Recovery is an intricate aspect of transaction processing architectures. In its traditional implementation, recovery requires the management of two persistent data stores---a write-ahead log and a materialized database---which must be carefully orchestrated to maintain transactional consistency. Furthermore, the design and implementation of recovery algorithms have deep ramifications into almost every component of the internal system architecture, from concurrency control to buffer management and access path implementation. Such complexity not only incurs high costs for development, testing, and training, but also unavoidably affects system performance, introducing overheads and limiting scalability.

Traditional database management systems (DBMSs) running on powerful single-node servers are usually over-provisioned for most of their daily workloads and, because they do not show good-enough energy proportionality, waste a lot of energy while underutilized. A cluster of small (wimpy) servers, where its size can be dynamically adjusted to the current workload, offers better energy characteristics for those workloads. Yet, data migration, necessary to balance utilization among the nodes, is a non-trivial and time-consuming task that may consume the energy saved. For this reason, a sophisticated and easy to adjust partitioning scheme fostering dynamic reorganization is needed. In this paper, we adapt a technique originally created for SMP systems, called physiological partitioning, to distribute data among nodes that allows to easily repartition data without interrupting transactions. We dynamically partition DB tables based on the nodes' utilization and given energy constraints and compare our approach with physical partitioning and logical partitioning methods. To quantify possible energy saving and its conceivable drawback on query runtimes, we evaluate our implementation on an experimental cluster and compare the results w.r.t. performance and energy consumption. Depending on the workload, we can substantially save energy without sacrificing too much performance.

Phase-change memory (PCM), as one of the most promising next-generation memory technologies, offers various attractive properties such as non-volatility, byte addressability, bit alterability, and low idle energy consumption. Recently, PCM has drawn much attention from the database community for optimizing query and transaction performance. As a complement to existing work, we present PCMLogging, a novel logging scheme that exploits PCM for both data caching and transaction logging to minimize I/O accesses in disk-based databases. Specifically, PCMLogging caches dirty pages/records in PCM and further maintains an implicit log in the cached updates to support database recovery. By integrating log and cached updates, PCMLogging enables simplified recovery and prolongs PCM lifetime. Furthermore, using PCMLogging, we develop a wear-leveling algorithm, that evenly distributes the write traffic across the PCM storage space, and a cost-based destaging algorithm that adaptively migrates cached data from PCM to external storage. Compared to classical write-ahead logging (WAL), our trace-driven simulation results reveal up to 1 20X improvement in system throughput.

The management of data acquired in a daily basis, together with historical data kept available during variable time frames, became a practical concern to the healthcare practice. Data organized according to the DICOM (Digital Imaging and Communications in Medicine) standard contribute to this scenario, demanding solutions for storage and retrieval of metadata and images that lie beyond the customary file system approach. As a way of experimentation, this work defines and implements a data model using a NoSQL, row-store database, aiming to evaluate its suitability on managing DICOM content at tag level, as well as its performance when compared to a commonly approach based on a relational schema. The obtained results attest the capacity of the proposed model in storing full-content DICOM images, using tags as data units. In terms of performance, however, the data model is outperformed by the relational approach.

OBJECTIVE: To design, build, and evaluate a storage model able to manage heterogeneous digital imaging and communications in medicine (DICOM) images. The model must be simple, but flexible enough to accommodate variable content without structural modifications; must be effective on answering query/retrieval operations according to the DICOM standard; and must provide performance gains on querying/retrieving content to justify its adoption by image-related projects. METHODS: The proposal adapts the original decomposed storage model, incorporating structural and organizational characteristics present in DICOM image files. Tag values are stored according to their data types/domains, in a schema built on top of a standard relational database management system (RDBMS). Evaluation includes storing heterogeneous DICOM images, querying metadata using a variable number of predicates, and retrieving full-content images for different hierarchical levels. RESULTS AND DISCUSSION: When compared to a well established DICOM image archive, the proposal is 0.6-7.2 times slower in storing content; however, in querying individual tags, it is about 48.0% faster. In querying groups of tags, DICOM decomposed storage model (DCMDSM) is outperformed in scenarios with a large number of tags and low selectivity (being 66.5% slower); however, when the number of tags is balanced with better selectivity predicates, the performance gains are up to 79.1%. In executing full-content retrieval, in turn, the proposal is about 48.3% faster. CONCLUSIONS: DCMDSM is a model built for the storage of heterogeneous DICOM content, based on a straightforward database design. The results obtained through its evaluation attest its suitability as a storage layer for projects where DICOM images are stored once, and queried/retrieved whenever necessary.

