A Big Data approach for multi-experiment data management. (2019) - Pardi, Silvio; Russo, Guido
Data sharing among similar experiments is made difficult by the usage of ad hoc directory structures, data and metadata naming and by the large variety of access protocols. The Big Data paradigm provides the context to overcome the current heterogeneity problems. In this work, we present a study for a Global Storage Ecosystem designed to manage large and distributed datasets, in the context of physics experiments. The proposed environment is based on HTTP/WebDav protocols, together with modern data searching technologies, according to the Big Data paradigm. The main goal is to aggregate multiple storage areas and to simplify the operations of data retrieval, using Elasticsearch and Apache Lucene library. This platform offers to physicists an effective instrument to simplify the multi-experiment data analysis without knowing a priori the directory format or the data itself. As a proof of concept, we realised a prototype over the ReCaS Supercomputing infrastructure in Napoli.