Temporal Database Systems Research Articles

T-SQL: A Lightweight Implementation to Enable Built-in Temporal Support in MVCC-based RDBMSs

The adoption of temporal expressions into SQL:2011 has continuously driven the extensions of temporal support in relational database systems (a.b.a. RDBMSs). In this paper, we present T-SQL, a lightweight yet efficient built-in temporal implementation in RDBMSs. T-SQL completely relies on multi-version concurrency control (MVCC) which is widely adopted in RDMBSs to manage temporal data. For temporal data, current records are maintained in legacy databases, and historical records, i.e., previoius versions of current records (if any), which used to be periodically reclaimed are separately maintained in KV stores. To enable temporal query processing under SQL:2011, we extend the query engine in legacy RDBMSs to support query processing over either historical records or current records or both. Further, regarding temporal data are ever-increasing, we propose various optimizations to reduce the storage overhead of KV stores while keeping efficient query performance. We elaborate on a publicly available implementation, on how to integrate T-SQL into both centralized and distributed RDBMSs. We conduct extensive experiments on both YCSB and TPC-series benchmarks by comparing T-SQL with other temporal database systems. The results show that T-SQL is both lightweight and efficient.

The Opportunistic Projection Mining Algorithm in Massive Data

Temporal data model ensures the correctness, validity and compability of data in temporal database, and temporal formal languages model describes the semantic specification of temporal database, both two are core and basis of temporal database system design and development. The paper has exploited the quo of temporal data models and temporal formal languages models, presented FTDM (Formal Temporal Data Model) and L(FTDM) over FTDM by denotation semantics methods. Referring to thinking of software reuse, this paper proposed the definition of languages reuse. Based on the previous works the authors further made temporal formal languages models family {Li} with its particular categorical properties analyzed in this paper by categorical methods, also demonstrated rigorously inherent relationships between temporal formal languages models in {Li}. Their works provided a category theoretic method with universality and flexible expansion for temporal formal languages models, meantime, proposed solid theoretical foundations for design and development of temporal database system.

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.

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.

Spatial, temporal and spatio-temporal databases - hot issues and directions for phd research

Spatial and temporal database systems, both in theory and in practice, have developed dramatically over the past two decades to the point where usable commercial systems, underpinned by a robust theoretical foundation, are now starting to appear. While much remains to be done, topics for research must be chosen carefully to avoid embarking on impractical or unprofitable areas. This is particularly true for doctoral research where the candidate must build a tangible contribution in a relatively short time.The panel session at the Eighth International Symposium on Spatial and Temporal Databases (SSTD 2003) held on Santorini Island, Greece [7] in July 2003 thus took as its focus the question What to focus on (and what to avoid) in Spatial and Temporal Databases: recommendations for doctoral research. This short paper, authored by the panel members, summarizes these discussions.

Integrating Spatial and Temporal Relationship Operators into SQL3 for Historical Data Management

A spatial object changes its states over time. However, existing spatial and temporal database systems cannot fully manage time-varying data with both spatial and nonspatial attributes. To overcome this limitation, we present a framework for spatio-temporal databases that can manage all time-varying historical information and integrate spatial and temporal relationship operators into the select statement in SQL3. For the purpose of our framework, we define three referencing macros and a history aggregate operator and classify the existing spatial and temporal relationship operators into three groups: exclusively spatial relationship operators, exclusively temporal relationship operators, and spatio-temporal common relationship operators. Finally, we believe the integration of spatial and temporal relationship operators into SQL3 will provide a useful framework for the history management of time-varying spatial objects in a uniform manner.

Extending temporal query languages to handle imprecise time intervals

Previous work on temporal and historical databases has been mainly based on the assumption that the time intervals of temporal attributes and the start/finish points of modeled events are precisely known. In many real life situations, however, the time boundary of events and the duration of entity relationships may not be exactly known. Modeling these situations and providing a way to write queries dealing with time impreciseness represents a useful extension currently lacking in existing/proposed temporal database systems. In this paper, we discuss the problem of handling time impreciseness in temporal databases and present three models for the representation of imprecise time intervals. We illustrate the basic idea and motivation of each model, its underlying logic, tradeoffs, and important properties. We also propose query language extensions that can enrich the user interface with capabilities to formulate queries dealing with time impreciseness. Extensions to existing query constructs at both the transaction level and the operator level are presented. New operators related to time impreciseness are also presented. The models and extensions discussed in this paper enrich the flexibility of temporal databases and can be used to help users obtain more meaningful replies for their temporal queries.

Time, tense and aspect in natural language database interfaces

Most existing Natural Language Database Interfaces (NLDB) were designed to be used with database systems that provide very limited facilities for manipulating time-dependent data, and they do not support adequately temporal linguistic mechanisms (verb tenses, temporal adverbials, temporal subordinate clauses, etc.). The database community is becoming increasingly interested in temporal database systems, which are intended to store and manipulate in a principled manner information not only about the present, but also about the past and future. When interfacing to temporal databases, supporting temporal linguistic mechanisms becomes crucial.We present a framework for constructing Natural Language Interfaces for Temporal Databases (NLTDB), which draws on research in tense and aspect theories, temporal logics and temporal databases. The framework consists of a temporal intermediate representation language, called TOP, an HPSG grammar that maps a wide range of questions involving temporal mechanisms to appropriate TOP expressions, and a provably correct method for translating from TOP to TSQL2, TSQL2 being a recently proposed temporal extension of the SQL database language. This framework was employed to implement a prototype NLTDB.

