words for representation of data with both a linear ordering and a hierarchically nested matching of items. Examples of data with such dual linear-hierarchical structure include executions of structured programs, annotated linguistic data, and HTML/XML documents. Nested words generalize both words and ordered trees, and allow both word and tree operations. We define nested word automata—finite-state acceptors for nested words, and show that the resulting class of regular languages of nested words has all the appealing theoretical properties that the classical regular word languages enjoys: deterministic nested word automata are as expressive as their nondeterministic counterparts; the class is closed under union, intersection, complementation, concatenation, Kleene-*, prefixes, and language homomorphisms; membership, emptiness, language inclusion, and language equivalence are all decidable; and definability in monadic second order logic corresponds exactly to finite-state recognizability. We also consider regular languages of infinite nested words and show that the closure properties, MSO-characterization, and decidability of decision problems carry over. The linear encodings of nested words give the class of visibly pushdown languages of words, and this class lies between balanced languages and deterministic context-free languages. We argue that for algorithmic verification of structured programs, instead of viewing the program as a context-free language over words, one should view it as a regular language of nested words (or equivalently, a visibly pushdown language), and this would allow model checking of many properties (such as stack inspection, pre-post conditions) that are not expressible in existing specification logics. We also study the relationship between ordered trees and nested words, and the corresponding automata: while the analysis complexity of nested word automata is the same as that of classical tree automata, they combine both bottom-up and top-down traversals, and enjoy expressiveness and succinctness benefits over tree automata. 1

The important challenge of evaluating XPath queries over XML streams has sparked much interest in the past few years. A number of algorithms have been proposed, supporting wider fragments of the query language, and exhibiting better performance and memory utilization. Nevertheless, all the algorithms known to date use a prohibitively large amount of memory for certain types of queries. A natural question then is whether this memory bottleneck is inherent or just an artifact of the proposed algorithms. In this paper we initiate the first systematic and theoretical study of lower bounds on the amount of memory required to evaluate XPath queries over XML streams. We present a general lower bound technique, which given a query, specifies the minimum amount of memory that any algorithm evaluating the query on a stream would need to incur. The lower bounds are stated in terms of new graph-theoretic properties of queries. The proofs are based on tools from communication complexity. We then exploit insights learned from the lower bounds to obtain a new algorithm for XPath evaluation on streams. The algorithm uses space close to the optimum. Our algorithm deviates from the standard paradigm of using automata or transducers, thereby avoiding the need to store large transition tables. 1

We propose a new, highly scalable and efficient technique for evaluating node-selecting queries on XML trees which is based on recent advances in the theory of tree automata. Our query