Because energy use of single-server systems is far from being energy proportional, we explore whether or not better energy efficiency may be achieved by a cluster of nodes whose size is dynamically adjusted to the current workload demand. As data-intensive workloads, we submit specific TPC-H queries against a distributed shared-nothing DBMS, where time and energy use are captured by specific monitoring and measurement devices. We configure various static clusters of varying sizes and show their influence on energy efficiency and performance. Further, using an EnergyController and a load-aware scheduler, we verify the hypothesis that energy proportionality can be well approximated by dynamic clusters.

Developing a full-fledged cost-based XQuery optimizer is a fairly complex task. Nowadays, there is little knowledge concerning suitable cost formulae and optimization strategies for exploring and constraining the tremendously large search space. To allow for a fair assessment of different optimization strategies, physical algebra operators, and indexing approaches, we developed an extensible optimization framework. The framework is accompanied by a supportive visual explain tool that enables user interactions to refine the inspection and the comprehension of the query plans proposed. Using this tool, the optimizer can be dynamically reconfigured and the impact of different optimization strategies on the final query execution plan can be immediately visualized.

Flash SSDs originate a disruptive change concerning storage technology and become a competitor for conventional magnetic disks in the area of persistent database stores. Compared to them, they provide a dramatic speed-up for random reads, but exhibit a distinct read/write (R/W) asymmetry, i.e., updates are more expensive than reads. Existing buffer management algorithms for those devices usually trade physical reads for physical writes to some extent. But they ignore the actual R/W cost ratio of the underlying device and the update intensity of the workload. Therefore, their performance advantage is sensitive to device and workload changes. We propose CASA (Cost-Aware Self-Adaptive), a novel buffer replacement policy, which makes the trade-off between physical reads and physical writes in a controlled fashion, depending on the R/W cost ratio, and automatically adapts itself to changing update intensities in workloads. Our experiments show that CASA outperforms previous proposals in a variety of cost settings and under changing workloads.

Even though an effective cost-based query optimizer is of utmost importance for the efficient evaluation of XQuery expressions in native XML database systems, such a component is currently out of sight, because former approaches do not pay attention to the latest advances in the area of physical operators (e. g., Holistic Twig Joins and advanced indexes) or just focus only on some of them.

Flash disks are becoming an important alternative to conventional magnetic disks. Although accessed through the same interface by applications, flash disks have some distinguished characteristics that make it necessary to reconsider the design of the software to leverage their performance potential. This paper addresses this problem at the buffer management layer of database systems and proposes a flash-aware replacement policy that significantly improves and outperforms one of the previous proposals in this area.

A natural consequence of the widespread adoption of XML as standard for information representation and exchange is the redundant storage of large amounts of persistent XML documents. Compared to relational data tables, data represented in XML format can potentially be even more sensitive to data quality issues because structure, besides textual information, may cause variations in XML documents representing the same information entity. Therefore, correlating XML documents, which are similar in content an structure, is a fundamental operation. In this paper, we present an effective, flexible, and high-performance XML-based similarity join framework. We exploit structural summaries and clustering concepts to produce compact and high-quality XML document representations: our approach outperforms previous work both in terms of performance and accuracy. In this context, we explore different ways to weigh and combine evidence from textual and structural XML representations. Furthermore, we address user interaction, when the similarity framework is configured for a specific domain, and updatability of clustering information, when new documents enter datasets under consideration. We present a thorough experimental evaluation to validate our techniques in the context of a native XML DBMS.

