Coupling of FDBS and WfMS for Integrating Database and Application Systems: Architecture, Complexity, Performance
With the emergence of so-called 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 novel and extended kind of integration. In particular, so-called federated functions combining functionality of one or more application system calls (local functions) have to be integrated. Starting with the overall architecture, we explain the functionality and cooperation of its core components: a federated database system and, connected via a wrapper, a workflow management system composing and executing the federated functions. Due to missing wrapper support in commercial products, we also explore the use of user-defined table functions. In addition to our workflow solution, we present several alternative architectures where the federated database system directly controls the execution of the requested local functions. These two different approaches are primarily compared w.r.t. their mapping complexity and their performance.
KeywordsLocal Function Function Call Table Function Query Optimization Function Access
Unable to display preview. Download preview PDF.
- 4.Hergula, K., Härder, T.: A Middleware Approach for Combining Heterogeneous Data Sources-Integration of Generic Queries and Predefined Function Access. Proc. 1st Int. Conf. on Web Information Systems Engineering, Hongkong (2000) 22–29Google Scholar
- 5.Leymann, F., Roller, D.: Production Workflow: Concepts and Techniques, Prentice Hall (2000)Google Scholar
- 6.ISO & ANSI: Database Languages-SQL-Part 9: Management of External Data, Working Draft (2000)Google Scholar
- 7.M. Tork Roth, P. Schwarz: Don’t Scrap It, Wrap It! A Wrapper Architecture for Legacy Data Sources. Proc. 23rd Int. Conf. on Very Large Data Bases, Athens (1997) 266–275Google Scholar
- 8.Levy, A.Y., Rajaraman, A., Ordille, J.J.: Querying Heterogeneous Information Sources Using Source Descriptions. Proc. 22nd Int. Conf. on Very Large Data Bases, Bombay (1996) 251–262Google Scholar
- 9.Papakonstantinou, Y., Garcia-Molina, H., Widom, J.: Object Exchange Across Heterogeneous Information Sources. Proc. 11th Int. Conf. on Data Engineering, Taipei (1995) 251–260Google Scholar
- 10.Chaudhuri, S., Shim, K.: Query Optimization in the Presence of Foreign Functions. Proc. 19th Int. Conf. on Very Large Data Bases, Dublin (1993) 529–542Google Scholar
- 11.Florescu, D., Levy, A., Manolescu, I., Suciu, D.: Query Optimization in the Presence of Limited Access Patterns. Proc. ACM SIGMOD Int. Conf. on Management of Data, Philadelphia (1999) 311–322Google Scholar
- 12.Garcia-Molina, H., Labio, W., Yerneni, R.: Capability-Sensitive Query Processing on Internet Sources. Proc. 15th Int. Conf. on Data Engineering, Sidney (1999) 50–59Google Scholar
- 13.Reinwald, B., Pirahesh, H., Krishnamoorthy, G., Lapis, G., Tran, B., Vora, S.: Heterogeneous Query Processing through SQL Table Functions. Proc. 15th Int. Conf. on Data Engineering, Sidney (1999) 366–373Google Scholar
- 14.Hergula, K., Härder, T.: How Foreign Function Integration Conquers Heterogeneous Query Processing. Proc. 10th Int. Conf. on Information and Knowledge Management, Atlanta (2001) 215–222Google Scholar