Mignify is a platform for collecting, storing and analyzing Big Data harvested from the web. It aims at providing an easy access to focused and structured information extracted from Web data flows. It consists of a distributed crawler, a resource-oriented storage based on HDFS and HBase, and an extraction framework that produces filtered, enriched, and aggregated data from large document collections, including the temporal aspect. The whole system is deployed in an innovative hardware architecture comprising of a high number of small (low-consumption) nodes. This talk will tackle the decisions made along the design and development of the platform, both under a technical and functional perspective. It will introduce the cloud infrastructure, the LTE-like ingestion of the crawler output into HBase/HDFS, and the triggering mechanism of analytics based on a declarative filter/extraction specification. The design choices will be illustrated with a pilot application targeting Daily Web Monitoring in the context of a national domain.
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