We propose a new framework for the summarization of XML document properties called EXsum (Element-wise XML summarization), which can capture statistical information of all important XPath axes related to (the nodes having) the same element name in a document. Compared to conventional summaries, cardinality estimates for a richer spectrum of XPath/XQuery expressions can be provided for query optimization. For the important class of queries consisting of one or two location steps only, even accurate cardinalities are computed. Besides adequate storage consumption, it provides fast access times which helps to keep the query optimization overhead low. Using a collection of XML documents embodying considerable structural variations, we have empirically analyzed the EXsum framework by running a large number of experiments in our XML native database management system called XTC. These evaluations clearly show the predominance of EXsum as to important aspects when compared to competitor approaches.

There are numerous and influential parameters associated with the selection of suitable native storage structures for XML documents within an XML DBMS. The most important parameters are related to node labeling, path synopsis, document container layout, indexing, and text compression. While node labeling and the presence of a path synopsis greatly determine flexibility and efficiency of the entire DBMS-internal XML processing, the remaining issues primarily address I/O demand and space consumption. In particular, text compression---considered orthogonal to the design choices affected by the other parameters---implies additional algorithmic costs for encoding/decoding during document processing. Having the vision in mind that future storage managers can autonomously figure out optimal choices for all of these parameters, we discuss how various storage options favor different usage patterns and how they can be specified beforehand to influence native XML storage options by the anticipated usages.

XTCcmp, the XQuery Compiler of a native XML database system, extends Starburst's well-known Query Graph Model to serve as an internal representation and basis for query restructuring of XQuery expressions. Furthermore, XTCcmp is able to generate execution plans supporting a wide range of both well-known and newly developed variants of core XML processing algorithms and indexes. Our demo visualizes all rule-based transformation stages, i. e., simplification, algebraic rewriting, and plan generation. Furthermore, via an interface to the extensible rule configuration, it allows interaction with the query compiler to vary configuration parameters and to control the compilation outcome.

Because XML documents tend to be very large, are accessed by declarative and navigational languages, and often are processed in a collaborative way using read/write transactions, their fine-grained storage and management in XML DBMSs is a must for which, in turn, a flexible and space-economic tree representation is mandatory. In this paper, we explore a variety of options to natively store, encode, and compress XML documents thereby preserving the full DBMS processing flexibility on the documents required by the various language models and usage characteristics. Important issues of our empirical study are related to node labeling, document container layout, indexing, as well as structure and content compression. Encoding and compression of XML documents with their complete structure leads to a space consumption of ~40% to ~60% compared to their plain representation, whereas structure virtualization (elementless storage) saves in the average more than 10%, in addition.

As observed in many publications so far, the matching of twig pattern queries (i.e., queries that contain only the child and the descendant axis) is a core operation in XML database management systems (XDBMSs) for which the structural join and the holistic twig join algorithms were proposed. In a single-user environment, especially the latter algorithm provides a good evaluation strategy. However, when it comes to multi-user access to a single XML document, it may lead to extensive blocking situations: The XDBMS has to ensure data consistency and, therefore, has to prevent concurrent modification operations from changing elements in the input sequences, a holistic twig algorithm accesses while operating. To circumvent this problem, we propose a set of new locking-aware operators for twig pattern query evaluation that rely on stable path labels (SPLIDs) as well as document and element set indexes. Furthermore, by running extensive tests on our own XDBMS, we show that their performance is comparable to existing approaches in a single-user environment, and leads to higher throughput rates in the case of multi-user access.

With the emergence of application systems which encapsulate databases and related application components, pure data integration using, for example, a federated database system is not possible anymore. Instead, access via predefined functions is the only way to get data from an application system. As a result, retrieval of such heterogeneous and encapsulated data sources needs the combination of generic query as well as predefined function access. In this paper, we present a middleware approach supporting such a novel and extended kind of integration. Starting with the overall architecture, we explain the functionality and cooperation of its core components: a federated database system and a workflow management system connected via a wrapper. Afterwards, we concentrate on essential aspects of query processing across these heterogeneous components focusing on the impact of the functions included. We discuss the operations the wrapper should provide in order to extend the workflow system's native functionality. In addition to selection and projection, these operations could include aggregation and the support of subqueries. Moreover, we point out modifications to the traditional cost model needed to consider the cost estimates for the function calls as well.

