Information structures and database support for solid modeling

The question we are going to investigate is how to map solid representations to DB structures and how to process this information efficiently. Starting from analytical representations based on analytical methods we discuss the use of constructive solid geometry and boundary representation models with various refinements. Furthermore, additional submodels (organizational, technological, physical) are considered in order to obtain an overall product model. This model representing all important aspects of a complex design object may serve to derive special object representations needed by existing engineering tools or by mathematical methods (e.g. finite elements). Today's DBMS are unable to meet the increasing requirements of engineering applications that would prefer to use a DBMS. To alter this situation, a new generation of DBMS architectures tailored to the demands of such enhanced applications have to be developed. As a consequence, the flexibility and expressiveness of data models as well as the handling of application objects must be greatly improved before interactive design work can be supported. We outline our data model concepts and architectural decisions to provide effective data management support. Our DBMS architecture consists of a neutral kernel part running on a server machine and an application layer tailored to solid modeling tasks which together with the application, i.e. the solid modeler is allocated to the workstation

Instant restore after a media failure

Media failures usually leave database systems unavailable for several hours until recovery is complete, especially in applications with large devices and high transaction volume. Previous work introduced a technique called single-pass restore, which increases restore bandwidth and thus substantially decreases time to repair. Instant restore goes further as it permits read/write access to any data on a device undergoing restore--even data not yet restored--by restoring individual data segments on demand. Thus, the restore process is guided primarily by the needs of applications, and the observed mean time to repair is effectively reduced from several hours to a few seconds. This paper presents an implementation and evaluation of instant restore. The technique is incrementally implemented on a system starting with the traditional ARIES design for logging and recovery. Experiments show that the transaction latency perceived after a media failure can be cut down to less than a second and that the overhead imposed by the technique on normal processing is minimal. The net effect is that a few "nines" of availability are added to the system using simple and low-overhead software techniques

SCOOTER: A compact and scalable dynamic labeling scheme for XML updates

Although dynamic labeling schemes for XML have been the focus of recent research activity, there are significant challenges still to be overcome. In particular, though there are labeling schemes that ensure a compact label representation when creating an XML document, when the document is subject to repeated and arbitrary deletions and insertions, the labels grow rapidly and consequently have a significant impact on query and update performance. We review the outstanding issues todate and in this paper we propose SCOOTER - a new dynamic labeling scheme for XML. The new labeling scheme can completely avoid relabeling existing labels. In particular, SCOOTER can handle frequently skewed insertions gracefully. Theoretical analysis and experimental results confirm the scalability, compact representation, efficient growth rate and performance of SCOOTER in comparison to existing dynamic labeling schemes

Parallel Query Evaluation: A New Approach to Complex Object Processing

Abstract Complex objects to support non-standard database applications require the use of substantial computing resources because their powerful operations must be performed and maintained in an interactive environment. Since the exploitation of parallelism within such operations seems to be promising, we investigate the principal approaches for processing a query on complex objects (molecules) in parallel. A number of arguments favor methods based on inter-molecule parallelism as against intra-molecule parallelism. Retrieval of molecules may be optimized by multiple storage structures and access paths. Hence, maintenance of such storage redundancy seems to be another good application area to explore the use of parallelism

Evaluation of hardware architectures for parallel execution of complex database operations

Abstract New database applications, primarily in the areas of engineering and knowledge-based systems, refer to complex objects (e.g. representation of a CAD workpiece or a VLSI chip) while performing their tasks. Retrieval, maintenance, and integrity checking of such complex objects consume substantial computing resources which were traditionally used by conventional database management systems in a sequential manner. Rigid performance goals dictated by interactive use and design environments imply new approaches to master the functionality of complex objects under satisfactory time restrictions. Because of the object granularity, the set orientation of the database interface, and the complicated algorithms for object handling, the exploitation of parallelism within such operations seems to be promising. Our main goal is the investigation and evaluation of different hardware architectures and their suitability to efficiently cope with workloads generated by database operations on complex objects. Apparently, employing just a number of processors is not a panacea for our database problem. The sheer horse power of machines does not help very much when data synchronization and event serialization requirements play a major role during object handling. What are the critical hardware architecture properties? How can the existing MIPS be best utilized for the data management functions when processing complex objects? To answer these questions and related issues, we discuss different kinds of architectures combining multiple processors: loosely-, tightly-, and closely-coupled. Furthermore, we consider parallelism at different levels of abstraction: the distribution of (sub-)queries or the decomposition of such queries and their concurrent evaluation at an inter-or intra-object level. Finally, we give some thoughts as to the problems of load control and transaction management

Compacting XML Structures Using a Dynamic Labeling Scheme

Abstract. Due to the growing popularity of XML as a data exchange and storage format, the need to develop efficient techniques for stor-ing and querying XML documents has emerged. A common approach to achieve this is to use labeling techniques. However, their main prob-lem is that they either do not support updating XML data dynamically or impose huge storage requirements. On the other hand, with the ver-bosity and redundancy problem of XML, which can lead to increased cost for processing XML documents, compaction of XML documents has be-come an increasingly important research issue. In this paper, we propose an approach called CXDLS combining the strengths of both, labeling and compaction techniques. Our approach exploits repetitive consecu-tive subtrees and tags for compacting the structure of XML documents by taking advantage of the ORDPATH labeling scheme. In addition it stores the compacted structure and the data values separately. Using our proposed approach, it is possible to support efficient query and update processing on compacted XML documents and to reduce storage space dramatically. Results of a comprehensive performance study are provided to show the advantages of CXDLS.

FibLSS: A scalable label storage scheme for dynamic XML updates

Dynamic labeling schemes for XML updates have been the focus of significant research activity in recent years. However the label storage schemes underpinning the dynamic labeling schemes have not received as much attention. Label storage schemes specify how labels are physically encoded and stored on disk. The size of the labels and their logical representation directly influence the computational costs of processing the labels and can limit the functionality provided by the dynamic labeling scheme to an XML update service. This has significant practical implications when merging XML repositories such as clinical studies. In this paper, we provide an overview of the existing label storage schemes. We present a novel label storage scheme based on the Fibonacci sequence that can completely avoid relabeling existing nodes under dynamic insertions. Theoretical analysis and experimental results confirm the scalability and performance of the Fibonacci label storage scheme in comparison to existing approaches