ArchIS: an XML-based approach to transaction-time temporal database systems

Effective support for temporal applications by database systems represents an important technical objective that is difficult to achieve since it requires an integrated solution for several problems, including (i) expressive temporal representations and data models, (ii) powerful languages for temporal queries and snapshot queries, (iii) indexing, clustering and query optimization techniques for managing temporal information efficiently, and (iv) architectures that bring together the different pieces of enabling technology into a robust system. In this paper, we present the ArchIS system that achieves these objectives by supporting a temporally grouped data model on top of RDBMS. ArchIS’ architecture uses (a) XML to support temporally grouped (virtual) representations of the database history, (b) XQuery to express powerful temporal queries on such views, (c) temporal clustering and indexing techniques for managing the actual historical data in a relational database, and (d) SQL/XML for executing the queries on the XML views as equivalent queries on the relational database. The performance studies presented in the paper show that ArchIS is quite effective at storing and retrieving under complex query conditions the transaction-time history of relational databases, and can also assure excellent storage efficiency by providing compression as an option. This approach achieves full-functionality transaction-time databases without requiring temporal extensions in XML or database standards, and provides critical support to emerging application areas such as RFID.     

一个XML的数据模型及其存储策略

XML是用于数据表示、交换的Internet标准。通过和DTD的连接可以用像XML－QL这样的语言来执行丰富的查询操作。近年来,很多人致力于半结构化数据模型和其查询语言的研究^[1,2,5],其重点逐渐转移到XML数据集的查询上来,其中两个重要问题是使XML查询语言正规化和如何将XML数据转换为底层存储格式以获得理想的效率^[4]。表述了一个XML的正规数据模型及其代数方法,并介绍基于RDBMS实现该模型的方法。     

XML keyword search with promising result type recommendations

Keyword search enables inexperienced users to easily search XML database with no specific knowledge of complex structured query languages and XML data schemas. Existing work has addressed the problem of selecting data nodes that match keywords and connecting them in a meaningful way, e.g., SLCA and ELCA. However, it is time-consuming and unnecessary to serve all the connected subtrees to the users because in general the users are only interested in part of the relevant results. In this paper, we propose a new keyword search approach which basically utilizes the statistics of underlying XML data to decide the promising result types and then quickly retrieves the corresponding results with the help of selected promising result types. To guarantee the quality of the selected promising result types, we measure the correlations between result types and a keyword query by analyzing the distribution of relevant keywords and their structures within the XML data to be searched. In addition, relevant result types can be efficiently computed without keyword query evaluation and any schema information. To directly return top-k keyword search results that conform to the suggested promising result types, we design two new algorithms to adapt to the structural sensitivity of the keyword nodes over the keyword search results. Lastly, we implement all proposed approaches and present the relevant experimental results to show the effectiveness of our approach.     

一种基于关键字的XML文档查询算法

对XML文档查询的常用方法有两种：一种是使用查询语言;另一种是使用关键字,而使用关键字查询XML文档比使用查询语言更为简单方便。给出了一种使用关键字查询XML文档的索引查找算法。该算法只需要扫描一次关键字对应的编码列,就可以找到需要的编码,提高了查询效率。实验表明该算法是可行的和有效的。     

Efficient recursive XML query processing using relational database systems

Recursive queries are quite important in the context of XML databases. In addition, several recent papers have investigated a relational approach to store XML data and there is growing evidence that schema-conscious approaches are a better option than schema-oblivious techniques as far as query performance is concerned. However, the issue of recursive XML queries for such approaches has not been dealt with satisfactorily. In this paper we argue that it is possible to design a schema-oblivious approach that outperforms schema-conscious approaches for certain types of recursive queries. To that end, we propose a novel schema-oblivious approach, called Sucxent++ (Schema Unconcious XML Enabled System), that outperforms existing schema-oblivious approaches such as XParent by up to 15 times and schema-conscious approaches (Shared-Inlining) by up to eight times for recursive query execution. Our approach has up to two times smaller storage requirements compared to existing schema-oblivious approaches and 10% less than schema-conscious techniques. In addition Sucxent++ performs marginally better than Shared-Inlining and is 5.7–47 times faster than XParent as far as insertion time is concerned.     

Benchmarking temporal database models with interval-based and temporal element-based timestamping

Starting from mid 1980s, there has been a debate about what data model is most appropriate for temporal databases. A fundamental choice one has to make is whether to use intervals of time or temporal elements to timestamp objects and events with the periods of validity. The advantage of using interval timestamps is that Start and End columns can be added to relations for treating them within the framework of classical databases, leading to quick implementation. Temporal elements are finite unions of intervals. The advantage of temporal elements is that timestamps become implicitly associated with values, tuples, and relations. Furthermore, since temporal elements, by design, are closed under set theoretical operations such as union, intersection and complementation, they lead to query languages that are natural. Here, we investigate the ease of use as well as system performance for the two approaches to help settle the debate.     