With the emergence of so-called application systems which encapsulate databases and their applications, pure data integration using, for example, a federated database system is not possible anymore. Instead, access via predefined functions is the only way to get data from an application system. As a result, the combination of generic query as well as predefined function access is needed in order to integrate heterogeneous data sources. The authors focus on a middleware approach supporting this novel and extended kind of integration. Starting with the overall architecture, we explain the functionality and cooperation of its core components: a federated database system (FDBS) and a workflow management system (WfMS). Afterwards, we concentrate on the key problems of function integration by discussing query execution planning, precedence control of function execution, and parameter handling. In this context, we develop a lightweight description language based on XML for the global-to-local mapping of functions. In addition, we consider some important aspects of the execution model, focusing on the interaction of the FDBS and the WfMS as well as the support of distributed transactions.

Nowadays the complexity of design processes, no matter which design domain (CAD, software engineering, etc.) they belong to, requires system support by means of so-called repositories. Repositories help managing design artifacts by offering adequate storage and manipulation services. Some of the most important features of a repository are version management and activity management. Versioning comprises the specification, storage, and maintenance of versioned design objects whereas activity management is responsible for cooperation control, designflow management and management of design transactions processing versioned design objects. Regarding these issues (version and activity management) repository technology, as we think, should not only provide pre-defined services, but should be flexible enough to reflect different application needs. For that reason, we propose to provide repository managers by generic methods, i.e. by generating the corresponding functionality. In this paper, we consider a representative cooperation model, which is based on versioning services, in order to identify the major data manipulation and activity control needs of cooperative design applications. We will focus on the data manipulation needs by introducing our generative approach for customizing versioning facilities. Additionally, we will outline our ideas of applying a generative approach also for the provision of tailored activity control services. Thus, the paper wants to show that by exploiting generic methods and reuse as well as the extensibility properties of new object-relational database technology, repository managers can be flexibly tailored to special application needs and, thereby, applications do not have to be forced to deal with systems only providing pre-defined services.

To meet the ever challenging requirements of today's applications, both database research and industry are engaged in adding new features to database management systems (DBMSs). As a major effort in this direction, object-relational DBMSs (ORDBMSs) are becoming more and more popular due to their extensibility, i.e., allowing user-defined facilities to be used in the same way as built-in ones. Inspired by this idea, we started to develop a prototype ORIENT to enhance DBMSs with complex relationship semantics that are versatile in the real world but still insufficiently supported by new database technology. Our work reveals that data model changes to accommodate relationship semantics imply extensions at the processing level which are, however, not feasible in "extensible" ORDBMSs. Proper integration of new processing capabilities calls for a more open approach to database extensibility than current ORDBMSs exhibit.

In this paper, we address a specific topic within the context of nested transaction implementation, namely, the assignment of identifiers to transactions. We discuss the most important information such identifiers should carry. We do this based on an analysis of the main requirements the components of a general transaction processing system pose on the identifiers. Thereafter, we present some schemes for the assignment of transaction identifiers and discuss their pros and cons with regard to the requirements presented. Finally, we compare one of our schemes to a conventional one by considering the most common operations that are performed with the identifiers. Lastly, we show the performance measurements we have obtained.

Digital and interactive TV systems will bring hundreds of TV program channels to the people.Then, the use of existing strategies for channel selection will fail: It is neither possible to select the program by "sur@g" through the channels, nor by using printed program guides.This paper describes a new approach towards creation of a Personal Electronic Program Guide (EPG) regarding the individual view preferences of a usez The foundation of individual TV program pre-selection is a classified and categorized TV program description and the maintenance of user profiles describing his viewing preferences.Besides creation of user projiles, an automatic update technique will be introduced.Channel selection events are taken as parameters for an adjustment of user projiles.Personal program pre-selection is done by using intelligent $ltering techniques which apply individual user profiles to the TV program description (so-called matching).An approach to design and realize an EPG proto~pe system will be described in this papex