Transaction processing in distributed active real-time database systems

An active real-time database system (ARTDBS) is designed to provide timely response to the critical situations that are defined on database states. Although a number of studies have already addressed various issues in ARTDBSs, little attention has been paid to scheduling transactions in a distributed ARTDBS environment. In this paper, 2 An earlier version of this paper appears in the Proceedings of the Second International Workshop on Active, Real-Time and Temporal Database Systems. 2 we describe a detailed performance model of a distributed ARTDBS and investigate various performance issues in time-cognizant transaction processing in ARTDBSs. The experiments conducted evaluate the performance under various types of active workload and different distributed transaction-processing architectures. The performance metric used in the evaluations is the fraction of transactions that violate their timing constraints. We also describe and evaluate a nested transaction execution scheme that improves the real-time performance under high levels of active workload.

Temporal database system implementations

Although research on temporal database systems has been active for about 20 years, implementations have not appeared until recently. This is one reason why current commercial database systems provide only limited temporal functionality. This paper summarizes extant state of the art of temporal database implementations. Rather than being very specific about each system we have attempted to provide an indication of the functionality together with pointers to additional information. It is hoped that this leads to more efforts pushing the implementation of temporal database systems in the near future.

External segment trees

The segment tree is a well-known internal data structure with numerous applications in computational geometry. It allows the dynamical maintenance of a set of intervals such that the intervals enclosing a query point can be found efficiently (point enclosure search). In this paper we transfer the underlying principle of the segment tree in a nontrivial way to secondary storage and arrive at the EST-an external file structure with the same functionality and the following properties: (1) Point enclosure searches are very efficient--only very few pages are accessed that are not filled to more than 50% with result intervals. (2) A page filling of 50% is guaranteed--on the average it will be around 70%. Although the segment tree represents, in the worst case, each interval by a logarithmic number offragments, in practical cases fragmentation remains low and the storage requirements about linear. (3) The EST is balanced and the update algorithms are efficient. (4) Unlike many other file structures for spatial objects the EST has no problems with an arbitrarydensity, that is, an arbitrarily large number of intervals covering any point of the line. Furthermore, the EST can be used as a file structureconstructor in the following sense: Let there be a file structureX supporting searches for objects with propertyx and suppose it is necessary to maintain a collection of objects with associated (e.g., time) intervals. Then an EST-X structure that supports searches for objects with propertyx present at timet can be built. This suggests using the EST as a building block in the implementation of temporal database systems. Other applications include the one-dimensional indexing of collections of spatial objects in two or more dimensions. More generally, this paper shows techniques for mapping internal tree structures with node lists (other examples: range tree, interval tree) to secondary memory. In this context an intriguing theoretical problem, thecover-balancing problem, is solved: Given a tree whose nodes have associatedweights partitioned into subtrees whose weights must lie in a certain range, maintain this partition under weight changes at arbitrary nodes. This is in contrast to classical balancing problems where updates occur only at the leaves.

Unifying temporal data models via a conceptual model

To add time support to the relational model, both first normal form (1NF) and non-1NF data models have been proposed. Each has associated advantages and disadvantages. For example, remaining within 1NF when time support is added may introduce data redundancy. On the other hand, well-established storage organization and query evaluation techniques require atomic attribute values, and are thus intended for 1NF models; utilizing a non-1NF model may degrade performance. This paper describes a new temporal data model designed with the single purpose of capturing the time-dependent semantics of data. Here, tuples of bitemporal relations are stamped with sets of two-dimensional chronons in transaction-time/valid-time space. We use the notion of snapshot equivalence to map temporal relation instances and temporal operators of one existing model to equivalent instances and operators of another. We examine five previously proposed schemes for representing bitemporal data: two are tuple-timestamped 1NF representations, one is a Backlog relation composed of 1NF timestamped change requests, and two are non-1NF attribute value-timestamped representations. The mappings between these models are possible using mappings to and from the new conceptual model. The framework of well-behaved mappings between models, with the new conceptual model at the center, illustrates how it is possible to use different models for display and storage purposes in a temporal database system. Some models provide rich structure and are useful for display of temporal data, while other models provide regular structure useful for storing temporal data. The equivalence mappings effectively move the distinction between the investigated data models from a semantic basis to a display-related or a physical, performance-relevant basis, thereby allowing the exploitation of different data models by using each for the task(s) for which they are best suited.

Taxonomy of time models in databases

A study of real-world database applications that include time-related queries, and an examination of various approaches to easing the development of such applications, leads to the identification of three major issues to be addressed in temporal database systems. These are the representation of time at a conceptual level, the design of a usable and effective means of querying temporal data, and the specification of physical access strategies and methods to ensure the efficiency of access to (bulky) temporal data. The paper provides a taxonomy of methods and approaches for each of these issues, showing the extent to which various researchers have recently resolved the subissues deemed to be essential for temporal database systems to be feasible.

Using temporal hierarchies to efficiently maintain large temporal databases

Many real-world applications involve the management of large amounts of time-dependent information. Temporal database systems maintain this information in order to support various sorts of inference (e.g., answering questions involving propositions that are true over some intervals and false over others). For any given proposition, there are typically many different occasions on which that proposition becomes true and persists for some length of time. In this paper, these occasions are referred to as time tokens. Many routine database operations must search through the database for time tokens satisfying certain temporal constraints. To expedite these operations, this paper describes a set of techniques for organizing temporal information by exploiting the local and global structure inherent in a wide class of temporal reasoning problems. The global structure of time is exemplified in conventions for partitioning time according to the calendar and the clock. This global structure is used to partition the set of time tokens to facilitate retrieval. The local structure of time is exemplified in the causal relationships between events and the dependencies between planned activities. This local structure is used as part of a strategy for reducing the computation required during constraint propagation. The organizational techniques described in this paper are quite general, and have been used to support a variety of powerful inference mechanisms. Integrating these techniques into an existing temporal database system has increased, by an order of magnitude or more in most applications, the number of time tokens that can be efficiently handled. — Author's Abstract