时态查询语言对处理不明确时间间隔的扩展

关于时态数据库的先前工作，主要是建立在时态属性的时间间隔和事件的开始／终止点都十分清楚的基础上，然而，在许多实际情况中，事件的时间界限并不十分清楚。因此，表示不明确时间，并给出处理不明确时间查询的方法，是对时态数据库中目前仍缺少的一个有效的扩展。讨论了时态数据库处理不明确时间存在的一些问题，并描述不明确时间隔的方法，之后扩展了各种时态运算，并给出了与不明确时间相关的新运算符。也提出了能够处理不明确时间的查询语言扩展。在此讨论的时是询语言对处理不明确时间间隔的扩展和丰富时态数据库的适应性有一定作用。     

不明确时间间隔的表示及时态运算的扩展

讨论了时态数据库处理不明确时间存在的一些问题，并给出描述不明确时间间隔的表示方法，在此基础上给出了各种时态运算的扩展，丰富了时态数据库的适应性。     

Time-based operators for relational algebra query languages

We present a new approach for historical relational algebra languages based upon generalized logic for Boolean and comparison operators and a temporal modification of the standard relational algebra operators. Historical versions of standard (snapshot) relational algebra operators based upon this generalized logic are presented. The temporal modification employs a logic that operates on sets of value/time-interval pairs and which can be applied to snapshot as well as historical databases. Our emphasis is that the generalized operators can be used to enrich existing historical query languages and to provide an easier and more natural time-based interface. Using the generalized operators, users can express their queries more naturally, succinctly and elegantly. Examples are presented which illustrate that the modified operators offer a good degree of flexibility in expressing different temporal requirements.     

RQL: a recursive query language

Different classes of recursive queries in the relational databases are identified. It is shown that existing proposals to extend the relational query languages are either not powerful enough to express queries in many of these classes or use nonfirst normal form constructs. RQL, a recursive database query language that can be used to express recursive queries on all the classes identified, is presented. RQL is based on the relational algebra. In addition to functions that correspond to the standard and extended relational algebra operators, RQL supports functions required to express general recursive queries. The elements of RQL and the ways in which they are used to formulate complicated, but useful, recursive queries are described. The effects of the extensions embodied in RQL on the termination of recursive query evaluation are discussed     

Temporal Coupling Verification in Time Series Databases

Time series are often generated by continuous sampling or measurement of natural or social phenomena. In many cases, events cannot be represented by individual records, but instead must be represented by time series segments (temporal intervals). A consequence of this segment-based approach is that the analysis of events is reduced to analysis of occurrences of time series patterns that match segments representing the events.A major obstacle on the path toward event analysis is the lack of query languages for expressing interesting time series patterns. We have introduced SQL/LPP (Perng and Parker, 1999). Which provides fairly strong expressive power for time series pattern queries, and are now able to attack the problem of specifying queries that analyze temporal coupling, i.e., temporal relationships obeyed by occurrences of two or more patterns.In this paper, we propose SQL/LPP+, a temporal coupling verification language for time series databases. Based on the pattern definition language of SQL/LPP (Perng and Parker, 1999), SQL/LPP+ enables users to specify a query that looks for occurrences of a cascade of multiple patterns using one or more of Allen's temporal relationships (Allen, 1983) and obtain desired aggregates or meta-aggregates of the composition. Issues of pattern composition control are also discussed.     

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.     

不确定时态信息表示及时态运算的扩展

时态信息表示和查询是时态数据库的研究重点,但现有的时态数据库模型在处理不确定时态信息方面仍存在较大困难。而现实生活中很多时态信息都是不确定的,故提出了一种不确定时态信息的表示方法,并扩展时态运算使其支持不确定时态信息的处理和查询,从而扩展了时态数据库的适用范围。     

A foundation for conventional and temporal query optimizationaddressing duplicates and ordering

Most real-world databases contain substantial amounts of time-referenced, or temporal, data. Recent advances in temporal query languages show that such database applications may benefit substantially from built-in temporal support in the DBMS. To achieve this, temporal query representation, optimization, and processing mechanisms must be provided. This paper presents a foundation for query optimization that integrates conventional and temporal query optimization and is suitable for both conventional DBMS architectures and ones where the temporal support is obtained via a layer on top of a conventional DBMS. This foundation captures duplicates and ordering for all queries, as well as coalescing for temporal queries, thus generalizing all existing approaches known to the authors. It includes a temporally extended relational algebra to which SQL and temporal SQL queries may be mapped, six types of algebraic equivalences, concrete query transformation rules that obey different equivalences, a procedure for determining which types of transformation rules are applicable for optimizing a query, and a query plan enumeration algorithm     