Efficiently Querying Large XML Data Repositories: A Survey

Extensible markup language (XML) is emerging as a de facto standard for information exchange among various applications on the World Wide Web. There has been a growing need for developing high-performance techniques to query large XML data repositories efficiently. One important problem in XML query processing is twig pattern matching, that is, finding in an XML data tree D all matches that satisfy a specified twig (or path) query pattern Q. In this survey, we review, classify, and compare major techniques for twig pattern matching. Specifically, we consider two classes of major XML query processing techniques: the relational approach and the native approach. The relational approach directly utilizes existing relational database systems to store and query XML data, which enables the use of all important techniques that have been developed for relational databases, whereas in the native approach, specialized storage and query processing systems tailored for XML data are developed from scratch to further improve XML query performance. As implied by existing work, XML data querying and management are developing in the direction of integrating the relational approach with the native approach, which could result in higher query processing performance and also significantly reduce system reengineering costs.     

An XML-based methodology for parametric temporal database model implementation

Parametric data model is one of dimensional data models. It defines attributes as functions, modeling a real world object into a single tuple in a database. Such one-to-one correspondence between an object in the real world and a tuple provides various advantages in modeling dimensional data, avoiding self-joins which frequently appear in temporal data models which fragment an object into multiple tuples. Despite its modeling advantages, it is impractical to implement the parametric data model on top of conventional database systems because of the data model’s variable attribute sizes. However, such implementation challenge can be resolved by XML because XML is flexible for data boundaries. In this paper, we present an XML-based implementation methodology for the parametric temporal data model. In our implementation, we develop our own XML storage called CanStoreX (Canonical Storage for XML) and build the temporal database system on top of the CanStoreX.     

Navigational accesses in a temporal object model

A considerable research effort has been devoted in past years to query languages for temporal data in the context of both the relational and the object oriented model. Object oriented databases provide a navigational approach for data access based on object references. We investigate the navigational approach to querying object oriented databases. We formally define the notion of temporal path expression, and we address on a formal basis issues related to the correctness of such expressions. In particular, we focus on static analysis and give a set of conditions ensuring that an expression always results in a correct access at runtime     

Rule-based composite event queries: the language XChangeEQ and its semantics

Web systems, Web services, and Web-based publish/subscribe systems communicate events as XML messages and in many cases, require composite event detection: it is not sufficient to react to single event messages, but events have to be considered in relation to other events that are received over time. This entails a need for expressive, high-level languages for querying composite events. Emphasizing language design and formal semantics, we describe the rule-based composite event query language XChange^EQ. XChange^EQ is designed to completely cover and integrate the four complementary querying dimensions: event data, event composition, temporal relationships, and event accumulation. Semantics are provided as a model theory with accompanying fixpoint theory, an approach that is established for rule languages but has not been applied to event queries so far. Because they are highly declarative, thus easy to understand and well suited for query optimization, such semantics are desirable for event queries.     

Expressiveness of temporal query languages: on the modelling of intervals, interval relationships and states

Storing and retrieving time-related information are important, or even critical, tasks on many areas of computer science (CS) and in particular for artificial intelligence (AI). The expressive power of temporal databases/query languages has been studied from different perspectives, but the kind of temporal information they are able to store and retrieve is not always conveniently addressed. Here we assess a number of temporal query languages with respect to the modelling of time intervals, interval relationships and states, which can be thought of as the building blocks to represent and reason about a large and important class of historic information. To survey the facilities and issues which are particular to certain temporal query languages not only gives an idea about how useful they can be in particular contexts, but also gives an interesting insight in how these issues are, in many cases, ultimately inherent to the database paradigm. While in the area of AI declarative languages are usually the preferred choice, other areas of CS heavily rely on the extended relational paradigm. This paper, then, will be concerned with the representation of historic information in two well known temporal query languages: Templog in the context of temporal deductive databases, and TSQL2 in the context of temporal relational databases. We hope the results highlighted here will increase cross-fertilisation between different communities. This article can be related to recent publications drawing the attention towards the different approaches followed by the Databases and AI communities when using time-related concepts.     

基于关系数据库有效地实现RPE查询

各种XML查询语言的共同特点就是利用正则路径表达式(RPE)来导航XML文档的查询。本文结合我们提出的一种新的XML数据的关系存储模式，对有效地实现RPE查询的相关研究工作进行了总结，并提出了两个有效地实现包含连接的索引改进归并连接算法。算法采用索引定位技术、短路技术和预侦技术来减少连接代价。因此，不仅能够在当前上下文计算环境下有效地实现包含连接的计算，而且能够大量地避免包含连接中不必要的扫描和搜索。     

Answering XML Queries Using Path-Based Indexes: A Survey

The problem of answering XML queries using path-based indexes is to find efficient methods for accelerating the XML query with pre-designed index structures over the XML database. This problem received increasing interests and have been lucubrated in recent years. Regular path expression is the core of the XML query languages e.g., XPath and XQuery. Most of the state-of-the-art path-based XML indexes, therefore, hammer at how to efficiently answer the path-based XML queries. This paper surveys various approaches to indexing XML data proposed in the literature. We give a step by step analysis to show the evolution of index structures for XML path information, based on tree structures or more commonly, directed labeled graphs. For each approach, we first present the specific issue it aims to tackle, and then the proposed solution presented. Furthermore, construction, physical data storage and maintenance costs, are analyzed.     

