A temporal database contains time-varying data. In a real-time database transactions have deadlines or timing constraints. In this paper we review the substantial research in these two heretofore separate research areas. We first characterize the time domain, then investigate temporal and real-time data models. We evaluate temporal and real-time query languages along several dimensions. Temporal and real-time DBMS implementation is examined. We conclude with a summary of the major accomplishments of the research to date, and list several research questions that should be addressed next. Keywords: object-oriented database, relational databases, query language, temporal data model, time-constrained database, transaction time, user-defined time, valid time 1 Introduction Time is an important aspect of all real-world phenomena. Events occur at specific points in time; objects and the relationships among objects exist over time. The ability to model this temporal dimension of the real worl...

In a variety of applications, we need to keep track of the development of a data set over time. For maintaining and querying these multiversion data efficiently, external storage structures are an absolute necessity. We propose a multiversion B-tree that supports insertions and deletions of data items at the current version and range queries and exact match queries for any version, current or past. Our multiversion B-tree is asymptotically optimal in the sense that the time and space bounds are asymptotically the same as those of the (single-version) B-tree in the worst case. The technique we present for transforming a (single-version) Btree into a multiversion B-tree is quite general: it applies to a number of hierarchical external access structures with certain properties directly, and it can be modified for others.

. An efficient benchmarking environment for spatiotemporal access methods should at least include modules for generating synthetic datasets, storing datasets (real datasets included), collecting and running access structures, and visualizing experimental results. Focusing on the dataset repository module, a collection of synthetic data that would simulate a variety of real life scenarios is required. Several algorithms have been implemented in the past to generate static spatial (point or rectangular) data, for instance, following a predefined distribution in the workspace. However, by introducing motion, and thus temporal evolution in spatial object definition, generating synthetic data tends to be a complex problem. In this paper, we discuss the parameters to be considered by a generator for such type of data, propose an algorithm, called "Generate_Spatio_Temporal_Data" (GSTD), which generates sets of moving point or rectangular data that follow an extended set of distri...

Abstract—An efficient multiversion access structure for a transaction-time database is presented. Our method requires optimal storage and query times for several important queries and logarithmic update times. Three version operations}inserts, updates, and deletes}are allowed on the current database, while queries are allowed on any version, present or past. The following query operations are performed in optimal query time: key range search, key history search, and time range view. The key-range query retrieves all records having keys in a specified key range at a specified time; the key history query retrieves all records with a given key in a specified time range; and the time range view query retrieves all records that were current during a specified time interval. Special cases of these queries include the key search query, which retrieves a particular version of a record, and the snapshot query which reconstructs the database at some past time. To the best of our knowledge no previous multiversion access structure simultaneously supports all these query and version operations within these time and space bounds. The bounds on query operations are worst case per operation, while those for storage space and version operations are (worst-case) amortized over a sequence of version operations. Simulation results show that good storage utilization and query performance is obtained. Index Terms—Transaction-time database, multidimensional data, access methods, data structures, indexing, I/O complexity.

Queries on XML documents typically combine selections on element contents, and, via path expressions, the structural relationships between tagged elements. Structural joins are used to find all pairs of elements satisfying the primitive structural relationships specified in the query, namely, parent child and ancestor descendant relationships. Efficient support for structural joins is thus the key to efficient implementations of XML queries. Recently proposed node numbering schemes enable the capturing of the XML document structure us- ing traditional indices (such as B+-trees or R-trees). This paper proposes efficient struc- tural join algorithms in the presence of tag indices. We first concentrate on using B+- trees and show how to expedite a structural join by avoiding collections of elements that do not participate in the join. We then intro- duce an enhancement (based on sibling pointers) that further improves performance. Such sibling pointers are easily implemented and dynamically maintainable. We also present a structural join algorithm that utilizes R-trees.

