This article proposes an index key compression scheme based on the notion of distinction bits. It proves that the distinction bits of index keys are sufficient information to determine the sorted order of the index keys. The actual compression ratio may vary depending on the characteristics of datasets (an average of 2.76:1 compression ratio was observed in the authors’ experiments). However, the index key compression scheme leads to significant performance improvements during the reconstruction of large-scale indexes. This study’s index key compression can be effectively used for database replication and index recovery in modern main-memory database systems.

Detecting major system anomalies with observed multivariate time series requires not only the characteristics of each time series but also the status of the entire time series dynamics. Therefore, we propose a method that can detect substantial anomalies by generating a transfer network and an influence network from a multivariate time series. To form a transfer network, each vertex represents a single time series. Each edge indicates the strength of the information flow between each pair of time series using transfer entropy. With the transfer network, we exploit the random walk approach to calculate the affinity score between two vertices and create an influence network that reflects both the direct and indirect influences. In our experiment, we show the efficacy of the proposed method using simple synthetic time series networks and the real data set such as world stock indices and key performance indicators of the SAP HANA in-memory database system.

One of the core principles of the SAP HANA database system is the comprehensive support of distributed query facility. Supporting scale-out scenarios was one of the major design principles of the system from the very beginning. Within this paper, we first give an overview of the overall functionality with respect to data allocation, metadata caching and query routing. We then dive into some level of detail for specific topics and explain features and methods not common in traditional disk-based database systems. In summary, the paper provides a comprehensive overview of distributed query processing in SAP HANA database to achieve scalability to handle large databases and heterogeneous types of workloads.

Abstract With the proliferation of various geographic databases on the Internet, we have seen increasing needs for accessing them concurrently and remotely via the Web for high‐level decision making. In this paper, we present Middleware for Efficient Access to Databases through OpenGIS Wrappers (MEADOW), an object‐oriented middleware system we have developed to meet these needs. Current OpenGIS standard addresses many interoperability issues involved in such a global utilization of geographic databases. However, existing Simple Feature specification for CORBA (SFCORBA) implementations of OpenGIS proved to be insufficient for MEADOW. The main problems are the complexity of system development and maintenance, and the inefficiency of accessing remote data servers for processing region queries. We resolved the complexity problem by automatically generating a major portion of the application code, specifically wrappers on database servers and client library modules called transparent access providers. A MEADOW view definition language was developed as a high‐level specification language for this purpose. The efficiency problem was resolved by using a region‐based group prefetching of spatial objects from a geographic region. In addition, we implemented an OID‐based semijoin for efficient global query processing, and a region‐level locking to enhance the level of concurrency among region queries. Copyright © 2002 John Wiley & Sons, Ltd

With the proliferation of various geographic database servers on the Internet, the need to access them simultaneously through the Web arises frequently for high-level decision making. The ongoing OpenGIS standard addresses many of the interoperability issues to make such global utilization of geographic databases possible. Based on the OpenGIS standard, the paper presents an object oriented architecture for the efficient Web based access to multiple geographic databases on the Internet. Called MEADOW, it provides a pair of automatically generated modules: the OpenGIS wrapper on the server side and the matching transparent access provider (TAP) on the client side. In cooperation with the wrapper, TAP supports an application's efficient access to the databases through prefetching and caching of remote objects.

Xmas is an extensible main-memory storage system for high-performance embedded database applications. Xmas not only provides the core functionality of DBMS, such as data persistence, crash recovery, and concurrency control, but also pursues an extensible architecture to meet the requirements from various application areas. One crucial aspect of such extensibility is that an application developer can compose application-specific, high-level operations with a basic set of operations provided by the system. Called composite actions in Xmas, these operations are processed by a customized Xmas server with minimum interaction with application processes, thus improving the overall performance. This paper first presents the architecture and functionality of Xmas, and then demonstrates a simulation of mobile communication service.