Efficient processing of XPath queries using indexes

A number of indexing techniques have been proposed in recent times for optimizing the queries on XML and other semi-structured data models. Most of the semi-structured models use tree-like structures and query languages (XPath, XQuery, etc.) which make use of regular path expressions to optimize the query processing. In this paper, we propose two algorithms called Entry-point algorithm (EPA) and Two-point Entry algorithms that exploit different types of indices to efficiently process XPath queries. We discuss and compare two approaches namely, Root-first and Bottom-first in implementing the EPA. We present the experimental results of the algorithms using XML benchmark queries and data and compare the results with that of traditional methods of query processing with and without the use of indexes, and ToXin indexing approach. Our algorithms show improved performance results than the traditional methods and Toxin indexing approach.     

Temporal XML: modeling, indexing, and query processing

In this paper we address the problem of modeling and implementing temporal data in XML. We propose a data model for tracking historical information in an XML document and for recovering the state of the document as of any given time. We study the temporal constraints imposed by the data model, and present algorithms for validating a temporal XML document against these constraints, along with methods for fixing inconsistent documents. In addition, we discuss different ways of mapping the abstract representation into a temporal XML document, and introduce TXPath, a temporal XML query language that extends XPath 2.0. In the second part of the paper, we present our approach for summarizing and indexing temporal XML documents. In particular we show that by indexing continuous paths, i.e., paths that are valid continuously during a certain interval in a temporal XML graph, we can dramatically increase query performance. To achieve this, we introduce a new class of summaries, denoted TSummary, that adds the time dimension to the well-known path summarization schemes. Within this framework, we present two new summaries: LCP and Interval summaries. The indexing scheme, denoted TempIndex, integrates these summaries with additional data structures. We give a query processing strategy based on TempIndex and a type of ancestor-descendant encoding, denoted temporal interval encoding. We present a persistent implementation of TempIndex, and a comparison against a system based on a non-temporal path index, and one based on DOM. Finally, we sketch a language for updates, and show that the cost of updating the index is compatible with real-world requirements.     

Temporal Connectives versus Explicit Timestamps to Query Temporal Databases

Temporal databases can be queried either by query languages working directly on a timestamp representation or by languages using an implicit access to time via temporal connectives. We study the differences in expressive power between these two approaches. First, we consider temporal and first-order logic. We show that future temporal logic is strictly less powerful than past–future temporal logic and also that there are queries expressible in first-order logic with explicit timestamps that are not expressible in extended temporal logic. Our proof technique is novel and based on communication complexity. Then, we consider extensions of first-order logic with fixpoints or while-loops. Again the explicit temporal version of these languages, using timestamps, is compared with an implicit one, using instructions for moving in time. We also compare the temporal versions of the fixpoint language with those of the while language.     

Consistent query answers from virtually integrated XML data

When data sources are virtually integrated, there is no common and centralized method to maintain global consistency, so inconsistencies with regard to global integrity constraints are very likely to occur. In this paper, we consider the problem of defining and computing consistent query answers when queries are posed to virtual XML data integration systems, which are specified following the local-as-view approach. We propose a powerful XML constraint model to define global constraints, which can express keys and functional dependencies, and which also extends the newly introduced conditional functional dependencies to XML. We provide an approach to defining XML views, which supports not only edge-path mappings but also data-value bindings to express the join operator. We give formal definitions of repair and consistent query answers with the XML data integration settings. Given a query on the global system, we present a two-step method to compute consistent query answers. First, the given query is transformed using the global constraints, such that to run the transformed query on the original global system will generate exactly the consistent query answers. Because the global instance is not materialized, the query on the global instance is then rewritten in the form of queries on the underlying data sources by reversing rules in view definitions. We illustrate that the XPath query transformations can be implemented in XQuery. Finally, we implement prototypes of our method and evaluate our algorithms in the experiments.     

A Query Language for XML Based on Graph Grammars

In this paper we present a graphical query language for XML. The language, based on a simple form of graph grammars, permits us to extract data and reorganize information in a new structure. As with most of the current query languages for XML, queries consist of two parts: one extracting a subgraph and one constructing the output graph. The semantics of queries is given in terms of graph grammars. The use of graph grammars makes it possible to define, in a simple way, the structural properties of both the subgraph that has to be extracted and the graph that has to be constructed. We provide an example-driven comparison of our language w.r.t. other XML query languages, and show the effectiveness and simplicity of our approach.     

Constraint-based Interoperability of Spatiotemporal Databases*

We propose constraint databases as an intermediate level facilitating the interoperability of spatiotemporal data models. Constraint query languages are used to express translations between different data models. We illustrate our approach in the context of a number of temporal, spatial, and spatiotemporal data models.     

Current approaches to XML management

The Extensible Markup Language has become the standard for information interchange on the Web. We study the data- and document-centric uses of XML management systems (XMLMS). We want to provide XML data users with a guideline for choosing the data management system that best meets their needs. Because the systems we test are first-generation approaches, we suggest a hypothetical design for a useful XML database that could use all the expressive power of XML and XML query languages.