Many applications require the ability to manipulate sequences of data. We motivate the importance of sequence query processing, and present a framework for the optimization of sequence queries based on several novel techniques. These include query transformations, optimizations that utilize meta--data, and caching of intermediate results. We present a bottom-up algorithm that generates an efficient query evaluation plan based on cost estimates. This work also identifies a number of directions in which future research can be directed. 1 Introduction Many real life applications manipulate data that is inherently sequential. Such data is logically viewed and queried in terms of a sequence abstraction and is often physically stored as a sequence. Databases should (a) allow sequences to be queried in a declarative manner, utilizing the ordered semantics of the data, and (b) take advantage of the opportunities available for query optimization. Relational databases are inadequate in this re...

Spatiotemporal objects, i.e., objects which change their position and/or extent over time appear in many applications. In this paper we examine the problem of indexing large volumes of such data. Important in this environment is how the spatiotemporal objects move and/or change. We consider a rather general case where object movements/changes are defined by combinations of polynomial functions. We further concentrate on "snapshot" as well as small "interval" queries as these are quite common when examining the history of the gathered data. The obvious approach that approximates each spatiotemporal object by an MBR and uses a traditional multidimensional access method to index them is inefficient. Objects that "live" for long time intervals have large MBRs which introduce a lot of empty space. Clustering long intervals has been dealt in temporal databases by the use of partially persistent indices. What differentiates this problem from traditional temporal indexing, is that objects are allowed to move/change during their lifetime. Better ways are thus needed to approximate general spatiotemporal objects. One obvious solution is to introduce artificial splits: the lifetime of a long-lived object is split into smaller consecutive pieces. This decreases the empty space but increases the number of indexed MBRs. We first give an optimal algorithm and a heuristic for splitting a given spatiotemporal object in a predefined number of pieces. Then, given an upper bound on the total number of possible splits, we present three algorithms that decide how the splits are distributed among all the objects so that the total empty space is minimized. The number of splits cannot be increased indefinitely since the extra objects will eventually affect query performance. Usi...

A new issue that arises in modern applications involves the efficient manipulation of (static or moving) spatial objects, and the relationships among them. As a result, modern database systems should be able to efficiently support that type of data. Towards this goal, appropriate extensions of multidimensional access methods can be exploited in order to index and retrieve spatiotemporal objects, satisfying users' demands. This paper introduces the basic specifications such a spatiotemporal index structure should follow, evaluates existing proposals with respect to the above specifications, and illustrates issues of interest involving object representation, query processing, and index maintenance.

Traditional approaches to versioning semistructured information are edit-based, i.e., subsequent document versions are represented by using edit scripts. This paper proposes a reference-based version management scheme that preserves the logical structure of the evolving document through the use of object references. By preserving the document structure among versions the new scheme facilitates more efficient query support. In particular, we examine queries involving projections and selections on the document versions, as well as queries on the document evolution history. Moreover, we show that the proposed scheme provides an effective representation of multiversioned XML documents, both at the transport and exchange levels. In fact, with the reference-based scheme, a document's history can also be viewed and processed as yet another XML document. Furthermore, we demonstrate the effectiveness of the new scheme at the storage level. In particular, the scheme is enhanced with a usefulness-based page management policy that extends and adapts techniques used in transaction-time databases to ensure efficient clustering of information among versions. An extensive comparison of the reference-based versioning against representations used in temporal databases and persistent object managers depicts the performance advantages of the new approach. Finally it should be noted that reference-based versioning is applicable to other kinds of semistructured information (besides XML documents), and can be used to replace traditional version control schemes, such as the edit-based RCS and the timestamp-based SCCS.

Abstract: Recently there has been an increasing interest in supporting bulk operations on multidimensional index structures. Bulk loading refers to the process of creating an initial index structure for a presumably very large data set. In this paper, we present a generic algorithm for bulk loading which is applicable to a broad class of index structures. Our approach differs completely from previous ones for the following reasons. First, sorting multidimensional data according to a predefined global ordering is completely avoided. Instead, our approach is based on the standard routines for splitting and merging pages which are already fully implemented in the corresponding index structure. Second, in contrast to inserting records one by one, our approach is based on the idea of inserting multiple records simultaneously. As an example we demonstrate in this paper how to apply our technique to the R-tree family. For R-trees we show that the I/O performance of our generic algorithm meets the lower bound of external sorting. Empirical results demonstrate that performance improvements are also achieved in practice without sacrificing query performance. 1