Parallel evaluation of multi-join queries
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Iterators, schedulers, and distributed-memory parallelism
Software—Practice & Experience
Decision Tables: Scalable Classification Exploring RDBMS Capabilities
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Adaptive Query Processing: A Survey
BNCOD 19 Proceedings of the 19th British National Conference on Databases: Advances in Databases
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
IBM Systems Journal
The design and implementation of Grid database services in OGSA-DAI: Research Articles
Concurrency and Computation: Practice & Experience - Grid Performance
Service-Oriented Architecture: Concepts, Technology, and Design
Service-Oriented Architecture: Concepts, Technology, and Design
D^3G: Novel Approaches to Data Statistics, Understanding and Preprocessing on the Grid
AINA '06 Proceedings of the 20th International Conference on Advanced Information Networking and Applications - Volume 01
An integrated query optimization system for data grids
COMPUTE '08 Proceedings of the 1st Bangalore Annual Compute Conference
Databases in grid applications: locality and distribution
BNCOD'05 Proceedings of the 22nd British National conference on Databases: enterprise, Skills and Innovation
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A focus of Grid computing are data intensive applications. Additionally, database management systems (DBMS) are gaining on importance in many scientific disciplines for publication of research results. The employment of Service-oriented-Architecture (SoA) raises the question of how DBMSs and their built-in technologies can be best utilized in such environments. A common way is to pull out all required data for a certain task from a source and process it service side far away from the original source. This approach is characterized by a passive usage of the DBMS as a pure data provider which implies significant overheads. The research effort described in this paper allows an active usage of a DBMS by relocating distributed query processing functionality inside it. Our novel solution utilizes the existing database technology, puts just the interface code at the service level while the data processing code resides at the database level and uses a push mechanism for the result data. The advantages are less overheads and data movement as well as increased data locality. Our proof of concept implementation is evaluated by comparing our distributed query processing prototype working inside popular relational DBMS (Oracle 10g and PostGreSQL 8.3) with a traditional installation of the OGSA-DQP middleware developed for distributed query processing on the Grid.