Incomplete deductive databases

We investigate the complexity of query processing in databases which have both incompletely specified data and deductive rules. The paper is divided into two parts: in the first we consider databases in which incompletely specified data occurs only in the database intension; in the second we consider databases in which incomplete information is represented only in database extension. We prove that, in general, the query processing problem for databases with incomplete intensions is undecidable. A number of classes of rules for which all conjunctive queries can be processed in polynomial time is then characterized. For databases with incomplete extensions we prove a number of CoNP completeness results. For instance, we demonstrate that processing disjunctions which are restricted to individual columns of database predicates can, in general, be as bad as processing arbitrary disjunctions (i.e. CoNP-complete). This falsifies the conjecture that such limited disjunctions could be computationally beneficial. We also show two simple examples of situations in which query processing is guaranteed to be polynomial. These situations are linked to certain assumptions about database updates.Finally, we provide a summary of the data complexity of queries depending on the type of database extension, intension, query sublanguage and Open World vs Closed World assumption.Research supported by NSF grant DCR 85-04140.More precisely, we can say this only in the presence of the closed world assumption [18].     

Incremental computation of time-varying query expressions

We present and analyze algorithms for the incremental computation of time-varying queries in which selection predicates refer to the state of a clock. Such queries occur naturally in many situations where temporal data are processed. Incremental techniques for query computation have proven to be more efficient than other techniques in many situations. However, all existing incremental techniques for query computation assume that old query results remain valid if no intermediate changes are made to the underlying database. Unfortunately, this assumption does not hold for time-varying queries whose results may change just because time passes. In order to solve this problem, we introduce the notion of a superview which contains all current tuples that will eventually satisfy the selection predicate of a time-varying selection. Based on the notion of superview, we develop efficient algorithms for the incremental computation of time-varying selections. Our algorithms, combined with existing incremental algorithms, allow complex time-varying queries to benefit from the proven efficiency of incremental techniques. It is important to notice that without our algorithms, the existing algorithms for incremental computation would be useless for any time-varying query expression     

Query rewriting using views in the presence of functional and inclusion dependencies

Query rewriting using views is a technique for determining how a query may be answered using a given set of resources, which may include materialized views, cached results of previous queries, or queries answerable by other databases. The power of query rewriting can be considerably enhanced by taking into account integrity constraints that are known to hold on base relations. This paper describes an extension of query rewriting that utilizes inclusion dependencies to find rewritings of queries that would otherwise be overlooked. We describe a complete strategy for finding rewritings in the presence of inclusion dependencies and present a basic algorithm that implements that strategy. We also describe extensions to this algorithm when both inclusion and functional dependencies are considered.     

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.     

Reachability and connectivity queries in constraint databases

It is known that standard query languages for constraint databases lack the power to express connectivity properties. Such properties are important in the context of geographical databases, where one naturally wishes to ask queries about connectivity (What are the connected components of a given set?) or reachability (Is there a path from A to B that lies entirely in a given region?). No existing constraint query languages that allow closed-form evaluation can express these properties. In the first part of the paper, we show that, in principle, there is no obstacle to getting closed languages that can express connectivity and reachability queries. In fact, we show that adding any topological property to standard languages like FO+Lin and FO+Poly results in a closed language. In the second part of the paper, we look for tractable closed languages for expressing reachability and connectivity queries. We introduce path logic, which allows one to state properties of paths with respect to given regions. We show that it is closed, has polynomial time data complexity for linear and polynomial constraints, and can express a large number of reachability properties beyond simple connectivity. Query evaluation in the logic involves obtaining a discrete abstraction of a continuous path, and model-checking of temporal formulae on the discrete structure.     

Indexing range sum queries in spatio-temporal databases

Although spatio-temporal databases have received considerable attention recently, there has been little work on processing range sum queries on the historical records of moving objects despite their importance. Since the direct access to a huge amount of data to answer range sum queries incurs prohibitive computation cost, materialization techniques based on existing index structures are suggested. A simple but effective solution is to apply the materialization technique to the MVR-tree known as the most efficient structure for window queries with spatio-temporal conditions. Aggregate structures based on other index structures such as the HR-tree and the 3DR-tree do not provide satisfactory query performance. In this paper, we propose a new index structure called the Adaptively Partitioned Aggregate R-Tree (APART) and query processing algorithms to efficiently process range sum queries in many situations. Our experimental results show that the performance of the APART is typically 1.3 times better than that of its competitor for a wide range of scenarios.     

