Unifying the processing of xml streams and relational data streams

Relational data streams and XML streams have previously provided two separate research foci, but their unified support by a single Data Stream Management System (DSMS) is very desirable from an application viewpoint. In this paper, we propose a simple approach to extend relational DSMSs to support both kinds of streams efficiently. In our Stream Mill system, XML streams expressed as SAX events, can be easily transformed into relational streams, and vice versa. This enables a close cooperation of their query languages, resulting in great power and flexibility. For instance, XQuery can call functions defined in our SQLbased Expressive Stream Language (ESL) using the logical/physical windows that have proved so useful on relational data streams. Many benefits are also gained at the system level, since relational DSMS techniques for load shedding, memory management, query scheduling, approximate query answering, and synopsis maintenance can now be applied to XML streams. Moreover, the many FSA-based optimization techniques developed for XPath and XQuery can be easily and efficiently incorporated in our system. Indeed, we show that YFilter, which is capable of efficiently processing multiple complex XML queries, can be easily integrated in Stream Mill via ESL user-defined and systemdefined aggregates. This approach produces a powerful and flexible system where relational and XML streams are unified and processed efficiently.

Temporal Information Management using XML

A closer integration of XML and database systems is actively pursued by researchers and vendors because of the many practical benefits it offers. Additional special benefits can be achieved on temporal information management — an important application area that represents an unsolved challenge for relationa

Efficient Temporal Coalescing Query Support in Relational Database Systems

Abstract. The interest in and user demand for temporal databases have only increased with time; unfortunately, DBMS vendors and standard groups have not moved aggressively to extend their systems with support for transaction-time or valid-time. This can be partially attributed to the expected major R&D costs to add temporal support to RDBMS by directly extending the database engine. The newly introduced SQL:2003 standards have actually significantly enhanced our ability to support temporal applications in commercial database systems. The long recognized problem of coalescing, which is difficult to support in the framework of SQL:1992, can now be effectively supported in RDBMS. In this paper, we investigate alternatives of temporal coalescing queries under temporal data models in RDBMS. We provide an SQL:2003-based query algorithm and a native relational user defined aggregates (UDA) approach – both approaches only require a single scan of the database. We conclude that temporal queries can be best supported by OLAP functions supported in the current SQL:2003 standards. These new findings demonstrate that the current RDBMSs are mature enough to directly support efficient temporal queries, and provide a new paradigm for temporal database research and implementation.

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