Grahne et al. have presented a graph algorithm for a subset of recursive queries. This method consists of two phases. In the first phase, the method transforms a linear binary-chain program into a set of equations over expressions containing predicate symbols. In the second phase, a graph is constructed from the equations and the answers are produced by traversing the relevant paths. Here we describe a new algorithm which requires less time than the algorithm of Grahne et al. The key idea of the improvement is to reduce the search space that will be traversed when a query is invoked. Further, we speed up the evaluation of cyclic data by generating most answers directly in terms of the answers already found and the associated “path information” instead of traversing the corresponding paths as usual. In this way, our algorithm achieves a linear time complexity for both cyclic and non-cyclic data.

Knowledge Base Management Systems (KBMSs) are a growing research area finding applicability in different domains. As a consequence, the demand for ever-larger knowledge bases (KBs) is growing more and more. Inside this context, knowledge sharing turns out to be a crucial point to be supported by KBMSs. In this paper, we propose a way of controlling knowledge sharing. We show how we obtain serializability of transactions providing many different locking granules, which are based on the semantics of the abstraction relationships. The main benefit of our technique is the high degree of potential concurrency, to be obtained through a logical partitioning of the KB graph and the provision of lock types used for each referenced partition. By this way, we capture more of the semantics contained in a KB graph, through an interpretation of its edges grounded in the abstraction relationships, and make feasible a full exploitation of all inherent parallelism in a knowledge representation approach.

'Computer-Supported Cooperative Work' is a young research area considering applications with strong demands on database technology. Design applications need support for cooperation and some means for controlling their inherent dynamics. However, today's CAD systems consisting of a collection of diverse design tools typically do not support these requirements. Therefore, an encompassing processing model is needed that covers the overall design process in general as well as CAD-tool application in particular. The CONCORD model described in the paper, reflects the distinct properties of design process dynamics by distinguishing three levels of abstraction. The highest level supports application-specific cooperation control and design process administration, the second considers goal-oriented tool invocation and work-flow management while the third level provides tool processing of design data. To achieve level-spanning control, the authors rely on transactional facilities provided at the various system layers.>

PRIMA is a non-standard database system developed at the University Kaiserslautern. Its major purpose is the support of engineering design applications, such as VLSI design and software engineering. The applications require tailored application-dependent interfaces which, however, all share basic notions like that of a composite object. Hence, the approach of PRIMA is to offer an application-independent complex-object interface (the moleculeatom data model, shortly called MAD model) and to provide means to easily augment this interface by application-dependent functionality. In the following, we will concentrate on the MAD model and its implementation.

The concept of nested transactions offers more decomposable execution units and finer grained control over recovery and concurrency as compared to 'flat' transactions. To exploit these advantages, especially transaction recovery has to be refined and adjusted to the requirements of the control structure.In this paper, we investigate transaction recovery for nested transactions. Therefore, a model for nested transaction is introduced allowing for synchronous and asynchronous transaction invocation as well as single call and conversational interfaces. For the resulting four parameter combinations, the properties and dependencies of transaction recovery are explored if a transaction is 'unit of recovery' and if savepoints within transactions are used to gain finer recovery units.

This paper discusses the implementation of a database buffer manager as a component of a DBMS. The interface between calling components of higher system layers and the buffer manager is described; the principal differences between virtual memory paging and database buffer management are outlined; the notion of referencing versus addressing of database pages is introduced; and the concept of fixing pages in the buffer to prevent uncontrolled replacement is explained. Three basic tasks have to be performed by the buffer manager: buffer search, allocation of frames to concurrent transactions, and page replacement. For each of these tasks, implementation alternatives are discussed and illustrated by examples from a performance evaluation project of a CODASYL DBMS.

A new kind of implementation technique for access paths connecting sets of tuples qualified by attribute values is described. It combines the advantages of pointer chain and multilevel index implementation techniques. Compared to these structures the generalized access path structure is at least competitive in performing retrieval and update operations, while a considerable storage space saving is gained. Some additional features of this structure support m -way joins and the evaluation of multirelation queries, and allow efficient checks of integrity assertions and simple reorganization schemes.