On the decidability of termination of query evaluation in transitive-closure logics for polynomial constraint databases

The formalism of constraint databases, in which possibly infinite data sets are described by Boolean combinations of polynomial inequality and equality constraints, has its main application area in spatial databases. The standard query language for polynomial constraint databases is first-order logic over the reals. Because of the limited expressive power of this logic with respect to queries that are important in spatial data base applications, various extensions have been introduced. We study extensions of first-order logic with different types of transitive-closure operators and we are in particular interested in deciding the termination of the evaluation of queries expressible in these transitive-closure logics. It turns out that termination is undecidable in general. However, we show that the termination of the transitive closure of a continuous function graph in the two-dimensional plane, viewed as a binary relation over the reals, is decidable, and even expressible in first-order logic over the reals. Based on this result, we identify a particular transitive-closure logic for which termination of query evaluation is decidable and which is more expressive than first-order logic over the reals. Furthermore, we can define a guarded fragment in which exactly the terminating queries of this language are expressible.     

A 1NF temporal relational model and algebra coping with valid-time temporal indeterminacy

In the real world, many phenomena are time related and in the last three decades the database community has devoted much work in dealing with “time of facts” in databases. While many approaches incorporating time in the relational model have been already devised, most of them assume that the exact time of facts is known. However, this assumption does not hold in many practical domains, in which temporal indeterminacy of facts occurs. The treatment of valid-time indeterminacy requires in-depth extensions to the current relational approaches. In this paper, we propose a theoretically grounded approach to cope with this issue, overcoming the limitations of related approaches in the literature. In particular, we present a 1NF temporal relational model and propose a new temporal relational algebra to query it. We also formally study the properties of the new data model and algebra, thus granting that our approach is interoperable with pre-existent temporal and non-temporal relational approaches, and is implementable on top of them. Finally, we consider computational complexity, showing that only a limited overhead is added when moving from determinate to indeterminate time.     

Spatio-temporal querying recurrent multimedia databases using a semantic sequence state graph

We present an indexing method for spatiotemporal data: semantic sequence state graph (S³G). S³G maintains objects with their locations as states and events as transitions. The spatial information is maintained in states while the semantic events result in temporal ordering between the states. If the objects visit the same locations repeatedly, we call such databases as recurrent databases. Our querying interface supports queries based on spatio-temporal logic that includes operators such as ??next?? and ??eventually??. The interactive querying interface enables the user to build the query interactively and see the intermediate results of the query.     

Optimizing Queries with Object Updates

Object-oriented databases (OODBs) provide powerful data abstractions and modeling facilities but they usually lack a suitable framework for query processing and optimization. Even though there is an increasing number of recent proposals on OODB query optimization, only few of them are actually focused on query optimization in the presence of object identity and destructive updates, features often supported by most realistic OODB languages. This paper presents a formal framework for optimizing object-oriented queries in the presence of side effects. These queries may contain object updates at any place and in any form. We present a language extension to the monoid comprehension calculus to express these object-oriented features and we give a formal meaning to these extensions. Our method is based on denotational semantics, which is often used to give a formal meaning to imperative programming languages. The semantics of our language extensions is expressed in terms of our monoid calculus, without the need of any fundamental change to our basic framework. Our method not only maintains referential transparency, which allows us to do meaningful query optimization, but it is also practical for optimizing OODB queries since it allows the same optimization techniques applied to regular queries to be used with minimal changes for OODB queries with updates.     

PHIRST: A distributed architecture for P2P information retrieval

Recent progress in peer to peer (P2P) search algorithms has presented viable structured and unstructured approaches for full-text search. We posit that these existing approaches are each best suited for different types of queries. We present PHIRST, the first system to facilitate effective full-text search within P2P databases. PHIRST works by effectively leveraging between the relative strengths of these approaches. Similar to structured approaches, agents first publish terms within their stored documents. However, frequent terms are quickly identified and not exhaustively stored, resulting in a significant reduction in the system's storage requirements. During query lookup, agents use unstructured search to compensate for the lack of fully published terms. Additionally, they explicitly weigh between the costs involved in structured and unstructured approaches, allowing for a significant reduction in query costs. Finally, we address how node failures can be effectively addressed through storing multiple copies of selected data. We evaluated the effectiveness of our approach using both real-world and artificial queries. We found that in most situations our approach yields near perfect recall. We discuss the limitations of our system, as well as possible compensatory strategies.     

Querying imprecise data in moving object environments

In moving object environments, it is infeasible for the database tracking the movement of objects to store the exact locations of objects at all times. Typically, the location of an object is known with certainty only at the time of the update. The uncertainty in its location increases until the next update. In this environment, it is possible for queries to produce incorrect results based upon old data. However, if the degree of uncertainty is controlled, then the error of the answers to queries can be reduced. More generally, query answers can be augmented with probabilistic estimates of the validity of the answer. We study the execution of probabilistic range and nearest-neighbor queries. The imprecision in answers to queries is an inherent property of these applications due to uncertainty in data, unlike the techniques for approximate nearest-neighbor processing that trade accuracy for performance. Algorithms for computing these queries are presented for a generic object movement model and detailed solutions are discussed for two common models of uncertainty in moving object databases. We study the performance of these queries through extensive simulations.