Extending Binary Large Object Support to Open Grid Services Architecture-Data Access and Integration Middleware Client Toolkit
Kiran Kumar Patnaik and Bollam Nagarjun
DOI : 10.3844/jcssp.2011.832.835
Journal of Computer Science
Volume 7, Issue 6
Problem statement: OGSA-DAI middleware allows data resources to be federated and accessed via web services on the web or within grids or clouds. It provides a client API for writing programs that access the exposed databases. Migrating existing applications to the new technology and using a new API to access the data of DBMS with BLOB is difficult and discouraging. A JDBC Driver is a much convenient alternative to existing mechanism and provides an extension to OGSA-DAI middleware and allows applications to use databases exposed in a grid through the OGSA-DAI 3.0. However, the driver does not support Binary Large Objects (BLOB). Approach: The driver is enhanced to support BLOB using the OGSA-DAI Client API. It transforms the JDBC calls into an OGSA-DAI workflow request and sends it to the server using Web Services (WS). The client API of OGSA-DAI uses activities that are connected to form a workflow and executed using a pipeline. This workflow mechanism is embedded into the driver. The WS container dispatches the request to the OGSA-DAI middleware for processing and the result is then transformed back to an instance of ResultSet implementation using the OGSA-DAI Client API, before it is returned to the user. Results: Test on handling of BLOBs (images, flash files and videos) ranging from size 1 KB to size 2 GB were carried out on Oracle, MySQL and PostgreSQL databases using our enhanced JDBC driver and it performed well. Conclusion: The enhanced JDBC driver now can offer users, with no experience in Grid computing specifically on OGSA-DAI, the possibility to give their applications the ability to access databases exposed on the grid with minimal effort.
© 2011 Kiran Kumar Patnaik and Bollam Nagarjun. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.