Abstract
AMGA (ARDA Metadata Grid Application) is a grid metadata catalogue system that has been developed as a component of the EU FP7 EMI consortium based on the requirements of the HEP (High-Energy Physics) and the biomedical user communities. Currently, AMGA is exploited to manage the metadata in the gBasf2 framework at the Belle II experiment, one of the largest particle physics experiments in the world. In this paper, we present our efforts to optimize the metadata query performance of AMGA to better support the massive MC Campaign of the Belle II experiment. Although AMGA exhibits very outstanding performance for a relatively small amount of data, as the number of directories and the metadata size increase (e.g. hundreds of thousands of directories) during the MC Campaign, AMGA suffers from severe query processing performance degradation. To address this problem, we modified the query search mechanism and the database scheme of AMGA to provide dramatic improvements of metadata search performance and query response time. Throughout our comparative performance analysis of metadata search operations, we show that AMGA can be an optimal solution for a metadata catalogue in a large-scale scientific experimental framework
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